From fc220ae98500891d303121d6167dc743a5911503 Mon Sep 17 00:00:00 2001 From: jack Date: Fri, 23 Jan 2026 18:17:52 +0800 Subject: [PATCH] ++ --- alpha_template.py | 418 +++++++++ generated_alpha/2026/01/22/1.txt | 164 ++++ ...pseek-ai_DeepSeek-V3.1-Terminus_174736.txt | 105 +++ ...wen_Qwen3-VL-235B-A22B-Instruct_174833.txt | 44 + .../2026/01/23/template_output.txt | 500 +++++++++++ main.py | 4 +- .../01/22/manual_prompt_20260122135326.txt | 520 +++++++++++ .../01/22/manual_prompt_20260122150453.txt | 811 +++++++++++++++++ .../01/22/manual_prompt_20260122174534.txt | 812 ++++++++++++++++++ optimize_alpha.py | 58 -- planning_post_alpha.txt | 744 ++++++++++------ prepare_prompt/alpha_prompt.txt | 7 +- prepare_prompt/keys_text.txt | 2 +- template_output.txt | 500 +++++++++++ 手动生成模板提示词.txt | 69 ++ 15 files changed, 4450 insertions(+), 308 deletions(-) create mode 100644 alpha_template.py create mode 100644 generated_alpha/2026/01/22/1.txt create mode 100644 generated_alpha/2026/01/22/Pro_deepseek-ai_DeepSeek-V3.1-Terminus_174736.txt create mode 100644 generated_alpha/2026/01/22/Qwen_Qwen3-VL-235B-A22B-Instruct_174833.txt create mode 100644 generated_alpha/2026/01/23/template_output.txt create mode 100644 manual_prompt/2026/01/22/manual_prompt_20260122135326.txt create mode 100644 manual_prompt/2026/01/22/manual_prompt_20260122150453.txt create mode 100644 manual_prompt/2026/01/22/manual_prompt_20260122174534.txt delete mode 100644 optimize_alpha.py create mode 100644 template_output.txt create mode 100644 手动生成模板提示词.txt diff --git a/alpha_template.py b/alpha_template.py new file mode 100644 index 0000000..b2d46fe --- /dev/null +++ b/alpha_template.py @@ -0,0 +1,418 @@ +import os +import random +import sys +import re +import pandas as pd +from sqlalchemy import create_engine +from itertools import product + +# ==================== 全局配置 ==================== +# 添加项目路径 +sys.path.append(os.path.join(os.path.abspath(__file__).split('AlphaGenerator')[0] + 'AlphaGenerator')) +PROJECT_PATH = os.path.join(os.path.abspath(__file__).split('AlphaGenerator')[0] + 'AlphaGenerator') +PREPARE_PROMPT = os.path.join(str(PROJECT_PATH), 'prepare_prompt') +SQLITE_PATH = os.path.join(str(PREPARE_PROMPT), 'data_sets.db') + +# Alpha模板 - 支持 语法 +ALPHA_TEMPLATE = "ts_covariance(, , )" + +# 窗口列表 +WINDOW_LIST = [5, 20, 60, 250] + +# 运行模式：1=name搜索, 2=description搜索, 3=混合模式 +MODE = 2 + +# 数据库配置 +REGION = 'USA' +UNIVERSE = 'TOP3000' + +MAX_OUTPUT_COUNT = 1000 +ACTUAL_GENERATION_COUNT = 500 + +# ==================== 初始化 ==================== +engine = create_engine(f"sqlite:///{SQLITE_PATH}") +OUTPUT_FILE = "template_output.txt" + + +def extract_keywords_from_template(template): + """ + 从模板中提取所有 + 支持单个关键词和多关键词语法 + 返回结构: [{'param_index': i, 'keywords': [kw1, kw2, ...], 'original': ''}, ...] + """ + # 匹配 <> 中的内容，支持竖线分隔的多个关键词 + pattern = r'<([^<>]+)>' + all_matches = re.findall(pattern, template) + + keyword_params = [] + + for i, match in enumerate(all_matches): + # 分割竖线分隔的关键词 + if '|' in match: + keywords = [kw.strip() for kw in match.split('|') if kw.strip()] + else: + keywords = [match.strip()] + + # 检查是否包含'window'（特殊处理） + if 'window' in keywords: + has_window = True + # 从普通关键词中移除window + keywords = [kw for kw in keywords if kw != 'window'] + else: + has_window = False + + param_info = { + 'param_index': i, + 'keywords': keywords, + 'original': f'<{match}>', + 'has_window': has_window + } + + keyword_params.append(param_info) + + print(f"从模板解析到 {len(keyword_params)} 个参数:") + for param in keyword_params: + if param['has_window']: + print(f" 参数{param['param_index'] + 1}: {param['original']} (包含window)") + else: + print(f" 参数{param['param_index'] + 1}: {param['original']}") + print(f" 关键词列表: {param['keywords']}") + + return keyword_params + + +def search_keywords_in_database(keyword_params, search_field): + """ + 搜索所有参数的所有关键词 + search_field: 'name' 或 'description' + 返回结构: {参数索引: [匹配的指标名列表]} + 如果任何参数的所有关键词都没有匹配结果，返回None + """ + if not keyword_params: + return {} + + results = {} + all_missing_params = [] + + for param in keyword_params: + param_idx = param['param_index'] + param_keywords = param['keywords'] + + if not param_keywords: + # 没有普通关键词，只有window + results[param_idx] = [] + continue + + print(f"\n 搜索参数{param_idx + 1}的关键词:") + print(f" 搜索字段: {search_field}") + + param_all_results = [] + param_missing_keywords = [] + + for keyword in param_keywords: + # 构建查询 + if search_field == 'name': + query = """ + SELECT DISTINCT name + FROM data_sets + WHERE region = ? + AND universe = ? + AND LOWER(name) LIKE LOWER(?) \ + """ + else: # description + query = """ + SELECT DISTINCT name + FROM data_sets + WHERE region = ? + AND universe = ? + AND LOWER(description) LIKE LOWER(?) \ + """ + + # 使用 % 进行模糊匹配 + like_pattern = f'%{keyword}%' + + print(f" 关键词: '{keyword}'，模式: '{like_pattern}'") + + try: + df = pd.read_sql_query( + query, + engine, + params=(REGION, UNIVERSE, like_pattern) + ) + + names = df['name'].tolist() + + if names: + param_all_results.extend(names) # 合并所有关键词的结果 + print(f" ✓ 找到 {len(names)} 个结果") + else: + param_missing_keywords.append(keyword) + print(f" ✗ 没有匹配结果") + + except Exception as e: + print(f" ✗ 搜索出错: {e}") + param_missing_keywords.append(keyword) + + # 去重 + param_all_results = list(set(param_all_results)) + + if param_all_results: + results[param_idx] = param_all_results + print(f" 参数{param_idx + 1}总计找到 {len(param_all_results)} 个唯一结果") + if param_all_results: + print(f" 示例: {param_all_results[:3]}{'...' if len(param_all_results) > 3 else ''}") + else: + if param_missing_keywords: + print(f" ✗ 参数{param_idx + 1}的所有关键词都没有匹配结果:") + for kw in param_missing_keywords: + print(f" - {kw}") + all_missing_params.append(param_idx) + + # 如果有任何参数的所有关键词都没有匹配结果，返回None + if all_missing_params: + print(f"\n错误: 以下参数在{search_field}字段中没有匹配到任何结果:") + for param_idx in all_missing_params: + param_keywords = keyword_params[param_idx]['keywords'] + print(f" 参数{param_idx + 1}: <{'|'.join(param_keywords)}>") + return None + + return results + + +def generate_alpha_combinations(template, keyword_params, search_results): + """ + 生成Alpha表达式组合 + keyword_params: 参数信息列表 + search_results: {参数索引: [匹配的指标名列表]} + """ + if not search_results and not any(p['has_window'] for p in keyword_params): + return [template] # 没有需要替换的内容 + + # 准备所有参数的替换项 + all_param_replacements = [] + param_keys = [] + + # 按参数顺序处理 + for param in sorted(keyword_params, key=lambda x: x['param_index']): + param_idx = param['param_index'] + + if param_idx in search_results and search_results[param_idx]: + # 有普通关键词的搜索结果 + all_param_replacements.append(search_results[param_idx]) + param_keys.append(param['original']) + elif param['has_window']: + # 只有window，没有普通关键词 + all_param_replacements.append([str(w) for w in WINDOW_LIST]) + param_keys.append(param['original']) + else: + # 没有搜索结果也没有window（不应该发生） + print(f"警告: 参数{param_idx + 1}没有可替换的内容") + all_param_replacements.append([param['original']]) # 保留原样 + param_keys.append(param['original']) + + # 生成所有组合 + print(f"\n生成组合...") + print(f"替换键 ({len(param_keys)}个参数): {param_keys}") + + # 计算总组合数 + total_combinations = 1 + for replacement_list in all_param_replacements: + total_combinations *= len(replacement_list) + + print(f"预计生成 {total_combinations} 个组合") + + # 使用笛卡尔积生成所有组合 + combinations = [] + count = 0 + + for values in product(*all_param_replacements): + result = template + for key, value in zip(param_keys, values): + result = result.replace(key, str(value)) + combinations.append(result) + count += 1 + + # 进度显示 + if total_combinations > 1000 and count % 1000 == 0: + print(f" 已生成 {count}/{total_combinations} 个组合...") + + # 去重 + unique_combinations = list(set(combinations)) + + print(f"实际生成 {len(combinations)} 个组合，去重后 {len(unique_combinations)} 个") + + return unique_combinations + + +def run_mode(mode, template): + """ + 运行指定模式 + 如果任何参数的所有关键词都没有匹配结果，返回None + """ + print(f"\n{'=' * 60}") + print(f"运行模式 {mode}") + print(f"模板: {template}") + print(f"{'=' * 60}") + + # 解析模板 + keyword_params = extract_keywords_from_template(template) + + if not keyword_params: + print("错误: 模板中没有找到任何参数") + return None + + all_results = [] + + # 模式1: name搜索 + if mode in [1, 3]: + print(f"\n[模式1: name字段搜索]") + print("-" * 40) + + # 搜索name字段 + search_results = search_keywords_in_database(keyword_params, 'name') + + if search_results is None: + print(f"模式1失败: 有参数在name字段中没有匹配结果") + if mode == 1: # 如果是模式1，直接退出 + return None + # 如果是模式3，继续尝试模式2 + else: + # 生成组合 + combinations = generate_alpha_combinations(template, keyword_params, search_results) + all_results.extend(combinations) + + print(f"模式1生成 {len(combinations)} 个表达式") + + # 模式2: description搜索 + if mode in [2, 3]: + print(f"\n[模式2: description字段搜索]") + print("-" * 40) + + # 搜索description字段 + search_results = search_keywords_in_database(keyword_params, 'description') + + if search_results is None: + print(f"模式2失败: 有参数在description字段中没有匹配结果") + if mode == 2: # 如果是模式2，直接退出 + return None + # 如果是模式3，继续（可能模式1已经成功） + else: + # 生成组合 + combinations = generate_alpha_combinations(template, keyword_params, search_results) + all_results.extend(combinations) + + print(f"模式2生成 {len(combinations)} 个表达式") + + # 检查是否有结果 + if not all_results: + print(f"\n错误: 没有生成任何表达式") + return None + + # 去重 + unique_results = list(set(all_results)) + print(f"\n总计生成 {len(all_results)} 个表达式，去重后 {len(unique_results)} 个") + + return unique_results + + +def save_results(results, filename): + """ + 保存结果到文件 + 如果结果数量超过MAX_OUTPUT_COUNT，随机抽取ACTUAL_GENERATION_COUNT个结果 + """ + if not results: + print("没有结果需要保存") + return False + + total_count = len(results) + + # 处理结果数量限制 + if total_count > MAX_OUTPUT_COUNT: + print(f"\n警告: 生成结果 {total_count} 条，超过阈值 {MAX_OUTPUT_COUNT} 条") + print(f"将随机抽取 {ACTUAL_GENERATION_COUNT} 条结果保存") + + # 随机抽取（不使用固定种子，每次运行结果不同） + selected_results = random.sample(results, ACTUAL_GENERATION_COUNT) + + # 统计信息 + print(f"随机抽取 {len(selected_results)} 条结果") + save_results_list = selected_results + else: + save_results_list = results + + try: + with open(filename, 'w', encoding='utf-8') as f: + for alpha in save_results_list: + f.write(alpha + '\n') + + print(f"\n已保存 {len(save_results_list)} 个Alpha表达式到: {filename}") + + # 显示前10个结果 + print(f"\n前10个结果:") + print("-" * 60) + for i, alpha in enumerate(save_results_list[:10], 1): + print(f"{i:3d}. {alpha}") + + if len(save_results_list) > 10: + print(f"... 还有 {len(save_results_list) - 10} 个表达式") + + # 如果进行了随机抽取，显示统计信息 + if total_count > MAX_OUTPUT_COUNT: + print(f"\n统计信息:") + print(f" - 原始生成: {total_count} 条") + print(f" - 随机抽取: {ACTUAL_GENERATION_COUNT} 条") + print(f" - 抽取比例: {ACTUAL_GENERATION_COUNT / total_count * 100:.1f}%") + + return True + + except Exception as e: + print(f"保存文件时出错: {e}") + return False + + +def main(): + """ + 主函数 + """ + print("=" * 60) + print("Alpha表达式生成器 v2.0 - 支持多关键词参数") + print("=" * 60) + print(f"数据库: {SQLITE_PATH}") + print(f"区域: {REGION}, 股票池: {UNIVERSE}") + print(f"模板: {ALPHA_TEMPLATE}") + print(f"窗口列表: {WINDOW_LIST}") + print(f"运行模式: {MODE}") + print(f"输出文件: {OUTPUT_FILE}") + print("语法说明: 使用 支持多关键词") + print("=" * 60) + + # 检查数据库连接 + try: + # 测试连接 + test_df = pd.read_sql_query("SELECT 1", engine) + print("数据库连接成功") + except Exception as e: + print(f"数据库连接失败: {e}") + print(f"请检查数据库路径: {SQLITE_PATH}") + return + + # 运行指定模式 + results = run_mode(MODE, ALPHA_TEMPLATE) + + # 保存结果 + if results: + save_results(results, OUTPUT_FILE) + else: + print("\n程序终止: 有参数没有匹配到数据，请检查关键词或模板") + sys.exit(1) + + +if __name__ == '__main__': + try: + main() + except Exception as e: + print(f"程序运行出错: {e}") + import traceback + + traceback.print_exc() + sys.exit(1) \ No newline at end of file diff --git a/generated_alpha/2026/01/22/1.txt b/generated_alpha/2026/01/22/1.txt new file mode 100644 index 0000000..612bd67 --- /dev/null +++ b/generated_alpha/2026/01/22/1.txt @@ -0,0 +1,164 @@ +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095)), subindustry), market_cap_bucket) +winsorize(zscore(ts_mean(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, r_and_d_expense_total_fast_d1)), 1095)), 4) +rank(multiply(group_zscore(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), subindustry), sign(ts_delta(anl82_nety_profitability_profitability8, 30)))) +group_neutralize(rank(ts_zscore(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), inverse(anl10_netinnovation_score_fy1_2515)), 1095)), market_cap_bucket) +zscore(winsorize(ts_mean(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), reverse(anl82_nety_deltaprofitability_profitability4)), 1095), 4)) +rank(add(group_rank(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), subindustry), group_rank(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), market_cap_bucket))) +group_zscore(ts_quantile(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), anl10_epsinnovation_score_fy1), 1095), subindustry) +winsorize(ts_mean(divide(multiply(r_and_d_expense_balance, sign(ts_delta(mdl211_nety_profitability_profitability3, 60))), r_and_d_expense_total_fast_d1), 1095), 4) +rank(group_neutralize(ts_zscore(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, r_and_d_expense_total_fast_d1)), 1095), market_cap_bucket)) +zscore(multiply(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), reverse(anl82_opry_profitability_profitability6))) +group_rank(ts_decay_linear(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), anl10_preinnovation_score_fy2_1386), 1095), subindustry) +winsorize(add(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), reverse(ts_mean(mdl211_saly_profitability_profitability2, 1095))), 4) +rank(zscore(multiply(group_zscore(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), subindustry), sign(ts_delta(anl82_prey_profitability_profitability8, 90))))) +ts_mean(divide(multiply(r_and_d_expense_balance, inverse(anl10_dpsinnovation_score_fy1_1554)), r_and_d_expense_total_fast_d1), 1095) +group_neutralize(winsorize(ts_zscore(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), mdl211_opry_profitability_profitability11), 1095), 4), market_cap_bucket) +rank(ts_quantile(add(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), reverse(anl82_saly_profitability_profitability3)), 1095)) +zscore(group_zscore(ts_mean(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), reverse(anl82_ebty_profitability_profitability5)), 1095), subindustry)) +winsorize(multiply(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), sign(ts_delta(mdl211_netq_profitability_profitability1, 120))), 4) +group_rank(ts_zscore(divide(multiply(r_and_d_expense_balance, anl10_netinnovation_score_fq1_2521), r_and_d_expense_total_fast_d1), 1095), market_cap_bucket) +rank(add(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), reverse(ts_mean(anl82_oprq_profitability_profitability4, 1095)))) +ts_decay_linear(multiply(group_zscore(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), subindustry), inverse(mdl211_ebty_profitability_profitability7)), 1095) +zscore(winsorize(add(group_rank(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), subindustry), reverse(anl82_netq_profitability_profitability2)), 4)) +group_neutralize(rank(ts_mean(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), sign(ts_delta(anl82_preq_profitability_profitability12, 150))), 1095)), market_cap_bucket) +winsorize(ts_quantile(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), anl10_cpsinnovation_score_fy1), 1095), 4) +rank(zscore(multiply(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), reverse(mdl211_salq_profitability_profitability3)))) +group_zscore(ts_zscore(add(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), inverse(anl82_ebtq_profitability_profitability4)), 1095), subindustry) +ts_mean(divide(multiply(r_and_d_expense_balance, sign(ts_delta(mdl211_oprq_profitability_profitability1, 180))), r_and_d_expense_total_fast_d1), 1095) +rank(group_neutralize(winsorize(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), anl10_nerinnovation_score_fq2_1997), 4), market_cap_bucket)) +zscore(ts_decay_linear(multiply(group_zscore(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), subindustry), reverse(anl82_salq_profitability_profitability5)), 1095)) +winsorize(add(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), sign(ts_delta(mdl211_prey_profitability_profitability6, 210))), 4) +group_rank(ts_quantile(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), anl10_preinnovation_score_fq2_1369), 1095), market_cap_bucket) +rank(multiply(zscore(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095)), reverse(anl82_nety_deltaprofitability_profitability8))) +ts_zscore(group_zscore(add(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), inverse(mdl211_ebtq_profitability_profitability2)), 1095), subindustry) +group_neutralize(winsorize(multiply(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), sign(ts_delta(anl82_opry_deltaprofitability_profitability3, 240))), 4), market_cap_bucket) +zscore(rank(add(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), reverse(mdl211_nety_profitability_profitability9)))) +winsorize(ts_decay_linear(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), anl10_dpsinnovation_score_fy2_1544), 1095), 4) +rank(group_zscore(ts_mean(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), inverse(anl82_ebty_deltaprofitability_profitability6)), 1095), subindustry)) +ts_quantile(add(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), sign(ts_delta(mdl211_saly_deltaprofitability_profitability2, 270))), 1095) +group_neutralize(zscore(multiply(winsorize(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 4), anl10_cpsinnovation_score_fy2)), market_cap_bucket) +rank(winsorize(add(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), reverse(anl82_netq_deltaprofitability_profitability3)), 4)) +zscore(ts_zscore(multiply(group_rank(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), subindustry), sign(ts_delta(mdl211_oprq_deltaprofitability_profitability2, 300))), 1095)) +ts_mean(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), inverse(anl10_ebiinnovation_score_fq2_2599)), 1095) +group_rank(winsorize(multiply(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), reverse(mdl211_preq_profitability_profitability7)), 4), market_cap_bucket) +rank(zscore(add(group_zscore(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), subindustry), sign(ts_delta(anl82_prey_deltaprofitability_profitability12, 330))))) +winsorize(ts_decay_linear(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), anl10_salinnovation_score_fq2_1686), 1095), 4) +group_neutralize(ts_quantile(add(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), reverse(mdl211_ebty_deltaprofitability_profitability4)), 1095), market_cap_bucket) +zscore(multiply(rank(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1)), sign(ts_delta(anl82_ebtq_deltaprofitability_profitability10, 360)))) +rank(ts_zscore(winsorize(multiply(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), anl10_ebtinnovation_score_fy2_1040), 4), 1095)) +group_zscore(add(ts_mean(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), 1095), inverse(mdl211_nety_deltaprofitability_profitability11)), subindustry) +ts_decay_linear(winsorize(multiply(group_rank(divide(r_and_d_expense_balance, r_and_d_expense_total_fast_d1), subindustry), reverse(anl82_saly_deltaprofitability_profitability6)), 4), 1095) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl82_saly_profitability_profitability11, anl82_saly_profitability_profitability6), anl82_saly_profitability_profitability11), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(mdl211_ebty_profitability_profitability11, mdl211_ebty_profitability_profitability7), mdl211_ebty_profitability_profitability11), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl82_nety_profitability_profitability9, anl82_nety_profitability_profitability4), anl82_nety_profitability_profitability9), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(mdl211_nety_profitability_profitability12, mdl211_nety_profitability_profitability4), mdl211_nety_profitability_profitability12), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl82_prey_deltaprofitability_profitability12, anl82_prey_deltaprofitability_profitability6), anl82_prey_deltaprofitability_profitability12), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(mdl211_prey_deltaprofitability_profitability12, mdl211_prey_deltaprofitability_profitability6), mdl211_prey_deltaprofitability_profitability12), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl82_opry_deltaprofitability_profitability7, anl82_opry_deltaprofitability_profitability3), anl82_opry_deltaprofitability_profitability7), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(mdl211_opry_profitability_profitability7, mdl211_opry_profitability_profitability3), mdl211_opry_profitability_profitability7), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl82_salq_profitability_profitability9, anl82_salq_profitability_profitability3), anl82_salq_profitability_profitability9), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(mdl211_salq_profitability_profitability9, mdl211_salq_profitability_profitability3), mdl211_salq_profitability_profitability9), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl82_ebtq_profitability_profitability11, anl82_ebtq_profitability_profitability4), anl82_ebtq_profitability_profitability11), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(mdl211_ebtq_profitability_profitability12, mdl211_ebtq_profitability_profitability4), mdl211_ebtq_profitability_profitability12), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl82_netq_deltaprofitability_profitability10, anl82_netq_deltaprofitability_profitability2), anl82_netq_deltaprofitability_profitability10), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(mdl211_netq_profitability_profitability9, mdl211_netq_profitability_profitability1), mdl211_netq_profitability_profitability9), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl82_preq_profitability_profitability12, anl82_preq_profitability_profitability2), anl82_preq_profitability_profitability12), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(mdl211_preq_profitability_profitability11, mdl211_preq_profitability_profitability7), mdl211_preq_profitability_profitability11), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl82_oprq_deltaprofitability_profitability6, anl82_oprq_deltaprofitability_profitability1), anl82_oprq_deltaprofitability_profitability6), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(mdl211_oprq_profitability_profitability7, mdl211_oprq_profitability_profitability1), mdl211_oprq_profitability_profitability7), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_2_netprofit_af_matrix_all_median, pv87_2_netprofit_af_matrix_all_low), pv87_2_netprofit_af_matrix_all_median), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_2_operatingprofit_af_matrix_all_mean, pv87_2_operatingprofit_af_matrix_all_low), pv87_2_operatingprofit_af_matrix_all_mean), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_2_pretaxprofit_af_matrix_all_median, pv87_2_pretaxprofit_af_matrix_all_low), pv87_2_pretaxprofit_af_matrix_all_median), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_2_netprofit_qf_matrix_all_median, pv87_2_netprofit_qf_matrix_all_low), pv87_2_netprofit_qf_matrix_all_median), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_2_operatingprofit_qf_matrix_all_mean, pv87_2_operatingprofit_qf_matrix_all_low), pv87_2_operatingprofit_qf_matrix_all_mean), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_2_pretaxprofit_qf_matrix_all_median, pv87_2_pretaxprofit_qf_matrix_all_low), pv87_2_pretaxprofit_qf_matrix_all_median), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_2_netprofit_rep_af_matrix_all_median, pv87_2_netprofit_rep_af_matrix_all_low), pv87_2_netprofit_rep_af_matrix_all_median), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_2_pretaxprofit_rep_af_matrix_all_median, pv87_2_pretaxprofit_rep_af_matrix_all_low), pv87_2_pretaxprofit_rep_af_matrix_all_median), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_2_netprofit_rep_qf_matrix_all_mean, pv87_2_netprofit_rep_qf_matrix_all_low), pv87_2_netprofit_rep_qf_matrix_all_mean), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_2_pretaxprofit_rep_qf_matrix_all_mean, pv87_2_pretaxprofit_rep_qf_matrix_all_low), pv87_2_pretaxprofit_rep_qf_matrix_all_mean), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fnd3_a_grossprofit, fnd3_a_opeexpenses), fnd3_a_grossprofit), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fnd3_q_grossprofit, fnd3_q_opeexpenses_fast_d1), fnd3_q_grossprofit), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl44_netprofit_value, selling_general_admin_expense), anl44_netprofit_value), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl44_pretaxprofit_value, r_and_d_expense_balance), anl44_pretaxprofit_value), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl44_operatingprofit_best_fiscal_period_dt, r_and_d_expense_total_fast_d1), anl44_operatingprofit_best_fiscal_period_dt), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl49_netprofit, r_and_d_expense_balance_fast_d1), anl49_netprofit), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(anl49_backfill_netprofit, quarterly_r_and_d_expense_total), anl49_backfill_netprofit), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fn_profit_loss_a, depreciation_and_amortization_expense), fn_profit_loss_a), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fn_profit_loss_q, depreciation_expense_total), fn_profit_loss_q), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(operating_profit_total_2, bad_debt_expense), operating_profit_total_2), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(gross_profit_total, total_rental_expense), gross_profit_total), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(operating_profit_pre_tax, other_unusual_income_expense), operating_profit_pre_tax), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(interest_expense, annual_income_tax_expense_2), interest_expense), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_interest_expense_actual, pv87_interest_expense_consensus_high), pv87_interest_expense_actual), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_ann_matrix_interest_expense_estimate_high, pv87_ann_matrix_interest_expense_estimate_std), pv87_ann_matrix_interest_expense_estimate_high), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(pv87_qtr_matrix_interest_expense_estimate_mean, pv87_qtr_matrix_interest_expense_estimate_scale), pv87_qtr_matrix_interest_expense_estimate_mean), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fnd72_pit_or_is_a_is_int_expense, fnd72_pit_or_is_a_is_expense_stock_based_comp), fnd72_pit_or_is_a_is_int_expense), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fnd72_pit_or_is_q_is_int_expense, fnd72_pit_or_is_q_is_expense_stock_based_comp), fnd72_pit_or_is_q_is_int_expense), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fnd72_pit_or_cr_a_cash_flow_to_int_expense, fnd72_pit_or_is_a_is_oprb_expense_income), fnd72_pit_or_cr_a_cash_flow_to_int_expense), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fnd72_pit_or_cr_q_cash_flow_to_int_expense, fnd72_pit_or_is_q_is_pension_expense_income), fnd72_pit_or_cr_q_cash_flow_to_int_expense), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fnd72_pit_or_bs_a_bs_curr_rental_expense, fnd72_s_pit_or_is_a2_is_oprb_expense_income), fnd72_pit_or_bs_a_bs_curr_rental_expense), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fnd72_s_pit_or_bs_a2_bs_curr_rental_expense, fnd72_s_pit_or_is_a2_is_pension_expense_income), fnd72_s_pit_or_bs_a2_bs_curr_rental_expense), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fnd72_s_pit_or_is_q_is_expense_stock_based_comp, fnd72_s_pit_or_is_q_is_pension_expense_income), fnd72_s_pit_or_is_q_is_expense_stock_based_comp), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fn_allocated_share_based_compensation_expense_a, fn_allocated_share_based_compensation_expense_q), fn_allocated_share_based_compensation_expense_a), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fn_prepaid_expense_a, fn_prepaid_expense_q), fn_prepaid_expense_a), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(fn_def_income_tax_expense_q, current_tax_expense), fn_def_income_tax_expense_q), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(income_tax_expense_3, total_tax_expense_2), income_tax_expense_3), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(annual_equity_compensation_expense, quarterly_equity_compensation_expense), annual_equity_compensation_expense), 750), 2), 4) + +group_neutralize(group_neutralize(ts_mean(divide(subtract(annual_income_tax_expense_fast_d1, quarterly_income_tax_expense_fast_d1), annual_income_tax_expense_fast_d1), 750), 2), 4) \ No newline at end of file diff --git a/generated_alpha/2026/01/22/Pro_deepseek-ai_DeepSeek-V3.1-Terminus_174736.txt b/generated_alpha/2026/01/22/Pro_deepseek-ai_DeepSeek-V3.1-Terminus_174736.txt new file mode 100644 index 0000000..e979218 --- /dev/null +++ b/generated_alpha/2026/01/22/Pro_deepseek-ai_DeepSeek-V3.1-Terminus_174736.txt @@ -0,0 +1,105 @@ +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, depreciation_and_amortization_expense), 756)) * sign(ts_delta(anl49_netprofit, 252)), sector), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_balance, depreciation_expense_total), 756)) * sign(ts_delta(anl44_netprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_saly_profitability_profitability6), 756)) * sign(ts_delta(anl49_netprofit, 252)), sector), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, selling_general_admin_expense), 756)) * ts_rank(anl10_prrinnovation_score_fy1_2565, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(depreciation_and_amortization_expense, r_and_d_expense_total_fast_d1), 756)) * sign(ts_delta(anl44_operatingprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, fnd3_a_opeexpenses), 756)) * rank(anl10_ebtinnovation_score_fy2_1040), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_balance, anl82_ebty_profitability_profitability11), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_nety_profitability_profitability8), 756)) * ts_rank(anl10_netinnovation_score_fy1_2515, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, operating_profit), 756)) * sign(ts_delta(anl44_pretaxprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_opry_profitability_profitability6), 756)) * rank(anl10_dpsinnovation_score_fy1_1554), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_balance, anl82_salq_profitability_profitability3), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_prey_profitability_profitability12), 756)) * ts_rank(anl10_ebiinnovation_score_fq2_2599, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(depreciation_expense_total, r_and_d_expense_balance), 756)) * sign(ts_delta(anl44_netprofit_rep_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_ebtq_profitability_profitability1), 756)) * rank(anl10_preinnovation_score_fy2_1386), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_oprq_profitability_profitability11), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_balance, anl82_nety_profitability_profitability4), 756)) * ts_rank(anl10_netinnovation_score_fq1_2521, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_saly_profitability_profitability11), 756)) * sign(ts_delta(anl44_operatingprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_preq_profitability_profitability2), 756)) * rank(anl10_dpsinnovation_score_fq2_1557), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_balance, anl82_ebty_profitability_profitability5), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_salq_profitability_profitability7), 756)) * ts_rank(anl10_prrinnovation_score_fy1_2565, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(depreciation_and_amortization_expense, anl82_opry_profitability_profitability9), 756)) * sign(ts_delta(anl44_pretaxprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_nety_profitability_profitability9), 756)) * rank(anl10_ebtinnovation_score_fy2_1040), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_balance, anl82_saly_profitability_profitability3), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_ebtq_profitability_profitability10), 756)) * ts_rank(anl10_netinnovation_score_fq2_2539, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_oprq_profitability_profitability5), 756)) * sign(ts_delta(anl44_netprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_balance, anl82_prey_profitability_profitability6), 756)) * rank(anl10_ebiinnovation_score_fq2_2599), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_salq_profitability_profitability9), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_nety_profitability_profitability12), 756)) * ts_rank(anl10_preinnovation_score_fq2_1369, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(depreciation_expense_total, anl82_ebty_profitability_profitability8), 756)) * sign(ts_delta(anl44_operatingprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_balance, anl82_opry_profitability_profitability4), 756)) * rank(anl10_dpsinnovation_score_fy2_1544), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_saly_profitability_profitability8), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_preq_profitability_profitability9), 756)) * ts_rank(anl10_netinnovation_score_fy1_2515, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_balance, anl82_ebtq_profitability_profitability5), 756)) * sign(ts_delta(anl44_pretaxprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_nety_profitability_profitability2), 756)) * rank(anl10_prrinnovation_score_fy1_2565), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_oprq_profitability_profitability8), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_balance, anl82_saly_profitability_profitability10), 756)) * ts_rank(anl10_ebtinnovation_score_fy2_1040, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(depreciation_and_amortization_expense, anl82_prey_profitability_profitability8), 756)) * sign(ts_delta(anl44_netprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_ebty_profitability_profitability4), 756)) * rank(anl10_netinnovation_score_fq1_2521), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_balance, anl82_salq_profitability_profitability4), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_opry_profitability_profitability12), 756)) * ts_rank(anl10_ebiinnovation_score_fq2_2599, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_nety_profitability_profitability11), 756)) * sign(ts_delta(anl44_operatingprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_balance, anl82_ebtq_profitability_profitability11), 756)) * rank(anl10_preinnovation_score_fy2_1386), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_saly_profitability_profitability6), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_preq_profitability_profitability12), 756)) * ts_rank(anl10_dpsinnovation_score_fq1_1568, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(depreciation_expense_total, anl82_oprq_profitability_profitability7), 756)) * sign(ts_delta(anl44_pretaxprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_balance, anl82_nety_profitability_profitability8), 756)) * rank(anl10_netinnovation_score_fq2_2539), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_ebty_profitability_profitability9), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_salq_profitability_profitability8), 756)) * ts_rank(anl10_prrinnovation_score_fy1_2565, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_balance, anl82_opry_profitability_profitability7), 756)) * sign(ts_delta(anl44_netprofit_value, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_nety_profitability_profitability4), 756)) * rank(anl10_ebtinnovation_score_fy2_1040), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(r_and_d_expense_total_fast_d1, anl82_ebtq_profitability_profitability8), 756)) * sign(ts_delta(anl49_netprofit, 252)), industry), size_group) + +group_neutralize(group_neutralize(- rank(ts_mean(divide(r_and_d_expense_balance, anl82_saly_profitability_profitability9), 756)) * ts_rank(anl10_ebiinnovation_score_fq2_2599, 252), sector), size_group) + +group_neutralize(group_neutralize(rank(ts_mean(divide(depreciation_and_amortization_expense, anl82_preq_profitability_profitability11), 756)) * sign(ts_delta(anl44_operatingprofit_value, 252)), industry), size_group) \ No newline at end of file diff --git a/generated_alpha/2026/01/22/Qwen_Qwen3-VL-235B-A22B-Instruct_174833.txt b/generated_alpha/2026/01/22/Qwen_Qwen3-VL-235B-A22B-Instruct_174833.txt new file mode 100644 index 0000000..65d8aed --- /dev/null +++ b/generated_alpha/2026/01/22/Qwen_Qwen3-VL-235B-A22B-Instruct_174833.txt @@ -0,0 +1,44 @@ +divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)) +group_neutralize(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), sector) +ts_mean(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 750) +rank(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))) +zscore(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))) +group_zscore(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), industry) +ts_delta(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_rank(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 500) +normalize(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), useStd=true) +winsorize(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), std=3) +ts_std_dev(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 500) +group_scale(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), sector) +ts_zscore(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +quantile(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), driver="gaussian") +ts_av_diff(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +group_mean(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), market_cap, industry) +ts_corr(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), anl49_netprofit, 252) +ts_decay_linear(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_product(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_quantile(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_regression(anl49_netprofit, divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_backfill(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_count_nans(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_covariance(anl49_netprofit, divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_arg_max(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_arg_min(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_scale(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_sum(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 252) +ts_target_tvr_decay(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), 0.1, 0.9, 0.1) +ts_target_tvr_delta_limit(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), anl49_netprofit, 0.1, 0.9, 0.1) +group_backfill(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), industry, 252) +group_rank(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), sector) +group_max(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), industry) +group_min(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), sector) +vec_avg(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))) +vec_sum(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))) +vec_max(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))) +vec_min(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))) +bucket(rank(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))), range="0,1,0.1") +trade_when(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense)), anl49_netprofit > 0, 0) +reduce_avg(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))) +reduce_max(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))) +reduce_min(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))) +reduce_stddev(divide(r_and_d_expense_balance, add(r_and_d_expense_balance, selling_general_admin_expense))) \ No newline at end of file diff --git a/generated_alpha/2026/01/23/template_output.txt b/generated_alpha/2026/01/23/template_output.txt new file mode 100644 index 0000000..b3efa96 --- /dev/null +++ b/generated_alpha/2026/01/23/template_output.txt @@ -0,0 +1,500 @@ +ts_covariance(anl10_nersmun_2yf_2416, pv87_interval_bidsize_skewness, 60) +ts_covariance(fnd65_us5000_cusip_ebitdap, oth137_avg_txn_val, 60) +ts_covariance(anl15_ebtgics_s_cal_fy3_pe, pv104_insm_mean, 20) +ts_covariance(anl10_entfy1_pred_surps_v1_2442, pv87_interval_bidsize_median, 20) +ts_covariance(fnd72_pit_or_is_q_is_tot_cash_com_dvd, pv87_interval_bidsize_median, 60) +ts_covariance(anl15_cpsgics_gr_cal_fy3_pe, pv81_msni, 20) +ts_covariance(mdl211_ebtq_profitability_profitability5, pv103_mbds_topofbook_mbds_mean, 20) +ts_covariance(anl82_preq_profitability_profitability12, pv103_tbsz_mean, 250) +ts_covariance(anl14_mean_eps_fp5, pv64_trr_cur_mkt_cap, 20) +ts_covariance(anl14_high_eps_fy2, pv87_interval_bidsize_skewness, 250) +ts_covariance(anl14_high_ntprep_fy5, fnd65_totalcap_cusip_ohlsonscore, 5) +ts_covariance(anl82_delta_preq_q4_predict, pv81_zsbt, 250) +ts_covariance(mdl138_qpdi3_net_margin, mdl248_avg_txn_val, 5) +ts_covariance(anl15_ebt_gr_cal_fy3_gro, pv103_masz_mean, 5) +ts_covariance(mdl230_us5000_cusip_y5speq4rqsr, pv104_lbsz_mean, 20) +ts_covariance(pv20_ebt_indicator_4_feature7, pv52_asdaq_order_size_code, 250) +ts_covariance(mdl264_1l_qaeclg, oth567score_company_size_358, 250) +ts_covariance(pv20_ebt_indicator_4_feature7, fnd72_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(oth432_acae_q_profitability_profitability9, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(pv87_epsyld_ltm_d_mean, pv103_htsz_mean, 60) +ts_covariance(anl44_orig_en_pretaxprofit_rep_prevalue, pv81_zsbt, 250) +ts_covariance(anl82_ebty_deltaprofitability_profitability11, fnd72_pit_or_cr_q_debt_to_mkt_cap, 20) +ts_covariance(mdl77_2spe1yfvc_cf, pv87_interval_bidsizeinterval_slippage_correlation, 250) +ts_covariance(fnd13_cinx, fund_total_size, 20) +ts_covariance(anl15_ebt_gr_18_m_cos_dn, pv104_hbsz_mean, 60) +ts_covariance(pv20_gps_indicator_9_feature8, oth551_beta_size, 60) +ts_covariance(anl49_valugaugeestimatingdifficultyrank, pv87_interval_asksize_std, 60) +ts_covariance(pv20_opr_indicator_o_feature11, pv87_interval_asksize_std, 60) +ts_covariance(mdl77_2valuemomemtummodel_reportedearningsmomentummodule, company_size_sentiment_score, 250) +ts_covariance(mdl230_allcap_sedol_yoychgroa, pv103_masz_mean, 60) +ts_covariance(fnd72_s_pit_or_bs_q_2_bs_other_cur_asset_less_prepay, oth567score_company_size, 60) +ts_covariance(mdl264_einn_l1, pv87_interval_asksize_std, 60) +ts_covariance(fnd31_devnorthamericaadditionalfactor4_divgp, pv81_zsbt, 250) +ts_covariance(fnd28_dvfq1_value_18264q, fnd65_allcap_sedol_ohlsonscore, 250) +ts_covariance(anl15_ebtgics_ind_12_m_1m_chg, pv81_trlm, 20) +ts_covariance(mdl177_liquidityriskfactor_mad3yttmni_alt, company_offer_total_size, 60) +ts_covariance(mdl77_ooearningsmomemtummodel_fc_y2repsg, pv87_interval_asksizeinterval_slippage_correlation, 60) +ts_covariance(oth432_deltapredictebt_a_predict, oth551_r2_size, 20) +ts_covariance(pv87_daily_ann_matrix_r1_net_income_normalized_consensus_mean_numup, pv52_yse_arca_order_size_code, 5) +ts_covariance(anl69_rec_expected_report_time, mdl230_allcap_sedol_ohlsonscore, 5) +ts_covariance(fnd23_icsm_mvb_fbbs, pv103_sasz_mean, 5) +ts_covariance(pe_ratio_relative_component_rank_v2, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(pv20_eps_indicator_4_feature2, pv104_hasz_mean, 20) +ts_covariance(mdl230_us5000_cusip_pspeghc, pv52_yse_arca_order_size_code, 60) +ts_covariance(fnd3_A_nic, pv87_interval_asksize_numintervalsincehigh, 60) +ts_covariance(anl14_median_ntp_fy5, pv81_zsah, 250) +ts_covariance(mdl211_oprq_deltaprofitability_profitability5, pv87_interval_bidsize_numintervalsincelow, 5) +ts_covariance(anl82_delta_preq_q2_predict, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 20) +ts_covariance(fnd28_wcishta_value_18189a, pv103_taks_mean, 20) +ts_covariance(mdl354_sector_pt2net_margin, pv87_interval_asksize_median, 60) +ts_covariance(anl14_median_ntp_fy5, nws31_d1_bodysize, 5) +ts_covariance(fnd65_us5000_cusip_chgroepct, oth137_avg_txn_val, 250) +ts_covariance(est_q_gps_mean_3mth_ago, nws31_bodysize, 60) +ts_covariance(pv87_2_operatingprofit_qf_matrix_all_chngratio_mean, pv81_zsbm, 250) +ts_covariance(anl49_1stfiscalquarterearningspershare, pv87_interval_bidsize_mean, 250) +ts_covariance(fnd6_cibegni, pv52_yse_national_order_size_code, 250) +ts_covariance(pv87_2_eps_af_matrix_p1_chngratio_high, rsk70_mfm2_usfast_size, 20) +ts_covariance(mdl211_preq_deltaprofitability_profitability1, pv87_interval_asksize_kurtosis, 250) +ts_covariance(mdl26_v14_srprs_pct_lst_y_rnngs, pv87_interval_asksizeinterval_slippage_correlation, 250) +ts_covariance(est_q_pre_std_4wks_ago, pv52_yse_american_order_size_code, 60) +ts_covariance(fnd31_qsg5additionalfactor3_backfilled_rev6fy2, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(mdl230_totalcap_cusip_pfgmtt, pv103_htsz_mean, 20) +ts_covariance(pv20_pre_indicator_8_feature11, pv103_tbsz_mean, 250) +ts_covariance(mdl211_saly_profitability_profitability5, mdl177_liquidityriskfactor_ohlsonscore_alt, 60) +ts_covariance(mdl26_stm_f12m_rnngs, pv103_1m_mbds_mean, 5) +ts_covariance(oth460_3l_ifpv, oth551_beta_size, 60) +ts_covariance(mdl262_oibdpq_profitability_profitability8, pv103_tbds_mean, 250) +ts_covariance(fnd72_s_pit_or_is_q_is_pension_expense_income, pv87_interval_asksizeinterval_volume_correlation, 5) +ts_covariance(fnd3_a__earbeforetaxes, pv52_yse_order_size_code, 250) +ts_covariance(oth432_che_profitability_profitability2, pv103_sbps_mean, 20) +ts_covariance(pv87_2_pretaxprofit_qf_matrix_all_chngratio_high, pv104_tbsz_mean, 250) +ts_covariance(pv20_gps_indicator_9_feature11, pv104_lsbs_mean, 20) +ts_covariance(mdl26_mstchg_pct_f12m_rnngs_14, pv52_asdaq_order_size_code, 5) +ts_covariance(fnd28_wsbshtq_value_01551q, pv64_trr_stal_cur_mkt_cap, 20) +ts_covariance(mdl264_viat_class, pv81_zsbh, 60) +ts_covariance(mdl262_cheq_profitability_profitability3, pv103_lbsz_mean, 5) +ts_covariance(oth460_uniamiq_l3, company_offer_total_size, 60) +ts_covariance(act_q_gps_surprisestd, fund_total_size, 5) +ts_covariance(anl14_low_ntprep_fy2, pv87_interval_asksizeinterval_bidsize_correlation, 250) +ts_covariance(mdl262_deltapredictni_a_mae, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(mdl77_2deepvaluefactor_vesspem21f, pv103_sasz_mean, 5) +ts_covariance(oth432_rasv2splitprofitabilityfcf_ttm_profitability3, mdl77_liquidityriskfactor_ohlsonscore, 60) +ts_covariance(anl69_roa_expected_report_time, pv64_dif_stal_fund_creation_unit_size, 5) +ts_covariance(fnd14_hiwater_incmst_net_income_fy, pv104_lsts_mean, 5) +ts_covariance(anl10_gpspast_det_analyst_1321, pv81_zsbl, 5) +ts_covariance(fnd17_ttmnichg, pv103_saps_mean, 5) +ts_covariance(mdl230_totalcap_cusip_spe2yfvc_cf, fnd31_ohlsonscore, 20) +ts_covariance(fnd3_Q_interestincome, pv103_sbsz_mean, 5) +ts_covariance(anl49_backfill_typeofearningspershare, pv104_tbsz_mean, 20) +ts_covariance(pv20_eps_indicator_1_feature7, fund_total_size, 250) +ts_covariance(count_negative_profitability_question, pv104_masz_mean, 60) +ts_covariance(pv87_daily_qtr_matrix_net_income_gaap_consensus_mean_numdown, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(anl15_ebtgics_ind_cal_fy3_3m_chg, pv103_1m_mlrt_mean, 20) +ts_covariance(mdl77_earningmomentumfactor_stdevfy1epsp, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(mdl77_historicalgrowthfactor_pspeghc, oth567_deltascore_company_size_432, 20) +ts_covariance(fnd65_allcap_sedol_fqsurstd60dlag, pv98_daily_mean_taks_taks_mean, 5) +ts_covariance(mdl138_in_3idp, pv52_yse_chicago_order_size_code, 20) +ts_covariance(mdl77_fa_pge_cf, pv52_yse_order_size_code, 250) +ts_covariance(fnd28_wcfsq1nbf_value_01401q, mdl248_avg_txn_val, 20) +ts_covariance(oth460_unopincq_l3, fund_total_size, 250) +ts_covariance(mdl177_2_globaldevnorthamerica_v502_fc_epsrm, pv52_asdaq_order_size_code, 250) +ts_covariance(fnd28_statisticsa_value_05290a, pv103_masz_mean, 60) +ts_covariance(investment_income_nonoperating, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(fnd65_us5000_cusip_fqsurstd60dlag, pv81_sasl, 250) +ts_covariance(fnd7_ointfund_qipon, pv103_lbsz_mean, 5) +ts_covariance(pv87_webv2_expavg20_group_css_earnings, mdl177_2_liquidityriskfactor_ohlsonscore, 60) +ts_covariance(fnd28_pftlta_value_08365a, pv103_1m_maks_mean, 250) +ts_covariance(mdl264_3l_21fspe, pv103_tbsz_mean, 250) +ts_covariance(fnd72_s_pit_or_cr_q_trail_12m_eps, pv52_asdaq_order_size_code, 5) +ts_covariance(pv20_gps_indicator_q_feature8, oth551_beta_size, 5) +ts_covariance(mdl77_earningsmomemtummodel_fc_y2repsg, pv64_dif_stal_fund_creation_unit_size, 250) +ts_covariance(est_12m_opr_std, pv87_interval_asksizeinterval_slippage_rankcorrel, 20) +ts_covariance(pv87_2_operatingprofit_qf_matrix_p1_dts, pv81_zsbm, 5) +ts_covariance(anl49_netprofit, pv81_trlm, 20) +ts_covariance(mdl77_2min2ygrossmargin, oth137_avg_txn_val, 20) +ts_covariance(oth432_ebit_compustatdeltapredict_annual_funda_predict, pv103_mbsz_mean, 5) +ts_covariance(anl14_high_ebit_fp4, pv87_interval_bidsizeinterval_slippage_rankcorrel, 20) +ts_covariance(pv20_eps_indicator_8_feature10, pv81_trlt, 250) +ts_covariance(anl82_opry_profitability_profitability12, pv87_interval_bidsizeinterval_slippage_rankcorrel, 250) +ts_covariance(fnd65_allcap_sedol_lagegp, pv104_lasz_mean, 20) +ts_covariance(anl15_ebt_gr_18_m_mean, oth567score_company_size, 250) +ts_covariance(mdl26_trailing_4_quarter_pe, pv103_mbsz_mean, 20) +ts_covariance(pv87_2_operatingprofit_qf_matrix_p1_median, pv52_asdaq_bx_order_size_code, 5) +ts_covariance(mdl77_historicalgrowthfactor_chg3yepsast, pv103_1m_mlrt_mean, 250) +ts_covariance(pv20_gps_indicator_n_feature5, mdl77_liquidityriskfactor_ohlsonscore, 60) +ts_covariance(pv20_net_indicator_n_feature3, pv64_dif_fund_creation_unit_size, 250) +ts_covariance(mdl77_omomemtumanalystmodel_qma_repearnmom, pv87_interval_asksizeinterval_slippage_correlation, 20) +ts_covariance(anl14_low_ntprep_fy2, pv103_laks_mean, 60) +ts_covariance(oth460_2l_eiuv, pv103_maus_mean, 5) +ts_covariance(oth432_oibdpq_profitability_profitability4, pv103_tbds_mean, 250) +ts_covariance(anl69_roe_expected_report_time, pv103_tbds_mean, 5) +ts_covariance(fnd65_allcap_sedol_pspeghc, pv87_interval_asksize_mean, 20) +ts_covariance(anl10_ebtfq1_smart_ests_v1_936, pv87_interval_bidsize_std, 60) +ts_covariance(pv87_2_eps_qf_matrix_all_high, pv87_interval_asksizeinterval_bidsize_rankcorrel, 60) +ts_covariance(mdl26_rm02fy_prsprs_fy2_rnngs, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(fnd72_pit_or_cr_a_prof_margin, pv81_trlt, 20) +ts_covariance(pv20_gps_indicator_1_feature8, pv103_tbsz_mean, 250) +ts_covariance(anl4_qfv4_eps_number, pv81_stlh, 5) +ts_covariance(eps_fiscal_quarter, nws31_d1_bodysize, 60) +ts_covariance(pv87_simpleavg20_group_css_earnings, pv87_interval_asksize_std, 60) +ts_covariance(pv87_2_pretaxprofit_qf_matrix_all_chngratio_median, pv87_interval_bidsizeinterval_slippage_rankcorrel, 60) +ts_covariance(mdl177_valanalystmodel_qva_earnquality, pv52_asdaq_psx_order_size_code, 60) +ts_covariance(mdl77_oearningmomentumfactor_rev6, pv103_tasz_mean, 250) +ts_covariance(oth553_ptg_wordcnt, pv52_yse_arca_order_size_code, 250) +ts_covariance(anl14_mean_ntprep_fp5, pv52_yse_national_order_size_code, 250) +ts_covariance(mdl264_sani_l3, pv87_interval_bidsize_kurtosis, 60) +ts_covariance(oth432_accruals_oeps12_predict, pv52_yse_american_order_size_code, 60) +ts_covariance(anl82_nety_profitability_profitability10, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(anl15_ebtgics_s_fy3_cos_dn, pv87_interval_asksizeinterval_volume_correlation, 60) +ts_covariance(pv87_2_pretaxprofit_rep_af_matrix_all_chngratio_high, pv81_zsbh, 250) +ts_covariance(fnd3_aacctadj__earbeforetaxes, pv103_tasz_mean, 250) +ts_covariance(anl10_ebiinnovation_score_fy2_2589, fnd72_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(pv87_2_epsr_qf_matrix_all_high, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(anl49_earningspershare, pv103_mbus_mean, 250) +ts_covariance(fnd72_pit_or_cr_a_net_inc_growth, pv52_yse_national_order_size_code, 20) +ts_covariance(mdl262_niq_compustatdeltapredict_funda_mada, pv87_interval_asksizeinterval_slippage_correlation, 5) +ts_covariance(fnd28_wcfsa1_value_01266a, pv103_tbds_mean, 5) +ts_covariance(fnd65_totalcap_cusip_fc_numrevq1, rsk70_mfm2_usfast_size, 5) +ts_covariance(mdl230_us5000_cusip_ebitdadebtchg, fnd31_ohlsonscore, 20) +ts_covariance(pv87_2_epsr_af_matrix_p1_dts, pv103_tasz_mean, 5) +ts_covariance(anl10_nerpast_det_indicator_913, pv64_dif_fund_creation_unit_size, 5) +ts_covariance(anl44_second_en_netprofit_rep_coveredby, pv103_lasz_mean, 250) +ts_covariance(fnd7_ointfund_rq21hsc, company_offer_total_size, 5) +ts_covariance(pv20_ebt_indicator_2_feature9, pv104_tasz_mean, 60) +ts_covariance(gross_profit_total, pv103_tasz_mean, 250) +ts_covariance(mdl26_v14_nnlyst_rvsng_dwn_fq1_rnngs_7, pv64_trr_stal_cur_mkt_cap, 5) +ts_covariance(oth460_usa_compustat_q1_dl8_ibadjq_l2, pv87_interval_asksizeinterval_bidsize_correlation, 250) +ts_covariance(anl4_epsr_value, pv103_mbus_mean, 20) +ts_covariance(oth460_ibadjq_l3, pv81_stsl, 20) +ts_covariance(pv20_net_indicator_n_feature6, pv52_yse_american_order_size_code, 20) +ts_covariance(anl10_ebspast_det_excflag, pv104_masz_mean, 5) +ts_covariance(fnd89_jones_accrual_major_11, pv87_interval_asksize_mean, 60) +ts_covariance(fnd28_annualgrowth_value_08601a, pv81_zsbl, 5) +ts_covariance(anl14_numofests_ebitda_fp4, pv104_masz_mean, 5) +ts_covariance(mdl177_valueanalystmodel_qva_earnval_alt, oth137_avg_txn_val, 250) +ts_covariance(mdl26_mn_f_rvsnclstr_nlysts_fy2_rnngs, oth567_deltascore_company_size_432, 20) +ts_covariance(pv87_2_netprofit_rep_qf_matrix_p1_median, fnd31_ohlsonscore, 5) +ts_covariance(fnd72_q1_geo_grow_ebitda_cap_exp_to_int, pv81_trlm, 250) +ts_covariance(mdl230_us5000_cusip_ebitdadebt, pv64_dif_stal_fund_creation_unit_size, 60) +ts_covariance(oth460_net_margin_l2, mdl177_2_liquidityriskfactor_ohlsonscore, 250) +ts_covariance(mdl77_valuemomemtummodel_earningsqualitymodule, pv52_yse_arca_order_size_code, 5) +ts_covariance(pv87_epsyld_gro_mean, pv103_1m_mbds_mean, 20) +ts_covariance(mdl262_compustatpredictivetxtq_prediction, pv104_tbsz_mean, 250) +ts_covariance(mdl262_txtq_compustatdeltapredict_funda_predict, pv98_tbds_mean, 5) +ts_covariance(mdl230_allcap_sedol_saleeps, fund_total_size, 20) +ts_covariance(mdl262_rasv2splitprofitabilityebitd_ttm_profitability9, oth567score_company_size_358, 250) +ts_covariance(anl10_ebiinnovation_score_fy2_2589, fnd65_allcap_sedol_ohlsonscore, 20) +ts_covariance(ern6_actual_period, pv103_hasz_mean, 20) +ts_covariance(mdl262_rasv2splitprofitabilityebitd_q_profitability9, pv87_interval_asksize_median, 60) +ts_covariance(mdl262_sbda_a_profitability_profitability4, pv87_interval_asksize_numintervalsincehigh, 5) +ts_covariance(anl69_eps_best_eps, fnd72_pit_or_cr_a_debt_to_mkt_cap, 60) +ts_covariance(fnd28_wcfsq1nbf_value_01706q, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(fnd72_pit_or_cr_a_trail_12m_oper_inc, pv87_interval_asksizeinterval_bidsize_correlation, 5) +ts_covariance(oth460_ttax_l3, pv87_interval_bidsizeinterval_volume_correlation, 60) +ts_covariance(oth432_txtq_mae, oth551_resret_size, 60) +ts_covariance(anl82_preq_deltaprofitability_profitability11, company_offer_total_size, 20) +ts_covariance(fnd6_newa1v1300_ibadj, oth567score_company_size_358, 20) +ts_covariance(star_eq_ope_rank, pv98_daily_mean_taks_taks_mean, 5) +ts_covariance(anl15_dps_gr_cal_fy1_pe, oth551_r2_size, 5) +ts_covariance(mdl26_dsnc_prd_srprs_flg_chg_fq4_rnngs, pv104_insm_mean, 60) +ts_covariance(anl49_backfill_estdcurrentperatio, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(mdl77_2mqf_yoychggpm, fnd65_totalcap_cusip_ohlsonscore, 60) +ts_covariance(pv20_pre_indicator_3_feature0, pv87_interval_bidsize_median, 250) +ts_covariance(anl14_numofests_opp_fp1, fnd14_zs_lf_nlf_drp_ncr, 5) +ts_covariance(anl14_mean_ntp_fy1, mdl177_2_liquidityriskfactor_ohlsonscore, 250) +ts_covariance(mdl211_preq_profitability_profitability7, company_size_sentiment_score, 5) +ts_covariance(fnd65_us5000_cusip_pfcmtt, pv103_masz_mean, 5) +ts_covariance(mdl177_historicalgrowthfactor_chgeps, pv103_sbsz_mean, 20) +ts_covariance(mdl109_b_mtl_dlyspe, pv103_1m_mlrt_mean, 60) +ts_covariance(oth432_compustatpredictiveniq_prediction, pv103_tasz_mean, 5) +ts_covariance(mdl211_nety_y1_mada, mdl177_2_liquidityriskfactor_ohlsonscore, 20) +ts_covariance(pv87_2_operatingprofit_qf_matrix_all_low, mdl230_totalcap_cusip_ohlsonscore, 250) +ts_covariance(pv20_ebt_indicator_7_feature6, pv87_interval_asksize_skewness, 60) +ts_covariance(anl82_preq_q4_madp, pv103_lasz_mean, 250) +ts_covariance(anl82_delta_netq_q1_predict, pv81_lasz, 250) +ts_covariance(mdl230_totalcap_cusip_epschgetr, oth551_resret_size, 20) +ts_covariance(mdl26_7dy_bld_stmt_flg_fq4_rnngs, pv104_lsbs_mean, 250) +ts_covariance(fnd89_jones_accrual_pct_major_13, oth567score_company_size, 20) +ts_covariance(anl4_netprofit_mean, pv103_maks_topofbook_maks_mean, 250) +ts_covariance(act_12m_prr_value, pv87_interval_bidsize_mean, 60) +ts_covariance(fnd72_s_pit_or_cr_q_ev_to_t12m_ebit, pv104_tlrt_mean, 20) +ts_covariance(mdl211_ebtq_deltaprofitability_profitability11, pv103_sbps_mean, 250) +ts_covariance(pv87_2_pretaxprofit_rep_af_matrix_p1_chngratio_number, pv87_interval_bidsize_skewness, 250) +ts_covariance(anl82_oprq_q4_madp, fnd31_ohlsonscore, 20) +ts_covariance(pv87_2_netprofit_rep_af_matrix_all_low, pv103_mbsz_mean, 60) +ts_covariance(anl15_ebt_gr_cal_fy3_cos, im_shares_transacted, 60) +ts_covariance(pv20_indicator_4_feature8, mdl77_liquidityriskfactor_ohlsonscore, 20) +ts_covariance(max_ebit_guidance, mdl230_allcap_sedol_ohlsonscore, 20) +ts_covariance(mdl26_rm02fy_prsprs_fy2_rnngs, pv52_asdaq_order_size_code, 250) +ts_covariance(fnd90_us_qes_gamef_grossprofit_asset, pv103_tbsz_mean, 60) +ts_covariance(anl15_ebt_gr_18_m_6m_chg, rsk70_mfm2_usfast_size, 60) +ts_covariance(gross_profit_to_assets_ratio, pv98_tbds_mean, 250) +ts_covariance(fnd17_margin5yr, rsk70_mfm2_usfast_size, 20) +ts_covariance(fnd23_annfv1a_nimv, pv103_lasz_mean, 5) +ts_covariance(oth395_major_12_13, nws31_bodysize, 60) +ts_covariance(mdl264_2l_qic, pv104_tasz_mean, 5) +ts_covariance(mdl230_us5000_cusip_spe2yfvc_cf, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(anl14_numofests_ntprep_fp1, pv87_interval_asksize_mean, 250) +ts_covariance(mdl262_rasv2splitprofitabilityni_q_profitability3, pv64_trr_cur_mkt_cap, 250) +ts_covariance(pv20_pre_indicator_6_feature10, fund_total_size, 20) +ts_covariance(mdl26_mstchg_pct_fq2_rnngs_60, pv52_yse_order_size_code, 20) +ts_covariance(mdl264_1l_declg, fund_total_size, 5) +ts_covariance(anl14_high_ntprep_fy3, mdl230_us5000_cusip_ohlsonscore, 5) +ts_covariance(pv87_ann_matrix_net_income_gaap_estimate_high, pv52_yse_national_order_size_code, 250) +ts_covariance(pv87_daily_qtr_matrix_net_income_gaap_consensus_mean_numup, pv87_interval_bidsize_std, 20) +ts_covariance(mdl26_nnlyst_rvsng_p_fy1_rnngs_7, mdl248_avg_txn_val, 60) +ts_covariance(mdl26_v14_prsprise_pct_fq2_earnings, rsk70_mfm2_usfast_size, 250) +ts_covariance(pv87_2_operatingprofit_af_matrix_p1_chngratio_mean, pv103_sbps_mean, 5) +ts_covariance(anl14_median_ebit_fy4, pv87_interval_asksize_numintervalsincehigh, 250) +ts_covariance(anl15_dps_gr_12_m_pe, nws31_d1_bodysize, 60) +ts_covariance(mdl77_liquidityriskfactor_impduration, pv52_asdaq_psx_order_size_code, 60) +ts_covariance(pv87_2_netprofit_af_matrix_all_dts, pv103_1m_tlrt_mean, 250) +ts_covariance(oth432_oiadpq_profitability_profitability1, pv87_interval_asksizeinterval_bidsize_rankcorrel, 250) +ts_covariance(fnd72_q1_inc_tax_exp_to_net_sales, pv103_lbsz_mean, 60) +ts_covariance(pv20_ebt_indicator_7_feature2, pv87_interval_bidsize_kurtosis, 5) +ts_covariance(mdl177_2_earningsqualityfactor_saleeps, nws31_d1_bodysize, 20) +ts_covariance(mdl262_txtq_compustatdeltapredict_funda_mada, im_shares_transacted, 5) +ts_covariance(anl10_epsinnovation_score_fy1, pv103_tbsz_mean, 5) +ts_covariance(anl14_high_eps_fy4, company_size_sentiment_score, 20) +ts_covariance(mdl77_ohistoricalgrowthfactor_speghc, pv87_interval_asksizeinterval_slippage_correlation, 20) +ts_covariance(earnings_news_mention_count, pv104_lsbs_mean, 250) +ts_covariance(est_q_opr_num_28d, fund_total_size, 250) +ts_covariance(fnd72_s_pit_or_cr_q_trail_12m_inc_bef_xo_item, pv103_tbds_mean, 20) +ts_covariance(fnd72_a2_retention_ratio, fund_total_size, 250) +ts_covariance(mdl77_oindustryrrelativevaluefactor_curindcoreepsp_, mdl77_2liquidityriskfactor_ohlsonscore, 5) +ts_covariance(mdl262_deltapredictebt_q_predict, pv104_hasz_mean, 5) +ts_covariance(oth432_ninc_trkdpitdeltapredict_funda_mae, pv81_zsbm, 60) +ts_covariance(est_q_opr_mean_28d, pv103_maks_topofbook_maks_mean, 20) +ts_covariance(fnd6_newa2v1300_ni, pv104_mlrt_mean, 60) +ts_covariance(ebit_reported_value, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(pv20_ebt_indicator_n_feature4, pv87_interval_bidsize_std, 5) +ts_covariance(mdl177_v1_400_sue, pv64_dif_stal_fund_creation_unit_size, 5) +ts_covariance(anl49_backfill_earningspershareindicator, pv81_zsbl, 250) +ts_covariance(anl15_ebtgics_gr_cal_fy2_gro, oth551_r2_size, 60) +ts_covariance(anl10_ebsfq1_consensus, oth551_r2_size, 250) +ts_covariance(mdl262_che_profitability_profitability9, pv104_mlrt_mean, 5) +ts_covariance(est_12m_ner_std_28d, pv81_lasz, 250) +ts_covariance(mdl262_sbda_a_profitability_profitability2, pv103_laks_mean, 20) +ts_covariance(rsk62_id_spe, pv104_tasz_mean, 250) +ts_covariance(fnd72_pit_or_cr_a_ev_to_t12m_ebitda, pv103_laks_mean, 250) +ts_covariance(oth432_rasv2splitprofitabilityebt_ttm_profitability4, pv87_interval_bidsize_numintervalsincelow, 20) +ts_covariance(pv87_2_netprofit_af_matrix_p1_chngratio_std, pv104_hbsz_mean, 60) +ts_covariance(anl10_ebismun_2qf_2231, pv52_yse_national_order_size_code, 250) +ts_covariance(pv87_neg_earnings_matrix_css_sum, pv103_1m_maks_mean, 60) +ts_covariance(mdl262_rasv2splitprofitabilityebitd_q_profitability10, pv103_1m_maks_mean, 250) +ts_covariance(mdl264_usa_compustat_q1_dl8_ibadjq_l3, pv64_dif_fund_creation_unit_size, 250) +ts_covariance(oth460_usa_compustat_q1_dl8_epsfiq_l5, mdl177_2_liquidityriskfactor_ohlsonscore, 5) +ts_covariance(mdl77_2ccacw, pv98_quote_size_mean, 5) +ts_covariance(mdl177_2_liquidityriskfactor_oplev, pv87_interval_asksize_kurtosis, 250) +ts_covariance(pv20_net_indicator_q_feature7, pv103_laks_mean, 250) +ts_covariance(pv87_prv2_expavg60_group_event_sentiment_score_earnings, pv103_hasz_mean, 250) +ts_covariance(fnd28_newa1_value_08385a, pv103_1m_mbds_mean, 250) +ts_covariance(mdl177_2_globaldevnorthamerica_v502_wcacc, pv87_interval_asksize_mean, 5) +ts_covariance(fnd6_txs, pv52_yse_arca_order_size_code, 250) +ts_covariance(mdl26_nm_stm_nlysts_fy2_rnngs, mdl230_allcap_sedol_ohlsonscore, 250) +ts_covariance(mdl262_che_profitability_profitability5, pv98_quote_size_mean, 5) +ts_covariance(mdl77_ooearningsmomemtummodel_fc_numrevy1, pv81_stlh, 250) +ts_covariance(fnd65_totalcap_cusip_pe_wt, pv87_interval_bidsize_kurtosis, 250) +ts_covariance(pv20_gps_indicator_6_feature10, pv103_maus_mean, 60) +ts_covariance(fnd28_wcfsa1_value_01503a, mdl230_allcap_sedol_ohlsonscore, 250) +ts_covariance(mdl230_allcap_sedol_pedwf_cf, pv87_interval_asksizeinterval_slippage_rankcorrel, 20) +ts_covariance(mdl262_rasv2splitprofitabilityfcf_q_profitability9, nws31_d1_bodysize, 60) +ts_covariance(mdl77_momemtumanalystmodel_qma_composite, fnd65_allcap_sedol_ohlsonscore, 20) +ts_covariance(anl10_ebsfy2_smart_ests_v1, pv87_interval_bidsizeinterval_slippage_correlation, 60) +ts_covariance(oth432_compustatpredictiveepsfiq_mad_pred, pv87_interval_asksize_mean, 5) +ts_covariance(anl15_ebt_ind_cal_fy1_1m_chg, rsk70_mfm2_usfast_size, 5) +ts_covariance(pv20_net_indicator_8_feature12, pv104_lbsz_mean, 20) +ts_covariance(fnd65_allcap_sedol_bmpo, pv103_masz_mean, 250) +ts_covariance(pv20_eps_indicator_1_feature2, pv87_interval_asksize_median, 5) +ts_covariance(anl14_stddev_opp_fy1, oth551_resret_size, 250) +ts_covariance(anl69_eps_best_eps_lo, pv103_1m_mlrt_mean, 5) +ts_covariance(anl82_netq_deltaprofitability_profitability2, mdl230_totalcap_cusip_ohlsonscore, 20) +ts_covariance(mdl264_net_margin_l2, pv52_yse_arca_order_size_code, 60) +ts_covariance(fnd72_s_pit_or_is_a_is_rd_expend, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(est_12m_opr_mean_3mth_ago, pv81_zsbm, 60) +ts_covariance(mdl177_2_earningsqualityfactor_salegpm, pv104_lsbs_mean, 5) +ts_covariance(anl82_saly_deltaprofitability_profitability8, fnd72_pit_or_cr_a_debt_to_mkt_cap, 60) +ts_covariance(mdl262_compustatpredictiveoiadpq_mad_pred, pv104_tbsz_mean, 60) +ts_covariance(rsk62_beta_5_100_spe, pv87_interval_bidsize_median, 5) +ts_covariance(long_term_dividend_payout_ratio, company_offer_total_size, 60) +ts_covariance(fnd3_aacctadj_ebit, pv52_yse_national_order_size_code, 20) +ts_covariance(pv87_net_income_normalized_actual, pv103_tlrt_topofbook_tlrt_mean, 20) +ts_covariance(anl14_stddev_ebit_fp1, pv81_sasl, 60) +ts_covariance(mdl77_2mqf_niper, pv64_dif_fund_creation_unit_size, 20) +ts_covariance(est_ptpr, pv52_yse_chicago_order_size_code, 60) +ts_covariance(mdl26_v14_mstchg_pct_fy1_rnngs_14, pv98_tbds_mean, 20) +ts_covariance(gross_profit_current, pv81_stsl, 20) +ts_covariance(mdl264_usa_compustat_q1_dl8_miiq_l2, pv103_maus_mean, 250) +ts_covariance(fnd23_annfvmfm_rltr, pv103_lask_topofbook_lask_mean, 250) +ts_covariance(anl49_vector_depreciationdepletionamortization, pv103_tbsz_mean, 250) +ts_covariance(fnd31_qsg5additionalfactor3_backfilled_apg, pv103_sbps_mean, 250) +ts_covariance(est_12m_ner_median, pv103_1m_tlrt_mean, 5) +ts_covariance(pv87_ann_matrix_net_income_normalized_estimate_median, pv81_lasz, 5) +ts_covariance(anl14_high_epsrep_fy3, pv103_mbus_mean, 60) +ts_covariance(est_q_ner_median_3mth_ago, pv103_masz_mean, 250) +ts_covariance(pv87_web_weightedavg60_group_v2_0_1_css_earnings, mdl230_totalcap_cusip_ohlsonscore, 20) +ts_covariance(fnd65_us5000_cusip_min1yopmargin, pv81_zsbl, 60) +ts_covariance(anl15_ebt_ind_cal_fy3_6m_chg, fnd65_us5000_cusip_ohlsonscore, 250) +ts_covariance(mdl262_rasv2splitprofitabilityebit_ttm_profitability12, pv52_yse_arca_order_size_code, 250) +ts_covariance(anl10_gpssmun_1qf_2624, pv103_mbsz_mean, 5) +ts_covariance(mdl262_compustatpredictiveepspiq_prediction, pv103_tbds_mean, 20) +ts_covariance(pv87_2_epsr_af_matrix_all_chngratio_low, pv81_zsbl, 5) +ts_covariance(anl10_nerinnovate_increase_fy1_1995, mdl230_us5000_cusip_ohlsonscore, 5) +ts_covariance(fnd3_q_ebitda, pv87_interval_bidsizeinterval_volume_correlation, 250) +ts_covariance(oth460_berry_l2, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(fnd65_us5000_cusip_aoer, pv103_mlrt_topofbook_mlrt_mean, 250) +ts_covariance(fnd72_s_pit_or_cr_q_com_eqy_to_tot_asset, pv103_tlrt_topofbook_tlrt_mean, 250) +ts_covariance(anl10_ebiinnovate_decrease_fq2_2606, pv81_zsah, 250) +ts_covariance(oth432_deltapredictebitd_a_mae, pv103_lasz_mean, 5) +ts_covariance(mdl264_epsfx_class, pv104_hlts_mean, 60) +ts_covariance(research_development_expense_reported_value, pv103_laks_mean, 250) +ts_covariance(mdl230_allcap_sedol_perg, fnd14_zs_lf_nlf_drp_ncr, 250) +ts_covariance(fnd65_totalcap_cusip_mpgghcy3_, pv81_zsbt, 5) +ts_covariance(mdl77_put_put_indepsp, pv104_tasz_mean, 5) +ts_covariance(mdl264_opepsq_l2, pv104_tasz_mean, 250) +ts_covariance(mdl77_2gdna_yoychgaa, mdl177_2_liquidityriskfactor_ohlsonscore, 250) +ts_covariance(mdl262_cheq_profitability_profitability2, pv52_yse_national_order_size_code, 5) +ts_covariance(mdl262_deltapredictebitd_q_predict, pv103_mbds_topofbook_mbds_mean, 60) +ts_covariance(est_q_eps_std_3mth_ago, pv87_interval_bidsize_skewness, 250) +ts_covariance(anl82_oprq_profitability_profitability10, pv103_mbds_topofbook_mbds_mean, 60) +ts_covariance(anl15_ebt_s_cal_fy3_mean, pv52_asdaq_order_size_code, 5) +ts_covariance(mdl116_epsyld_fy2_trendpredict_model_mada, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 20) +ts_covariance(pv87_2_netprofit_rep_qf_matrix_p1_low, pv104_masz_mean, 250) +ts_covariance(fnd28_value_18841a, pv104_lbsz_mean, 20) +ts_covariance(pv20_sal_indicator_p_feature1, pv87_interval_asksizeinterval_bidsize_rankcorrel, 5) +ts_covariance(anl14_high_ntp_fp2, pv87_interval_bidsizeinterval_volume_correlation, 20) +ts_covariance(mdl109_d_mtl_dlyspe, pv104_tbsz_mean, 5) +ts_covariance(anl14_stddev_ntp_fy1, pv103_sbsz_mean, 5) +ts_covariance(anl69_roe_expected_report_dt, pv52_yse_american_order_size_code, 60) +ts_covariance(mdl77_omomemtumanalystmodel_qma_mktresponse, pv64_dif_stal_fund_creation_unit_size, 250) +ts_covariance(oth460_usa_compustat_q1_dl8_epspxq_l4, pv104_hbsz_mean, 60) +ts_covariance(anl10_ebtfq2_pred_surps_v0_964, pv103_1m_mlrt_mean, 5) +ts_covariance(pv87_daily_ann_matrix_r1_net_income_normalized_consensus_mean_numnochangeunfiltered, oth567score_company_size, 250) +ts_covariance(quarterly_retained_earnings_total, pv87_interval_asksize_median, 5) +ts_covariance(pv20_ebt_indicator_q_feature5, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(fnd72_pit_or_is_a_is_interest_inc, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(mdl77_earningsmomemtummodel_fc_fqsurstd, oth551_beta_size, 250) +ts_covariance(fnd65_totalcap_cusip_mad3yttmni, pv87_interval_asksize_skewness, 60) +ts_covariance(pv20_opr_indicator_o_feature7, pv104_insm_mean, 5) +ts_covariance(earning_time_type, pv104_lasz_mean, 5) +ts_covariance(mdl177_2_historicalgrowthfactor_chg3yepsp, oth567_deltascore_company_size_432, 250) +ts_covariance(mdl211_saly_deltaprofitability_profitability9, fnd31_ohlsonscore, 250) +ts_covariance(mdl262_eps_oeps12_mae, pv104_masz_mean, 5) +ts_covariance(mdl264_uopiq_class, fnd72_pit_or_cr_q_debt_to_mkt_cap, 250) +ts_covariance(annual_retained_earnings_total_fast_d1, pv103_maus_mean, 60) +ts_covariance(anl15_bps_ind_12_m_pe, oth551_resret_size, 60) +ts_covariance(oth401_game_earning_smooth, oth567score_company_size, 60) +ts_covariance(mdl230_us5000_cusip_altmanz, pv103_htsz_mean, 20) +ts_covariance(mdl211_netq_profitability_profitability7, fund_total_size, 250) +ts_covariance(anl15_ebtgics_ind_18_m_cos_dn, pv103_maus_mean, 60) +ts_covariance(mdl264_usa_compustat_q1_dl8_epspiq_l1, mdl230_us5000_cusip_ohlsonscore, 5) +ts_covariance(mdl262_trkdpitpredictiveebitda_prediction, oth551_r2_size, 250) +ts_covariance(pv20_ebt_indicator_7_feature2, pv104_masz_mean, 60) +ts_covariance(pv87_2_operatingprofit_af_matrix_p1_dts, pv98_tbds_mean, 60) +ts_covariance(fnd28_ishta_value_01751a, pv64_dif_fund_creation_unit_size, 20) +ts_covariance(oth460_ciac_class, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(mdl26_v14_mstchg_pct_f12m_rnngs_90, pv103_maks_topofbook_maks_mean, 20) +ts_covariance(anl44_netprofit_gaap_best_cur_fiscal_qtr_period, company_offer_total_size, 60) +ts_covariance(fnd72_pit_or_cr_q_announcement_dt, pv87_interval_asksize_numintervalsincehigh, 250) +ts_covariance(earnings_announcement_time_of_day_fast_d1, pv52_asdaq_bx_order_size_code, 20) +ts_covariance(fnd28_bdea_value_18854a, pv81_sbsl, 60) +ts_covariance(anl82_ebtq_deltaprofitability_profitability5, oth567score_company_size_358, 20) +ts_covariance(pv87_pos_earnings_matrix_bee_sum, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(pv20_ebt_indicator_6_feature6, pv103_lbsz_mean, 5) +ts_covariance(anl15_ebtgics_ind_cal_fy1_6m_chg, company_offer_total_size, 250) +ts_covariance(mdl262_ninc_trkdpitdeltapredict_funda_mae, pv87_interval_asksizeinterval_bidsize_correlation, 5) +ts_covariance(fnd28_wsfsq_value_01451q, company_offer_size_value, 5) +ts_covariance(oth432_deltapredictni_a_predict, mdl177_2_liquidityriskfactor_ohlsonscore, 20) +ts_covariance(mdl354_group_pt12yf_dlyspe, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(anl15_cpsgics_s_18_m_pe, pv64_trr_cur_mkt_cap, 5) +ts_covariance(mdl262_predictiveebt_a_predict, mdl177_liquidityriskfactor_ohlsonscore_alt, 5) +ts_covariance(mdl262_deltapredictebit_q_predict, pv81_zsat, 5) +ts_covariance(anl10_ebtrevise_ratio_to_consensus_fq2_1011, pv81_zsbl, 5) +ts_covariance(fnd72_pit_or_cr_q_prof_margin, mdl230_totalcap_cusip_ohlsonscore, 250) +ts_covariance(mdl230_totalcap_cusip_rev6fy2, pv81_zsbl, 5) +ts_covariance(mdl211_ebtq_deltaprofitability_profitability12, pv103_hasz_mean, 5) +ts_covariance(mdl26_rvsnclstr_vg_rvsn_pr_fq1_rnngs, mdl77_liquidityriskfactor_ohlsonscore, 5) +ts_covariance(anl15_ebtgics_ind_cal_fy3_total, fund_total_size, 250) +ts_covariance(anl14_stddev_ntp_fp1, pv87_interval_asksize_std, 20) +ts_covariance(fnd72_pit_or_cr_a_com_eqy_to_tot_asset, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(pv87_ann_matrix_net_income_normalized_estimate_low, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(oth460_3l_qacf, pv104_tbsz_mean, 20) +ts_covariance(anl10_epsinnovate_decrease_fq2, pv52_yse_national_order_size_code, 20) +ts_covariance(mdl264_usa_compustat_q1_dl8_nopiq_l4, pv64_trr_stal_cur_mkt_cap, 250) +ts_covariance(anl10_nersmun_1yf_2417, pv87_interval_bidsize_std, 60) +ts_covariance(anl14_high_ebitda_fp5, pv104_lasz_mean, 250) +ts_covariance(fnd7_ointfund_qipspe, pv52_yse_arca_order_size_code, 20) +ts_covariance(anl82_oprq_profitability_profitability1, pv52_yse_national_order_size_code, 20) +ts_covariance(count_neutral_profitability_summary_fast_d1, pv87_interval_asksizeinterval_slippage_rankcorrel, 20) +ts_covariance(est_12m_pre_mean_3mth_ago, pv64_dif_stal_fund_creation_unit_size, 5) +ts_covariance(mdl26_v14_nnlyst_rvsng_dwn_fy1_rnngs_14, pv104_tasz_mean, 60) +ts_covariance(anl10_ebsfy2_pred_surps_v0, pv87_interval_asksizeinterval_bidsize_rankcorrel, 60) +ts_covariance(oth432_rasv2splitprofitabilityebt_ttm_profitability5, mdl230_totalcap_cusip_ohlsonscore, 20) +ts_covariance(fnd7_ointfund_qiim, pv103_sbps_mean, 250) +ts_covariance(mdl262_acae_q_profitability_profitability8, pv103_tbsz_mean, 60) +ts_covariance(fnd89_csjones_industry_major_14, pv87_interval_bidsize_skewness, 20) +ts_covariance(mdl230_allcap_sedol_aor, pv81_trlt, 250) +ts_covariance(mdl262_compustat_models_profitability7, pv103_mlrt_topofbook_mlrt_mean, 250) +ts_covariance(anl10_nerrevise_ratio_to_consensus_fq2_2016, pv103_sbsz_mean, 20) +ts_covariance(fnd65_us5000_cusip_divcov, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(pv87_weightedavg60_group_ess_earnings, pv81_stlh, 20) +ts_covariance(pretax_income_total, pv104_tasz_mean, 250) +ts_covariance(mdl264_onet_l1, oth137_avg_txn_val, 20) +ts_covariance(fnd2_itxreexftfedstyitxrt, mdl230_allcap_sedol_ohlsonscore, 60) +ts_covariance(anl10_ebsnormal_decrease_fy2, pv64_dif_fund_creation_unit_size, 60) +ts_covariance(oth432_rasv2splitprofitabilityni_ttm_profitability1, pv81_stlh, 250) +ts_covariance(anl14_numofests_ntp_fy2, pv87_interval_bidsize_numintervalsincelow, 250) +ts_covariance(mdl211_saly_deltaprofitability_profitability9, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(fnd23_intfvm_ipos, nws31_bodysize, 5) +ts_covariance(mdl211_salq_deltaprofitability_profitability7, pv87_interval_asksize_std, 60) +ts_covariance(fnd89_major_11_31, pv81_sasl, 5) +ts_covariance(pv20_indicator_0_feature0_121, pv103_lbsz_mean, 5) +ts_covariance(pv20_eps_indicator_2_feature0, nws31_bodysize, 5) +ts_covariance(pv87_net_income_normalized_of_estimates_scale, pv87_interval_asksize_mean, 5) +ts_covariance(pv20_ebt_indicator_q_feature11, oth567_deltascore_company_size_432, 60) +ts_covariance(mdl211_ebty_deltaprofitability_profitability5, pv103_1m_mlrt_mean, 20) +ts_covariance(anl10_nerrevise_value_fq1_2012, pv87_interval_asksizeinterval_slippage_correlation, 60) +ts_covariance(act_12m_opr_value, pv98_quote_size_mean, 5) +ts_covariance(pv20_gps_indicator_7_feature11, pv87_interval_asksizeinterval_bidsize_correlation, 250) +ts_covariance(fnd6_cptmfmq_opepsq, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(anl15_ebtgics_gr_cal_fy1_3m_chg, pv104_masz_mean, 250) +ts_covariance(fnd7_ointhstfundfn_hfqspepo, fnd65_totalcap_cusip_ohlsonscore, 60) +ts_covariance(mdl262_oiadpq_profitability_profitability3, pv103_1m_tlrt_mean, 5) +ts_covariance(pv20_opr_indicator_n_feature2, pv52_yse_order_size_code, 250) +ts_covariance(pv20_sal_indicator_2_feature12, mdl77_2liquidityriskfactor_ohlsonscore, 60) +ts_covariance(quarterly_earnings_before_tax_total, pv103_htsz_mean, 20) +ts_covariance(pv20_pre_indicator_n_feature10, pv104_tlrt_mean, 250) +ts_covariance(fnd72_s_pit_or_is_q_earn_for_common, pv87_interval_asksizeinterval_volume_correlation, 20) +ts_covariance(anl82_salq_profitability_profitability1, pv103_maus_mean, 5) +ts_covariance(fnd65_totalcap_cusip_mpoghc, pv104_tasz_mean, 5) +ts_covariance(mdl177_historicalgrowthfactor_pctchg3yeps, pv81_trlt, 20) +ts_covariance(mdl26_bld_stmt_flg_fq2_rnngs, fnd65_totalcap_cusip_ohlsonscore, 60) +ts_covariance(anl4_ptpr_number, pv52_asdaq_psx_order_size_code, 250) +ts_covariance(earning_fiscal_year_end, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(fnd28_newa2_value_09216a, nws31_d1_bodysize, 60) +ts_covariance(est_q_eps_std_4wks_ago, pv87_interval_bidsize_skewness, 5) +ts_covariance(anl14_high_eps_fp5, pv103_laks_mean, 60) +ts_covariance(mdl264_viat_l3, mdl230_allcap_sedol_ohlsonscore, 250) +ts_covariance(pv20_opr_indicator_1_feature1, pv103_sbsz_mean, 60) +ts_covariance(mdl262_che_profitability_profitability2, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 5) +ts_covariance(anl69_dps_expected_report_time, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(mdl26_p_yld_pct_stm_fy1, pv104_hbsz_mean, 60) +ts_covariance(anl82_opry_deltaprofitability_profitability3, pv104_mbsz_mean, 5) +ts_covariance(est_12m_gps_std_28d, pv104_lbsz_mean, 20) +ts_covariance(mdl77_2liquidityriskfactor_impduration, pv103_tlrt_topofbook_tlrt_mean, 60) +ts_covariance(mdl264_epspi_class, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 5) +ts_covariance(oth460_usa_compustat_q1_dl8_nopiq_l4, pv103_mlrt_topofbook_mlrt_mean, 250) +ts_covariance(earning_time_type_fast_d1, pv103_hbsz_mean, 20) +ts_covariance(anl82_opry_y1_madp, pv64_trr_cur_mkt_cap, 60) +ts_covariance(pv20_net_indicator_q_feature0, company_offer_total_size, 60) +ts_covariance(fnd65_totalcap_cusip_rev3my1std, mdl248_avg_txn_val, 5) +ts_covariance(fnd23_icsm_m_caic, pv103_tlrt_topofbook_tlrt_mean, 250) +ts_covariance(pe_ratio_relative_component_rank, company_size_sentiment_score, 250) +ts_covariance(mdl26_lw_stmt_chng_fy1_rnngs_30, pv87_interval_bidsize_mean, 5) +ts_covariance(pv20_pre_indicator_1_feature11, pv103_tbsz_mean, 60) +ts_covariance(mdl262_txtq_compustatdeltapredict_funda_madp, fnd65_allcap_sedol_ohlsonscore, 250) +ts_covariance(anl69_sales_best_eeps_nxt_yr, pv103_1m_maks_mean, 60) +ts_covariance(anl44_netprofit_gaap_best_eeps_nxt_yr, pv104_lsas_mean, 60) +ts_covariance(anl4_epsr_high, nws31_d1_bodysize, 20) +ts_covariance(oth432_saleq_profitability_profitability9, pv98_tbds_mean, 20) diff --git a/main.py b/main.py index 5186d58..10fd0d7 100644 --- a/main.py +++ b/main.py @@ -53,9 +53,9 @@ SILICONFLOW_BASE_URL = "https://api.siliconflow.cn/v1" MODELS = [ 'Pro/deepseek-ai/DeepSeek-V3.1-Terminus', # 'deepseek-ai/DeepSeek-V3.2-Exp', - # 'Qwen/Qwen3-VL-235B-A22B-Instruct', + 'Qwen/Qwen3-VL-235B-A22B-Instruct', # 'Pro/moonshotai/Kimi-K2-Thinking', - 'MiniMaxAI/MiniMax-M2', + # 'MiniMaxAI/MiniMax-M2', # 'zai-org/GLM-4.6', # 'inclusionAI/Ring-flash-2.0', # 'inclusionAI/Ling-flash-2.0', diff --git a/manual_prompt/2026/01/22/manual_prompt_20260122135326.txt b/manual_prompt/2026/01/22/manual_prompt_20260122135326.txt new file mode 100644 index 0000000..c34a280 --- /dev/null +++ b/manual_prompt/2026/01/22/manual_prompt_20260122135326.txt @@ -0,0 +1,520 @@ +供应商账款集中度溢价 +在供应链管理中，供应商集中度过高会增加企业供应中断风险，但投资者往往忽视这一风险，导致高集中度企业被系统性高估，形成风险溢价。多空逻辑：多高集中度企业（因风险被低估而高估），空低集中度企业（风险被正确认价而合理定价）。 +核心指标为前五大供应商销售额占比，需进行行业中性化处理以消除行业特性影响，并采用滚动平均法处理缺失值。同时引入应收账款周转率和存货周转率作为辅助验证变量，以检验因子与运营效率的相关性。 + +*=========================================================================================* +输出格式： +输出必须是且仅是纯文本。 +每一行是一个完整、独立、语法正确的WebSim表达式。 +严禁任何形式的解释、编号、标点包裹（如引号）、Markdown格式或额外文本。 +===================== !!! 重点(输出方式) !!! ===================== +现在，请严格遵守以上所有规则，开始生成可立即在WebSim中运行的复合因子表达式。 +不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 +**输出格式**(一行一个表达式, 每个表达式中间需要添加一个空行, 只要表达式本身, 不需要赋值, 不要解释, 不需要序号, 也不要输出多余的东西)： +表达式 +表达式 +表达式 +... +表达式 +================================================================= +重申：请确保所有表达式都使用WorldQuant WebSim平台函数，不要使用pandas、numpy或其他Python库函数。输出必须是一行有效的WQ表达式。 +以下是我的账号有权限使用的操作符, 请严格按照操作符, 以及我提供的数据集, 进行生成,组合 50 个 alpha： +不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 +================================================================= +**操作符汇总 +**算术运算符 (Arithmetic): +abs(x) - 绝对值 +add(x, y, filter=false) - 加法 (x + y) +densify(x) - 分组字段稠密化 +divide(x, y) - 除法 (x / y) +inverse(x) - 倒数 (1/x) +log(x) - 自然对数 +max(x, y, ..) - 最大值 +min(x, y, ..) - 最小值 +multiply(x, y, filter=false) - 乘法 (x * y) +power(x, y) - 幂运算 (x^y) +reverse(x) - 取反 (-x) +sign(x) - 符号函数 +signed_power(x, y) - 保留符号的幂运算 +sqrt(x) - 平方根 +subtract(x, y, filter=false) - 减法 (x - y) +to_nan(x, value=0, reverse=false) - 值与NaN转换 +**逻辑运算符 (Logical): +and(input1, input2) - 逻辑与 +if_else(input1, input2, input3) - 条件判断 +input1 < input2 - 小于比较 +input1 <= input2 - 小于等于 +input1 == input2 - 等于比较 +input1 > input2 - 大于比较 +input1 >= input2 - 大于等于 +input1 != input2 - 不等于 +is_nan(input) - 是否为NaN +not(x) - 逻辑非 +or(input1, input2) - 逻辑或 +**时间序列运算符 (Time Series): +days_from_last_change(x) - 上次变化天数 +hump(x, hump=0.01) - 限制变化幅度 +jump_decay(x, d, sensitivity=0.5, force=0.1) - 跳跃衰减 +kth_element(x, d, k) - 第K个值 +last_diff_value(x, d) - 最后一个不同值 +ts_arg_max(x, d) - 最大值相对索引 +ts_arg_min(x, d) - 最小值相对索引 +ts_av_diff(x, d) - 与均值的差 +ts_backfill(x, lookback=d, k=1, ignore="NAN") - 回填 +ts_corr(x, y, d) - 时间序列相关性 +ts_count_nans(x, d) - NaN计数 +ts_covariance(y, x, d) - 协方差 +ts_decay_linear(x, d, dense=false) - 线性衰减 +ts_delay(x, d) - 延迟值 +ts_delta(x, d) - 差值 (x - 延迟值) +ts_max(x, d) - 时间序列最大值 +ts_mean(x, d) - 时间序列均值 +ts_min(x, d) - 时间序列最小值 +ts_product(x, d) - 时间序列乘积 +ts_quantile(x, d, driver="gaussian") - 分位数 +ts_rank(x, d, constant=0) - 时间序列排名 +ts_regression(y, x, d, lag=0, rettype=0) - 回归分析 +ts_scale(x, d, constant=0) - 时间序列缩放 +ts_std_dev(x, d) - 时间序列标准差 +ts_step(1) - 天数计数器 +ts_sum(x, d) - 时间序列求和 +ts_target_tvr_decay(x, lambda_min=0, lambda_max=1, target_tvr=0.1) - 目标换手率衰减 +ts_target_tvr_delta_limit(x, y, lambda_min=0, lambda_max=1, target_tvr=0.1) - 目标换手率差值限制 +ts_zscore(x, d) - 时间序列Z分数 +**横截面运算符 (Cross Sectional): +normalize(x, useStd=false, limit=0.0) - 标准化 +quantile(x, driver=gaussian, sigma=1.0) - 分位数转换 +rank(x, rate=2) - 排名 +scale(x, scale=1, longscale=1, shortscale=1) - 缩放 +scale_down(x, constant=0) - 按比例缩放 +vector_neut(x, y) - 向量中性化 +winsorize(x, std=4) - 缩尾处理 +zscore(x) - Z分数 +**向量运算符 (Vector): +vec_avg(x) - 向量均值 +vec_max(x) - 向量最大值 +vec_min(x) - 向量最小值 +vec_sum(x) - 向量求和 +**变换运算符 (Transformational): +bucket(rank(x), range="0,1,0.1" or buckets="2,5,6,7,10") - 分桶 +generate_stats(alpha) - 生成统计量 +trade_when(x, y, z) - 条件交易 +**分组运算符 (Group): +combo_a(alpha, nlength=250, mode='algo1') - 组合Alpha +group_backfill(x, group, d, std=4.0) - 分组回填 +group_cartesian_product(g1, g2) - 笛卡尔积分组 +group_max(x, group) - 分组最大值 +group_mean(x, weight, group) - 分组均值 +group_min(x, group) - 分组最小值 +group_neutralize(x, group) - 分组中性化 +group_rank(x, group) - 分组排名 +group_scale(x, group) - 分组缩放 +group_zscore(x, group) - 分组Z分数 +**特殊运算符 (Special): +in - 包含判断 +self_corr(input) - 自相关性 +universe_size - 宇宙大小 +**归约运算符 (Reduce): +reduce_avg(input, threshold=0) - 平均值归约 +reduce_choose(input, nth, ignoreNan=true) - 选择归约 +reduce_count(input, threshold) - 计数归约 +reduce_ir(input) - IR归约 +reduce_kurtosis(input) - 峰度归约 +reduce_max(input) - 最大值归约 +reduce_min(input) - 最小值归约 +reduce_norm(input) - 范数归约 +reduce_percentage(input, percentage=0.5) - 百分比归约 +reduce_powersum(input, constant=2, precise=false) - 幂和归约 +reduce_range(input) - 范围归约 +reduce_skewness(input) - 偏度归约 +reduce_stddev(input, threshold=0) - 标准差归约 +reduce_sum(input) - 求和归约 + +以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子 + +========================= 操作符开始 ======================================= +注意: Operator: 后面的是操作符(是可以使用的), +Description: 此字段后面的是操作符对应的描述或使用说明(禁止使用, 仅供参考), Description字段后面的内容是使用说明, 不是操作符 +特别注意!!!! 必须按照操作符字段Operator的使用说明生成 alphaOperator: abs(x) +Description: Absolute value of x +Operator: add(x, y, filter = false) +Description: Add all inputs (at least 2 inputs required). If filter = true, filter all input NaN to 0 before adding +Operator: densify(x) +Description: Converts a grouping field of many buckets into lesser number of only available buckets so as to make working with grouping fields computationally efficient +Operator: divide(x, y) +Description: x / y +Operator: inverse(x) +Description: 1 / x +Operator: log(x) +Description: Natural logarithm. For example: Log(high/low) uses natural logarithm of high/low ratio as stock weights. +Operator: max(x, y, ..) +Description: Maximum value of all inputs. At least 2 inputs are required +Operator: min(x, y ..) +Description: Minimum value of all inputs. At least 2 inputs are required +Operator: multiply(x ,y, ... , filter=false) +Description: Multiply all inputs. At least 2 inputs are required. Filter sets the NaN values to 1 +Operator: power(x, y) +Description: x ^ y +Operator: reverse(x) +Description: - x +Operator: sign(x) +Description: if input > 0, return 1; if input < 0, return -1; if input = 0, return 0; if input = NaN, return NaN; +Operator: signed_power(x, y) +Description: x raised to the power of y such that final result preserves sign of x +Operator: sqrt(x) +Description: Square root of x +Operator: subtract(x, y, filter=false) +Description: x-y. If filter = true, filter all input NaN to 0 before subtracting +Operator: and(input1, input2) +Description: Logical AND operator, returns true if both operands are true and returns false otherwise +Operator: if_else(input1, input2, input 3) +Description: If input1 is true then return input2 else return input3. +Operator: input1 < input2 +Description: If input1 < input2 return true, else return false +Operator: input1 <= input2 +Description: Returns true if input1 <= input2, return false otherwise +Operator: input1 == input2 +Description: Returns true if both inputs are same and returns false otherwise +Operator: input1 > input2 +Description: Logic comparison operators to compares two inputs +Operator: input1 >= input2 +Description: Returns true if input1 >= input2, return false otherwise +Operator: input1!= input2 +Description: Returns true if both inputs are NOT the same and returns false otherwise +Operator: is_nan(input) +Description: If (input == NaN) return 1 else return 0 +Operator: not(x) +Description: Returns the logical negation of x. If x is true (1), it returns false (0), and if input is false (0), it returns true (1). +Operator: or(input1, input2) +Description: Logical OR operator returns true if either or both inputs are true and returns false otherwise +Operator: days_from_last_change(x) +Description: Amount of days since last change of x +Operator: hump(x, hump = 0.01) +Description: Limits amount and magnitude of changes in input (thus reducing turnover) +Operator: kth_element(x, d, k) +Description: Returns K-th value of input by looking through lookback days. This operator can be used to backfill missing data if k=1 +Operator: last_diff_value(x, d) +Description: Returns last x value not equal to current x value from last d days +Operator: ts_arg_max(x, d) +Description: Returns the relative index of the max value in the time series for the past d days. If the current day has the max value for the past d days, it returns 0. If previous day has the max value for the past d days, it returns 1 +Operator: ts_arg_min(x, d) +Description: Returns the relative index of the min value in the time series for the past d days; If the current day has the min value for the past d days, it returns 0; If previous day has the min value for the past d days, it returns 1. +Operator: ts_av_diff(x, d) +Description: Returns x - tsmean(x, d), but deals with NaNs carefully. That is NaNs are ignored during mean computation +Operator: ts_backfill(x,lookback = d, k=1, ignore="NAN") +Description: Backfill is the process of replacing the NAN or 0 values by a meaningful value (i.e., a first non-NaN value) +Operator: ts_corr(x, y, d) +Description: Returns correlation of x and y for the past d days +Operator: ts_count_nans(x ,d) +Description: Returns the number of NaN values in x for the past d days +Operator: ts_covariance(y, x, d) +Description: Returns covariance of y and x for the past d days +Operator: ts_decay_linear(x, d, dense = false) +Description: Returns the linear decay on x for the past d days. Dense parameter=false means operator works in sparse mode and we treat NaN as 0. In dense mode we do not. +Operator: ts_delay(x, d) +Description: Returns x value d days ago +Operator: ts_delta(x, d) +Description: Returns x - ts_delay(x, d) +Operator: ts_mean(x, d) +Description: Returns average value of x for the past d days. +Operator: ts_product(x, d) +Description: Returns product of x for the past d days +Operator: ts_quantile(x,d, driver="gaussian" ) +Description: It calculates ts_rank and apply to its value an inverse cumulative density function from driver distribution. Possible values of driver (optional ) are "gaussian", "uniform", "cauchy" distribution where "gaussian" is the default. +Operator: ts_rank(x, d, constant = 0) +Description: Rank the values of x for each instrument over the past d days, then return the rank of the current value + constant. If not specified, by default, constant = 0. +Operator: ts_regression(y, x, d, lag = 0, rettype = 0) +Description: Returns various parameters related to regression function +Operator: ts_scale(x, d, constant = 0) +Description: Returns (x - ts_min(x, d)) / (ts_max(x, d) - ts_min(x, d)) + constant. This operator is similar to scale down operator but acts in time series space +Operator: ts_std_dev(x, d) +Description: Returns standard deviation of x for the past d days +Operator: ts_step(1) +Description: Returns days' counter +Operator: ts_sum(x, d) +Description: Sum values of x for the past d days. +Operator: ts_zscore(x, d) +Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean: (x - tsmean(x,d)) / tsstddev(x,d). This operator may help reduce outliers and drawdown. +Operator: normalize(x, useStd = false, limit = 0.0) +Description: Calculates the mean value of all valid alpha values for a certain date, then subtracts that mean from each element +Operator: quantile(x, driver = gaussian, sigma = 1.0) +Description: Rank the raw vector, shift the ranked Alpha vector, apply distribution (gaussian, cauchy, uniform). If driver is uniform, it simply subtract each Alpha value with the mean of all Alpha values in the Alpha vector +Operator: rank(x, rate=2) +Description: Ranks the input among all the instruments and returns an equally distributed number between 0.0 and 1.0. For precise sort, use the rate as 0 +Operator: scale(x, scale=1, longscale=1, shortscale=1) +Description: Scales input to booksize. We can also scale the long positions and short positions to separate scales by mentioning additional parameters to the operator +Operator: winsorize(x, std=4) +Description: Winsorizes x to make sure that all values in x are between the lower and upper limits, which are specified as multiple of std. +Operator: zscore(x) +Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean +Operator: vec_avg(x) +Description: Taking mean of the vector field x +Operator: vec_sum(x) +Description: Sum of vector field x +Operator: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10") +Description: Convert float values into indexes for user-specified buckets. Bucket is useful for creating group values, which can be passed to GROUP as input +Operator: trade_when(x, y, z) +Description: Used in order to change Alpha values only under a specified condition and to hold Alpha values in other cases. It also allows to close Alpha positions (assign NaN values) under a specified condition +Operator: group_backfill(x, group, d, std = 4.0) +Description: If a certain value for a certain date and instrument is NaN, from the set of same group instruments, calculate winsorized mean of all non-NaN values over last d days +Operator: group_mean(x, weight, group) +Description: All elements in group equals to the mean +Operator: group_neutralize(x, group) +Description: Neutralizes Alpha against groups. These groups can be subindustry, industry, sector, country or a constant +Operator: group_rank(x, group) +Description: Each elements in a group is assigned the corresponding rank in this group +Operator: group_scale(x, group) +Description: Normalizes the values in a group to be between 0 and 1. (x - groupmin) / (groupmax - groupmin) +Operator: group_zscore(x, group) +Description: Calculates group Z-score - numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. zscore = (data - mean) / stddev of x for each instrument within its group. +========================= 操作符结束 ======================================= + +========================= 数据字段开始 ======================================= +注意: data_set_name: 后面的是数据字段(可以使用), description: 此字段后面的是数据字段对应的描述或使用说明(不能使用) + +{'id': 5730, 'data_set_name': '可以使用:anl40_netturnoverrate', 'description': '不可使用,仅供参考:TotalChanges / (OldCount + NewCount). No record before 20160729.'} +{'id': 5743, 'data_set_name': '可以使用:anl40_turnoverrate', 'description': '不可使用,仅供参考:MoveOut / (OldCount + NewCount). No record before 20160729.'} +{'id': 6839, 'data_set_name': '可以使用:anl49_backfill_inventoryindicator', 'description': '不可使用,仅供参考:Inventory indicator'} +{'id': 6840, 'data_set_name': '可以使用:anl49_backfill_inventoryturnoverindicator', 'description': '不可使用,仅供参考:inventory turnover indicator'} +{'id': 6925, 'data_set_name': '可以使用:anl49_inventoryindicator', 'description': '不可使用,仅供参考:Inventory indicator'} +{'id': 6926, 'data_set_name': '可以使用:anl49_inventoryturnoverindicator', 'description': '不可使用,仅供参考:inventory turnover indicator'} +{'id': 78578, 'data_set_name': '可以使用:fnd17_ainventory', 'description': '不可使用,仅供参考:Inventory - most recent fiscal year'} +{'id': 78752, 'data_set_name': '可以使用:fnd17_qinventory', 'description': '不可使用,仅供参考:Inventory - most recent quarter'} +{'id': 78929, 'data_set_name': '可以使用:fn_allowance_for_doubtful_accounts_receivable_a', 'description': '不可使用,仅供参考:For an unclassified balance sheet, a valuation allowance for receivables due a company that are expected to be uncollectible.'} +{'id': 78930, 'data_set_name': '可以使用:fn_allowance_for_doubtful_accounts_receivable_q', 'description': '不可使用,仅供参考:For an unclassified balance sheet, a valuation allowance for receivables due a company that are expected to be uncollectible.'} +{'id': 79041, 'data_set_name': '可以使用:fn_interest_payable_a', 'description': '不可使用,仅供参考:Carrying value as of the balance sheet date of [accrued] interest payable on all forms of debt, including trade payables, that has been incurred and is unpaid. For classified balance sheets, used to reflect the current portion of the liabilities (due within 1 year or within the normal operating cycle if longer); for unclassified balance sheets, used to reflect the total liabilities (regardless of due date).'} +{'id': 79042, 'data_set_name': '可以使用:fn_interest_payable_q', 'description': '不可使用,仅供参考:Carrying value as of the balance sheet date of accrued interest payable on all forms of debt, including trade payables, that has been incurred and is unpaid. For classified balance sheets, used to reflect the current portion of the liabilities (due within 1 year or within the normal operating cycle if longer); for unclassified balance sheets, used to reflect the total liabilities (regardless of due date).'} +{'id': 79106, 'data_set_name': '可以使用:fn_taxes_payable_a', 'description': '不可使用,仅供参考:Carrying value as of the balance sheet date of obligations incurred and payable for statutory income, sales, use, payroll, excise, real, property, and other taxes. For classified balance sheets, used to reflect the current portion of the liabilities (due within 1 year or within the normal operating cycle if longer); for unclassified balance sheets, used to reflect the total liabilities (regardless of due date).'} +{'id': 79107, 'data_set_name': '可以使用:fn_taxes_payable_q', 'description': '不可使用,仅供参考:Carrying value as of the balance sheet date of obligations incurred and payable for statutory income, sales, use, payroll, excise, real, property and other taxes. For classified balance sheets, used to reflect the current portion of the liabilities (due within 1 year or within the normal operating cycle if longer); for unclassified balance sheets, used to reflect the total liabilities (regardless of due date).'} +{'id': 79143, 'data_set_name': '可以使用:fnd2_a_inventoryfinishedgoods', 'description': '不可使用,仅供参考:Amount before valuation and LIFO reserves of completed merchandise or goods expected to be sold within 1 year or operating cycle, if longer.'} +{'id': 79144, 'data_set_name': '可以使用:fnd2_a_inventoryrawmaterials', 'description': '不可使用,仅供参考:Amount before valuation and LIFO reserves of raw materials expected to be sold, or consumed within 1 year or operating cycle, if longer.'} +{'id': 79223, 'data_set_name': '可以使用:fnd2_q_inventoryfinishedgoods', 'description': '不可使用,仅供参考:Amount before valuation and LIFO reserves of completed merchandise or goods expected to be sold within 1 year or operating cycle, if longer.'} +{'id': 79224, 'data_set_name': '可以使用:fnd2_q_inventoryrawmaterials', 'description': '不可使用,仅供参考:Amount before valuation and LIFO reserves of raw materials expected to be sold, or consumed within 1 year or operating cycle, if longer.'} +{'id': 79249, 'data_set_name': '可以使用:accounts_cash_and_equivalents', 'description': '不可使用,仅供参考:Total value of cash and cash equivalents at the end of the period.'} +{'id': 79250, 'data_set_name': '可以使用:accounts_current_assets_equity', 'description': '不可使用,仅供参考:Current assets related to equity accounts.'} +{'id': 79251, 'data_set_name': '可以使用:accounts_payable_current', 'description': '不可使用,仅供参考:Accounts payable due within one year.'} +{'id': 79252, 'data_set_name': '可以使用:accounts_payable_current_2', 'description': '不可使用,仅供参考:[Quarterly] Construction in Progress - Gross'} +{'id': 79253, 'data_set_name': '可以使用:accounts_payable_deferred', 'description': '不可使用,仅供参考:[Quarterly] Pension Obligation - Domestic'} +{'id': 79254, 'data_set_name': '可以使用:accounts_payable_noncurrent', 'description': '不可使用,仅供参考:Accounts payable that are not due within the next year.'} +{'id': 79255, 'data_set_name': '可以使用:accounts_payable_nontrade', 'description': '不可使用,仅供参考:Accounts payable not related to trade transactions.'} +{'id': 79256, 'data_set_name': '可以使用:accounts_payable_notes', 'description': '不可使用,仅供参考:Notes payable included in accounts payable.'} +{'id': 79257, 'data_set_name': '可以使用:accounts_payable_trade_creditors', 'description': '不可使用,仅供参考:Accounts payable to trade creditors.'} +{'id': 79258, 'data_set_name': '可以使用:accounts_payable_year_end', 'description': '不可使用,仅供参考:Accounts payable balance at fiscal year end.'} +{'id': 79259, 'data_set_name': '可以使用:accounts_receivable_current', 'description': '不可使用,仅供参考:Current accounts receivable at period end.'} +{'id': 79260, 'data_set_name': '可以使用:accounts_receivable_current_assets', 'description': '不可使用,仅供参考:Accounts receivable included in current assets for the annual period.'} +{'id': 79261, 'data_set_name': '可以使用:accounts_receivable_gross', 'description': '不可使用,仅供参考:Gross amount of accounts receivable outstanding.'} +{'id': 79262, 'data_set_name': '可以使用:accounts_receivable_gross_2', 'description': '不可使用,仅供参考:[Quarterly] Accounts Receivable - Trade, Gross'} +{'id': 79263, 'data_set_name': '可以使用:accounts_receivable_long_term', 'description': '不可使用,仅供参考:Restricted Cash – Long-Termrepresents cash or cash equivalents that are prepared for specific\r\npurposes, subject to long-term restrictions, and not readily available for operational uses.'} +{'id': 79264, 'data_set_name': '可以使用:accounts_receivable_total_5', 'description': '不可使用,仅供参考:Total accounts receivable as of the reporting date.'} +{'id': 79265, 'data_set_name': '可以使用:accounts_receivable_total_6', 'description': '不可使用,仅供参考:Total value of accounts receivable outstanding at period end.'} +{'id': 79266, 'data_set_name': '可以使用:accounts_total_current_assets', 'description': '不可使用,仅供参考:Total current assets as reported in accounts.'} +{'id': 79267, 'data_set_name': '可以使用:accounts_total_current_assets_2', 'description': '不可使用,仅供参考:Total current assets as reported in accounts.'} +{'id': 79268, 'data_set_name': '可以使用:accounts_total_receivables_current', 'description': '不可使用,仅供参考:Total current receivables as reported in accounts.'} +{'id': 79276, 'data_set_name': '可以使用:accrued_interest_payable', 'description': '不可使用,仅供参考:Interest expense that has been accrued but not yet paid.'} +{'id': 79277, 'data_set_name': '可以使用:accrued_interest_payable_2', 'description': '不可使用,仅供参考:Interest expense accrued but not yet paid.'} +{'id': 79291, 'data_set_name': '可以使用:allowance_for_doubtful_accounts', 'description': '不可使用,仅供参考:[Quarterly] Advertising Expense, Supplemental'} +{'id': 79332, 'data_set_name': '可以使用:current_tax_payable', 'description': '不可使用,仅供参考:Current tax payable as of the reporting date.'} +{'id': 79333, 'data_set_name': '可以使用:current_tax_receivable', 'description': '不可使用,仅供参考:Amount of tax receivables expected to be collected within one year.'} +{'id': 79399, 'data_set_name': '可以使用:fnd23_acc_payable', 'description': '不可使用,仅供参考:accounts payable'} +{'id': 80506, 'data_set_name': '可以使用:fnd23_tot_inventory', 'description': '不可使用,仅供参考:total inventory.'} +{'id': 80611, 'data_set_name': '可以使用:long_term_loans_payable', 'description': '不可使用,仅供参考:Outstanding long-term loans payable at period end.'} +{'id': 80620, 'data_set_name': '可以使用:long_term_tax_payable', 'description': '不可使用,仅供参考:Total value of long-term tax liabilities outstanding.'} +{'id': 80621, 'data_set_name': '可以使用:long_term_tax_payable_2', 'description': '不可使用,仅供参考:Long-term tax liabilities due beyond one year.'} +{'id': 80645, 'data_set_name': '可以使用:notes_payable_total_3', 'description': '不可使用,仅供参考:Total amount of notes payable outstanding at the reporting date.'} +{'id': 80662, 'data_set_name': '可以使用:other_current_receivables', 'description': '不可使用,仅供参考:Other receivables classified as current assets.'} +{'id': 80705, 'data_set_name': '可以使用:receivables_premium_total', 'description': '不可使用,仅供参考:Total value of premium receivables.'} +{'id': 80766, 'data_set_name': '可以使用:short_term_bonds_payable_2', 'description': '不可使用,仅供参考:Short-term bonds payable at the end of the period.'} +{'id': 80779, 'data_set_name': '可以使用:short_term_gross_premiums_payable', 'description': '不可使用,仅供参考:Short-term gross premiums payable at period end.'} +{'id': 80780, 'data_set_name': '可以使用:short_term_group_payables', 'description': '不可使用,仅供参考:Short-term payables to group companies.'} +{'id': 80793, 'data_set_name': '可以使用:short_term_loans_payable', 'description': '不可使用,仅供参考:Short-term loans payable outstanding at period end.'} +{'id': 80805, 'data_set_name': '可以使用:short_term_notes_payable', 'description': '不可使用,仅供参考:Short-term notes payable outstanding at period end.'} +{'id': 80806, 'data_set_name': '可以使用:short_term_notes_payable_matured', 'description': '不可使用,仅供参考:Short-term notes payable that matured during the period.'} +{'id': 80809, 'data_set_name': '可以使用:short_term_payables_other', 'description': '不可使用,仅供参考:[Quarterly] Total Plan Obligations'} +{'id': 80825, 'data_set_name': '可以使用:stock_dividends_payable', 'description': '不可使用,仅供参考:Dividends payable in the form of stock.'} +{'id': 80826, 'data_set_name': '可以使用:stock_dividends_payable_recorded', 'description': '不可使用,仅供参考:Stock dividends declared but not yet paid.'} +{'id': 80855, 'data_set_name': '可以使用:trade_payables_short_term', 'description': '不可使用,仅供参考:Short-term trade payables owed by the company.'} +{'id': 83103, 'data_set_name': '可以使用:annual_accounts_receivable_total', 'description': '不可使用,仅供参考:Total accounts receivable as of the year.'} +{'id': 83104, 'data_set_name': '可以使用:annual_accounts_receivable_total_fast_d1', 'description': '不可使用,仅供参考:Total accounts receivable as of the year.'} +{'id': 83141, 'data_set_name': '可以使用:annual_inventory_change_amount', 'description': '不可使用,仅供参考:Change in inventory during the year.'} +{'id': 83142, 'data_set_name': '可以使用:annual_inventory_change_amount_fast_d1', 'description': '不可使用,仅供参考:Change in inventory during the year.'} +{'id': 83155, 'data_set_name': '可以使用:annual_receivables_change_amount', 'description': '不可使用,仅供参考:Change in accounts receivable during the year.'} +{'id': 83156, 'data_set_name': '可以使用:annual_receivables_change_amount_fast_d1', 'description': '不可使用,仅供参考:Change in accounts receivable during the year.'} +{'id': 83179, 'data_set_name': '可以使用:fnd3_A_accpayable', 'description': '不可使用,仅供参考:Annual Accounts payable'} +{'id': 83180, 'data_set_name': '可以使用:fnd3_A_accreceivable', 'description': '不可使用,仅供参考:Annual Accounts receivable'} +{'id': 83212, 'data_set_name': '可以使用:fnd3_A_inventory', 'description': '不可使用,仅供参考:Annual Inventory'} +{'id': 83213, 'data_set_name': '可以使用:fnd3_A_inventoryincdec', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Inventory'} +{'id': 83226, 'data_set_name': '可以使用:fnd3_A_payables', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Accounts Payable'} +{'id': 83229, 'data_set_name': '可以使用:fnd3_A_receivables', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Receivables'} +{'id': 83249, 'data_set_name': '可以使用:fnd3_Aacctadj_accpayable', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Accounts payable'} +{'id': 83250, 'data_set_name': '可以使用:fnd3_Aacctadj_accreceivable', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Accounts receivable'} +{'id': 83282, 'data_set_name': '可以使用:fnd3_Aacctadj_inventory', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Increase or Decrease in Inventory'} +{'id': 83283, 'data_set_name': '可以使用:fnd3_Aacctadj_inventoryincdec', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Inventory'} +{'id': 83292, 'data_set_name': '可以使用:fnd3_Aacctadj_payables', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Increase or Decrease in Accounts Payable'} +{'id': 83296, 'data_set_name': '可以使用:fnd3_Aacctadj_receivables', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 83315, 'data_set_name': '可以使用:fnd3_Q_accpayable', 'description': '不可使用,仅供参考:Quarterly Accounts payable'} +{'id': 83316, 'data_set_name': '可以使用:fnd3_Q_accreceivable', 'description': '不可使用,仅供参考:Quarterly Accounts receivable'} +{'id': 83347, 'data_set_name': '可以使用:fnd3_Q_inventory', 'description': '不可使用,仅供参考:Quarterly Inventory'} +{'id': 83348, 'data_set_name': '可以使用:fnd3_Q_inventoryincdec', 'description': '不可使用,仅供参考:Quarterly Increase or Decrease in Inventory'} +{'id': 83360, 'data_set_name': '可以使用:fnd3_Q_payables', 'description': '不可使用,仅供参考:Quarterly Increase or Decrease in Accounts Payable'} +{'id': 83363, 'data_set_name': '可以使用:fnd3_Q_receivables', 'description': '不可使用,仅供参考:Quarterly Increase or Decrease in Receivables'} +{'id': 83383, 'data_set_name': '可以使用:fnd3_Qacctadj_accpayable', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Accounts payable'} +{'id': 83384, 'data_set_name': '可以使用:fnd3_Qacctadj_accreceivable', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Accounts receivable'} +{'id': 83415, 'data_set_name': '可以使用:fnd3_Qacctadj_inventory', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Inventory'} +{'id': 83416, 'data_set_name': '可以使用:fnd3_Qacctadj_inventoryincdec', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Inventory'} +{'id': 83425, 'data_set_name': '可以使用:fnd3_Qacctadj_payables', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Accounts Payable'} +{'id': 83429, 'data_set_name': '可以使用:fnd3_Qacctadj_receivables', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 83452, 'data_set_name': '可以使用:fnd3_a_accpayable', 'description': '不可使用,仅供参考:Annual Accounts payable'} +{'id': 83453, 'data_set_name': '可以使用:fnd3_a_accpayable_fast_d1', 'description': '不可使用,仅供参考:Annual Accounts payable'} +{'id': 83454, 'data_set_name': '可以使用:fnd3_a_accreceivable', 'description': '不可使用,仅供参考:Annual Accounts receivable'} +{'id': 83455, 'data_set_name': '可以使用:fnd3_a_accreceivable_fast_d1', 'description': '不可使用,仅供参考:Annual Accounts receivable'} +{'id': 83520, 'data_set_name': '可以使用:fnd3_a_inventory', 'description': '不可使用,仅供参考:Annual Inventory'} +{'id': 83521, 'data_set_name': '可以使用:fnd3_a_inventory_fast_d1', 'description': '不可使用,仅供参考:Annual Inventory'} +{'id': 83522, 'data_set_name': '可以使用:fnd3_a_inventoryincdec', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Inventory'} +{'id': 83523, 'data_set_name': '可以使用:fnd3_a_inventoryincdec_fast_d1', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Inventory'} +{'id': 83548, 'data_set_name': '可以使用:fnd3_a_payables', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Accounts Payable'} +{'id': 83549, 'data_set_name': '可以使用:fnd3_a_payables_fast_d1', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Accounts Payable'} +{'id': 83554, 'data_set_name': '可以使用:fnd3_a_receivables', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Receivables'} +{'id': 83555, 'data_set_name': '可以使用:fnd3_a_receivables_fast_d1', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Receivables'} +{'id': 83594, 'data_set_name': '可以使用:fnd3_aacctadj_accpayable', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Accounts payable'} +{'id': 83595, 'data_set_name': '可以使用:fnd3_aacctadj_accpayable_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Accounts payable'} +{'id': 83596, 'data_set_name': '可以使用:fnd3_aacctadj_accreceivable', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Accounts receivable'} +{'id': 83597, 'data_set_name': '可以使用:fnd3_aacctadj_accreceivable_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Accounts receivable'} +{'id': 83660, 'data_set_name': '可以使用:fnd3_aacctadj_inventory', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Increase or Decrease in Inventory'} +{'id': 83661, 'data_set_name': '可以使用:fnd3_aacctadj_inventory_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Increase or Decrease in Inventory'} +{'id': 83662, 'data_set_name': '可以使用:fnd3_aacctadj_inventoryincdec', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Inventory'} +{'id': 83663, 'data_set_name': '可以使用:fnd3_aacctadj_inventoryincdec_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Inventory'} +{'id': 83680, 'data_set_name': '可以使用:fnd3_aacctadj_payables', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Increase or Decrease in Accounts Payable'} +{'id': 83681, 'data_set_name': '可以使用:fnd3_aacctadj_payables_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Increase or Decrease in Accounts Payable'} +{'id': 83688, 'data_set_name': '可以使用:fnd3_aacctadj_receivables', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 83689, 'data_set_name': '可以使用:fnd3_aacctadj_receivables_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 83724, 'data_set_name': '可以使用:fnd3_q_accpayable', 'description': '不可使用,仅供参考:Quarterly Accounts payable'} +{'id': 83725, 'data_set_name': '可以使用:fnd3_q_accpayable_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accounts payable'} +{'id': 83726, 'data_set_name': '可以使用:fnd3_q_accreceivable', 'description': '不可使用,仅供参考:Quarterly Accounts receivable'} +{'id': 83727, 'data_set_name': '可以使用:fnd3_q_accreceivable_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accounts receivable'} +{'id': 83790, 'data_set_name': '可以使用:fnd3_q_inventory', 'description': '不可使用,仅供参考:Quarterly Inventory'} +{'id': 83791, 'data_set_name': '可以使用:fnd3_q_inventory_fast_d1', 'description': '不可使用,仅供参考:Quarterly Inventory'} +{'id': 83792, 'data_set_name': '可以使用:fnd3_q_inventoryincdec', 'description': '不可使用,仅供参考:Quarterly Increase or Decrease in Inventory'} +{'id': 83793, 'data_set_name': '可以使用:fnd3_q_inventoryincdec_fast_d1', 'description': '不可使用,仅供参考:Quarterly Increase or Decrease in Inventory'} +{'id': 83816, 'data_set_name': '可以使用:fnd3_q_payables', 'description': '不可使用,仅供参考:Quarterly Increase or Decrease in Accounts Payable'} +{'id': 83817, 'data_set_name': '可以使用:fnd3_q_payables_fast_d1', 'description': '不可使用,仅供参考:Quarterly Increase or Decrease in Accounts Payable'} +{'id': 83822, 'data_set_name': '可以使用:fnd3_q_receivables', 'description': '不可使用,仅供参考:Quarterly Increase or Decrease in Receivables'} +{'id': 83823, 'data_set_name': '可以使用:fnd3_q_receivables_fast_d1', 'description': '不可使用,仅供参考:Quarterly Increase or Decrease in Receivables'} +{'id': 83860, 'data_set_name': '可以使用:fnd3_qacctadj_accpayable', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Accounts payable'} +{'id': 83861, 'data_set_name': '可以使用:fnd3_qacctadj_accpayable_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Accounts payable'} +{'id': 83862, 'data_set_name': '可以使用:fnd3_qacctadj_accreceivable', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Accounts receivable'} +{'id': 83863, 'data_set_name': '可以使用:fnd3_qacctadj_accreceivable_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Accounts receivable'} +{'id': 83924, 'data_set_name': '可以使用:fnd3_qacctadj_inventory', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Inventory'} +{'id': 83925, 'data_set_name': '可以使用:fnd3_qacctadj_inventory_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Inventory'} +{'id': 83926, 'data_set_name': '可以使用:fnd3_qacctadj_inventoryincdec', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Inventory'} +{'id': 83927, 'data_set_name': '可以使用:fnd3_qacctadj_inventoryincdec_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Inventory'} +{'id': 83944, 'data_set_name': '可以使用:fnd3_qacctadj_payables', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Accounts Payable'} +{'id': 83945, 'data_set_name': '可以使用:fnd3_qacctadj_payables_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Accounts Payable'} +{'id': 83952, 'data_set_name': '可以使用:fnd3_qacctadj_receivables', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 83953, 'data_set_name': '可以使用:fnd3_qacctadj_receivables_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 84014, 'data_set_name': '可以使用:quarterly_accounts_receivable_total', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Accounts receivable'} +{'id': 84015, 'data_set_name': '可以使用:quarterly_accounts_receivable_total_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Accounts receivable'} +{'id': 84082, 'data_set_name': '可以使用:quarterly_inventory_change_amount', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Increase or Decrease in Inventory'} +{'id': 84083, 'data_set_name': '可以使用:quarterly_inventory_change_amount_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Increase or Decrease in Inventory'} +{'id': 84084, 'data_set_name': '可以使用:quarterly_inventory_total', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Inventory'} +{'id': 84085, 'data_set_name': '可以使用:quarterly_inventory_total_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Inventory'} +{'id': 84106, 'data_set_name': '可以使用:quarterly_payables_change_amount', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Increase or Decrease in Accounts Payable'} +{'id': 84107, 'data_set_name': '可以使用:quarterly_payables_change_amount_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Increase or Decrease in Accounts Payable'} +{'id': 84114, 'data_set_name': '可以使用:quarterly_receivables_change_amount', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 84115, 'data_set_name': '可以使用:quarterly_receivables_change_amount_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 85152, 'data_set_name': '可以使用:inventory', 'description': '不可使用,仅供参考:Inventories - Total'} +{'id': 85153, 'data_set_name': '可以使用:inventory_turnover', 'description': '不可使用,仅供参考:Inventory Turnover'} +{'id': 85162, 'data_set_name': '可以使用:receivable', 'description': '不可使用,仅供参考:Receivables - Total'} +{'id': 85524, 'data_set_name': '可以使用:fnd72_pit_or_bs_a_bs_acct_payable', 'description': '不可使用,仅供参考:Accounts Payable'} +{'id': 85587, 'data_set_name': '可以使用:fnd72_pit_or_bs_a_notes_receivable', 'description': "不可使用,仅供参考:Promissory notes written from a bank related to a company's ordinary business transaction"} +{'id': 85594, 'data_set_name': '可以使用:fnd72_pit_or_bs_q_bs_acct_payable', 'description': '不可使用,仅供参考:Accounts Payable'} +{'id': 85657, 'data_set_name': '可以使用:fnd72_pit_or_bs_q_notes_receivable', 'description': "不可使用,仅供参考:Promissory notes written from a bank related to a company's ordinary business transaction"} +{'id': 85750, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_accounts_payable_turnover', 'description': '不可使用,仅供参考:Company purchases over average accounts payable'} +{'id': 85751, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_accounts_payable_turnover_days', 'description': '不可使用,仅供参考:Number of days in the fiscal period as a multiple of Accounts Payable Turnover'} +{'id': 85752, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_accounts_receivable_growth', 'description': '不可使用,仅供参考:Percentage growth in inventory from last year to the current year'} +{'id': 85762, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_asset_turnover', 'description': '不可使用,仅供参考:Amount of sales or revenues generated per dollar of assets'} +{'id': 85847, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_inventory_growth', 'description': '不可使用,仅供参考:Percentage growth in inventory from last year to the current year'} +{'id': 85848, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_inventory_growth_to_sales_growth', 'description': '不可使用,仅供参考:Year-over-year growth in inventory as a multiple of year-over-year growth in sales'} +{'id': 85938, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_accounts_payable_turnover', 'description': '不可使用,仅供参考:Company purchases over average accounts payable'} +{'id': 85939, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_accounts_payable_turnover_days', 'description': '不可使用,仅供参考:Number of days in the fiscal period as a multiple of Accounts Payable Turnover'} +{'id': 85940, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_accounts_receivable_growth', 'description': '不可使用,仅供参考:Percentage growth in inventory from last year to the current year'} +{'id': 85950, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_asset_turnover', 'description': '不可使用,仅供参考:Amount of sales or revenues generated per dollar of assets'} +{'id': 86036, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_inventory_growth', 'description': '不可使用,仅供参考:Percentage growth in inventory from last year to the current year'} +{'id': 86037, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_inventory_growth_to_sales_growth', 'description': '不可使用,仅供参考:Year-over-year growth in inventory as a multiple of year-over-year growth in sales'} +{'id': 86481, 'data_set_name': '可以使用:fnd72_s_pit_or_bs_a_bs_acct_payable', 'description': '不可使用,仅供参考:Accounts Payable'} +{'id': 86517, 'data_set_name': '可以使用:fnd72_s_pit_or_bs_a_notes_receivable', 'description': "不可使用,仅供参考:Promissory notes written from a bank related to a company's ordinary business transaction"} +{'id': 86521, 'data_set_name': '可以使用:fnd72_s_pit_or_bs_q_1_bs_acct_payable', 'description': '不可使用,仅供参考:Accounts Payable'} +{'id': 86553, 'data_set_name': '可以使用:fnd72_s_pit_or_bs_q_1_notes_receivable', 'description': "不可使用,仅供参考:Promissory notes written from a bank related to a company's ordinary business transaction"} +{'id': 86597, 'data_set_name': '可以使用:fnd72_s_pit_or_bs_q_bs_acct_payable', 'description': '不可使用,仅供参考:Accounts Payable'} +{'id': 86660, 'data_set_name': '可以使用:fnd72_s_pit_or_bs_q_notes_receivable', 'description': "不可使用,仅供参考:Promissory notes written from a bank related to a company's ordinary business transaction"} +{'id': 86733, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_accounts_payable_turnover', 'description': '不可使用,仅供参考:Company purchases over average accounts payable'} +{'id': 86734, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_accounts_payable_turnover_days', 'description': '不可使用,仅供参考:Number of days in the fiscal period as a multiple of Accounts Payable Turnover'} +{'id': 86735, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_accounts_receivable_growth', 'description': '不可使用,仅供参考:Percentage growth in inventory from last year to the current year'} +{'id': 86745, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_asset_turnover', 'description': '不可使用,仅供参考:Amount of sales or revenues generated per dollar of assets'} +{'id': 86822, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_inventory_growth', 'description': '不可使用,仅供参考:Percentage growth in inventory from last year to the current year'} +{'id': 86823, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_inventory_growth_to_sales_growth', 'description': '不可使用,仅供参考:Year-over-year growth in inventory as a multiple of year-over-year growth in sales'} +{'id': 87492, 'data_set_name': '可以使用:fnd90_game_asset_turnover_chg', 'description': '不可使用,仅供参考:Change in Asset Turnover'} +{'id': 87512, 'data_set_name': '可以使用:fnd90_game_inventory_chg', 'description': '不可使用,仅供参考:Change in Inventory'} +{'id': 87513, 'data_set_name': '可以使用:fnd90_game_inventory_days', 'description': '不可使用,仅供参考:Inventory Days'} +{'id': 87530, 'data_set_name': '可以使用:fnd90_game_receivable_chg', 'description': '不可使用,仅供参考:Change in Receivables'} +{'id': 87531, 'data_set_name': '可以使用:fnd90_game_receivable_days', 'description': '不可使用,仅供参考:Receivable Days'} +{'id': 87557, 'data_set_name': '可以使用:fnd90_us_game_asset_turnover_chg', 'description': '不可使用,仅供参考:Change in Asset Turnover [ Ascending] - [Quality.Capital utilization]'} +{'id': 87577, 'data_set_name': '可以使用:fnd90_us_game_inventory_chg', 'description': '不可使用,仅供参考:Change in Inventory [ Descending] - [Quality.Working capital]'} +{'id': 87578, 'data_set_name': '可以使用:fnd90_us_game_inventory_days', 'description': '不可使用,仅供参考:Inventory Days [ Descending] - [Quality.Working capital]'} +{'id': 87595, 'data_set_name': '可以使用:fnd90_us_game_receivable_chg', 'description': '不可使用,仅供参考:Change in Receivables [ Descending] - [Quality.Working capital]'} +{'id': 87596, 'data_set_name': '可以使用:fnd90_us_game_receivable_days', 'description': '不可使用,仅供参考:Receivable Days [ Descending] - [Quality.Working capital]'} +{'id': 88049, 'data_set_name': '可以使用:oth401_game_asset_turnover_chg', 'description': '不可使用,仅供参考:Change in Asset Turnover'} +{'id': 88069, 'data_set_name': '可以使用:oth401_game_inventory_chg', 'description': '不可使用,仅供参考:Change in Inventory'} +{'id': 88070, 'data_set_name': '可以使用:oth401_game_inventory_days', 'description': '不可使用,仅供参考:Inventory Days'} +{'id': 88087, 'data_set_name': '可以使用:oth401_game_receivable_chg', 'description': '不可使用,仅供参考:Change in Receivables'} +{'id': 88088, 'data_set_name': '可以使用:oth401_game_receivable_days', 'description': '不可使用,仅供参考:Receivable Days'} +{'id': 316963, 'data_set_name': '可以使用:pv20_1_ard_accounts_payable_trade', 'description': '不可使用,仅供参考:ARD Accounts Payable - Trade'} +{'id': 316998, 'data_set_name': '可以使用:pv20_a2_ardr_inventory', 'description': '不可使用,仅供参考:ARD Ref Inventories'} +{'id': 317006, 'data_set_name': '可以使用:pv20_a_ard_accts_receivable_trade', 'description': '不可使用,仅供参考:ARD Accounts Receivable - Trade'} +{'id': 317038, 'data_set_name': '可以使用:pv20_ard_accounts_payable_trade', 'description': '不可使用,仅供参考:ARD Accounts Payable - Trade'} +{'id': 317043, 'data_set_name': '可以使用:pv20_ard_inventory', 'description': '不可使用,仅供参考:ARD Inventories'} +{'id': 317757, 'data_set_name': '可以使用:pv20_q_1_ard_accts_receivable_trade', 'description': '不可使用,仅供参考:ARD Accounts Receivable - Trade'} +{'id': 317762, 'data_set_name': '可以使用:pv20_q_1_ard_income_tax_accrued_payable', 'description': '不可使用,仅供参考:ARD Income Taxes Accrued/Payable'} +{'id': 317780, 'data_set_name': '可以使用:pv20_q_2_ardr_inventory', 'description': '不可使用,仅供参考:ARD Ref Inventories'} +{'id': 317795, 'data_set_name': '可以使用:pv20_q_ardr_inventory', 'description': '不可使用,仅供参考:ARD Ref Inventories'} +{'id': 319293, 'data_set_name': '可以使用:pv64_dif_fund_turnover', 'description': '不可使用,仅供参考:Fund turnover is the percentage of the portfolio that was changed or replaced over a 1-year time period. This 1 year is the fiscal year of the fund. Fund turnover is updated from annual reports.'} +{'id': 319331, 'data_set_name': '可以使用:pv64_dif_stal_fund_turnover', 'description': '不可使用,仅供参考:Fund turnover is the percentage of the portfolio that was changed or replaced over a 1-year time period. This 1 year is the fiscal year of the fund. Fund turnover is updated from annual reports.'} +{'id': 319409, 'data_set_name': '可以使用:pv64_out_stal_fund_turnover', 'description': '不可使用,仅供参考:Fund turnover is the percentage of the portfolio that was changed or replaced over a 1-year time period. This 1 year is the fiscal year of the fund. Fund turnover is updated from annual reports.'} +{'id': 323927, 'data_set_name': '可以使用:pv87_payable_to_mean', 'description': '不可使用,仅供参考:Accounts payable turnover'} +========================= 数据字段结束 ======================================= + +以上数据字段和操作符, 按照Description说明组合, 但是每一个 alpha 组合的使用的数据字段和操作符不要过于集中, 在符合语法的情况下, 多尝试不同的组合 + +你再检查一下, 如果你使用了 +Operator abs does not support event inputs +Operator ts_mean does not support event inputs +Operator ts_scale does not support event inputs +Operator add does not support event inputs +Operator sign does not support event inputs +Operator greater does not support event inputs +Operator ts_av_diff does not support event inputs +Operator ts_quantile does not support event inputs +Operator ts_arg_min does not support event inputs +Operator divide does not support event inputs +Operator ts_corr does not support event inputs +Operator ts_decay_linear does not support event inputs +Operator ts_sum does not support event inputs +Operator ts_delay does not support event inputs +Operator ts_arg_max does not support event inputs +Operator ts_std_dev does not support event inputs +Operator ts_regression does not support event inputs +Operator ts_backfill does not support event inputs +Operator signed_power does not support event inputs +Operator ts_product does not support event inputs +Operator ts_zscore does not support event inputs +Operator group_rank does not support event inputs +Operator subtract does not support event inputs +Operator ts_delta does not support event inputs +Operator ts_rank does not support event inputs +Operator ts_count_nans does not support event inputs +Operator ts_covariance does not support event inputs +Operator multiply does not support event inputs +Operator if_else does not support event inputs +Operator group_neutralize does not support event inputs +Operator group_zscore does not support event inputs +Operator winsorize does not support event inputs +注意, 以上操作符不能使用事件类型的数据集, 以上操作符禁止使用事件类型的数据集!! \ No newline at end of file diff --git a/manual_prompt/2026/01/22/manual_prompt_20260122150453.txt b/manual_prompt/2026/01/22/manual_prompt_20260122150453.txt new file mode 100644 index 0000000..6a7f152 --- /dev/null +++ b/manual_prompt/2026/01/22/manual_prompt_20260122150453.txt @@ -0,0 +1,811 @@ +客户集中度与盈利质量错配因子 +企业若高度依赖少数大客户，其收入稳定性脆弱，但市场常因短期高营收而给予过高估值，忽视潜在的议价劣势和收入波动风险。多空逻辑：做空客户集中度高且盈利质量（如经营现金流/净利润）低的企业，做多客户分散且盈利质量高的企业。 +核心指标为前五大客户销售收入占比，结合经营性现金流与净利润比值衡量盈利质量；需进行行业中性化，并对集中度指标取对数压缩尾部；缺失值采用过去12个月滚动填充；辅助变量包括销售费用率和应收账款天数。 +*=========================================================================================* +输出格式： +输出必须是且仅是纯文本。 +每一行是一个完整、独立、语法正确的WebSim表达式。 +严禁任何形式的解释、编号、标点包裹（如引号）、Markdown格式或额外文本。 +===================== !!! 重点(输出方式) !!! ===================== +现在，请严格遵守以上所有规则，开始生成可立即在WebSim中运行的复合因子表达式。 +不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 +**输出格式**(一行一个表达式, 每个表达式中间需要添加一个空行, 只要表达式本身, 不需要赋值, 不要解释, 不需要序号, 也不要输出多余的东西)： +表达式 +表达式 +表达式 +... +表达式 +================================================================= +重申：请确保所有表达式都使用WorldQuant WebSim平台函数，不要使用pandas、numpy或其他Python库函数。输出必须是一行有效的WQ表达式。 +以下是我的账号有权限使用的操作符, 请严格按照操作符, 以及我提供的数据集, 进行生成,组合 50 个 alpha： +不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 +================================================================= +**操作符汇总 +**算术运算符 (Arithmetic): +abs(x) - 绝对值 +add(x, y, filter=false) - 加法 (x + y) +densify(x) - 分组字段稠密化 +divide(x, y) - 除法 (x / y) +inverse(x) - 倒数 (1/x) +log(x) - 自然对数 +max(x, y, ..) - 最大值 +min(x, y, ..) - 最小值 +multiply(x, y, filter=false) - 乘法 (x * y) +power(x, y) - 幂运算 (x^y) +reverse(x) - 取反 (-x) +sign(x) - 符号函数 +signed_power(x, y) - 保留符号的幂运算 +sqrt(x) - 平方根 +subtract(x, y, filter=false) - 减法 (x - y) +to_nan(x, value=0, reverse=false) - 值与NaN转换 +**逻辑运算符 (Logical): +and(input1, input2) - 逻辑与 +if_else(input1, input2, input3) - 条件判断 +input1 < input2 - 小于比较 +input1 <= input2 - 小于等于 +input1 == input2 - 等于比较 +input1 > input2 - 大于比较 +input1 >= input2 - 大于等于 +input1 != input2 - 不等于 +is_nan(input) - 是否为NaN +not(x) - 逻辑非 +or(input1, input2) - 逻辑或 +**时间序列运算符 (Time Series): +days_from_last_change(x) - 上次变化天数 +hump(x, hump=0.01) - 限制变化幅度 +jump_decay(x, d, sensitivity=0.5, force=0.1) - 跳跃衰减 +kth_element(x, d, k) - 第K个值 +last_diff_value(x, d) - 最后一个不同值 +ts_arg_max(x, d) - 最大值相对索引 +ts_arg_min(x, d) - 最小值相对索引 +ts_av_diff(x, d) - 与均值的差 +ts_backfill(x, lookback=d, k=1, ignore="NAN") - 回填 +ts_corr(x, y, d) - 时间序列相关性 +ts_count_nans(x, d) - NaN计数 +ts_covariance(y, x, d) - 协方差 +ts_decay_linear(x, d, dense=false) - 线性衰减 +ts_delay(x, d) - 延迟值 +ts_delta(x, d) - 差值 (x - 延迟值) +ts_max(x, d) - 时间序列最大值 +ts_mean(x, d) - 时间序列均值 +ts_min(x, d) - 时间序列最小值 +ts_product(x, d) - 时间序列乘积 +ts_quantile(x, d, driver="gaussian") - 分位数 +ts_rank(x, d, constant=0) - 时间序列排名 +ts_regression(y, x, d, lag=0, rettype=0) - 回归分析 +ts_scale(x, d, constant=0) - 时间序列缩放 +ts_std_dev(x, d) - 时间序列标准差 +ts_step(1) - 天数计数器 +ts_sum(x, d) - 时间序列求和 +ts_target_tvr_decay(x, lambda_min=0, lambda_max=1, target_tvr=0.1) - 目标换手率衰减 +ts_target_tvr_delta_limit(x, y, lambda_min=0, lambda_max=1, target_tvr=0.1) - 目标换手率差值限制 +ts_zscore(x, d) - 时间序列Z分数 +**横截面运算符 (Cross Sectional): +normalize(x, useStd=false, limit=0.0) - 标准化 +quantile(x, driver=gaussian, sigma=1.0) - 分位数转换 +rank(x, rate=2) - 排名 +scale(x, scale=1, longscale=1, shortscale=1) - 缩放 +scale_down(x, constant=0) - 按比例缩放 +vector_neut(x, y) - 向量中性化 +winsorize(x, std=4) - 缩尾处理 +zscore(x) - Z分数 +**向量运算符 (Vector): +vec_avg(x) - 向量均值 +vec_max(x) - 向量最大值 +vec_min(x) - 向量最小值 +vec_sum(x) - 向量求和 +**变换运算符 (Transformational): +bucket(rank(x), range="0,1,0.1" or buckets="2,5,6,7,10") - 分桶 +generate_stats(alpha) - 生成统计量 +trade_when(x, y, z) - 条件交易 +**分组运算符 (Group): +combo_a(alpha, nlength=250, mode='algo1') - 组合Alpha +group_backfill(x, group, d, std=4.0) - 分组回填 +group_cartesian_product(g1, g2) - 笛卡尔积分组 +group_max(x, group) - 分组最大值 +group_mean(x, weight, group) - 分组均值 +group_min(x, group) - 分组最小值 +group_neutralize(x, group) - 分组中性化 +group_rank(x, group) - 分组排名 +group_scale(x, group) - 分组缩放 +group_zscore(x, group) - 分组Z分数 +**特殊运算符 (Special): +in - 包含判断 +self_corr(input) - 自相关性 +universe_size - 宇宙大小 +**归约运算符 (Reduce): +reduce_avg(input, threshold=0) - 平均值归约 +reduce_choose(input, nth, ignoreNan=true) - 选择归约 +reduce_count(input, threshold) - 计数归约 +reduce_ir(input) - IR归约 +reduce_kurtosis(input) - 峰度归约 +reduce_max(input) - 最大值归约 +reduce_min(input) - 最小值归约 +reduce_norm(input) - 范数归约 +reduce_percentage(input, percentage=0.5) - 百分比归约 +reduce_powersum(input, constant=2, precise=false) - 幂和归约 +reduce_range(input) - 范围归约 +reduce_skewness(input) - 偏度归约 +reduce_stddev(input, threshold=0) - 标准差归约 +reduce_sum(input) - 求和归约 + +以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子 + +========================= 操作符开始 ======================================= +注意: Operator: 后面的是操作符(是可以使用的), +Description: 此字段后面的是操作符对应的描述或使用说明(禁止使用, 仅供参考), Description字段后面的内容是使用说明, 不是操作符 +特别注意!!!! 必须按照操作符字段Operator的使用说明生成 alphaOperator: abs(x) +Description: Absolute value of x +Operator: add(x, y, filter = false) +Description: Add all inputs (at least 2 inputs required). If filter = true, filter all input NaN to 0 before adding +Operator: densify(x) +Description: Converts a grouping field of many buckets into lesser number of only available buckets so as to make working with grouping fields computationally efficient +Operator: divide(x, y) +Description: x / y +Operator: inverse(x) +Description: 1 / x +Operator: log(x) +Description: Natural logarithm. For example: Log(high/low) uses natural logarithm of high/low ratio as stock weights. +Operator: max(x, y, ..) +Description: Maximum value of all inputs. At least 2 inputs are required +Operator: min(x, y ..) +Description: Minimum value of all inputs. At least 2 inputs are required +Operator: multiply(x ,y, ... , filter=false) +Description: Multiply all inputs. At least 2 inputs are required. Filter sets the NaN values to 1 +Operator: power(x, y) +Description: x ^ y +Operator: reverse(x) +Description: - x +Operator: sign(x) +Description: if input > 0, return 1; if input < 0, return -1; if input = 0, return 0; if input = NaN, return NaN; +Operator: signed_power(x, y) +Description: x raised to the power of y such that final result preserves sign of x +Operator: sqrt(x) +Description: Square root of x +Operator: subtract(x, y, filter=false) +Description: x-y. If filter = true, filter all input NaN to 0 before subtracting +Operator: and(input1, input2) +Description: Logical AND operator, returns true if both operands are true and returns false otherwise +Operator: if_else(input1, input2, input 3) +Description: If input1 is true then return input2 else return input3. +Operator: input1 < input2 +Description: If input1 < input2 return true, else return false +Operator: input1 <= input2 +Description: Returns true if input1 <= input2, return false otherwise +Operator: input1 == input2 +Description: Returns true if both inputs are same and returns false otherwise +Operator: input1 > input2 +Description: Logic comparison operators to compares two inputs +Operator: input1 >= input2 +Description: Returns true if input1 >= input2, return false otherwise +Operator: input1!= input2 +Description: Returns true if both inputs are NOT the same and returns false otherwise +Operator: is_nan(input) +Description: If (input == NaN) return 1 else return 0 +Operator: not(x) +Description: Returns the logical negation of x. If x is true (1), it returns false (0), and if input is false (0), it returns true (1). +Operator: or(input1, input2) +Description: Logical OR operator returns true if either or both inputs are true and returns false otherwise +Operator: days_from_last_change(x) +Description: Amount of days since last change of x +Operator: hump(x, hump = 0.01) +Description: Limits amount and magnitude of changes in input (thus reducing turnover) +Operator: kth_element(x, d, k) +Description: Returns K-th value of input by looking through lookback days. This operator can be used to backfill missing data if k=1 +Operator: last_diff_value(x, d) +Description: Returns last x value not equal to current x value from last d days +Operator: ts_arg_max(x, d) +Description: Returns the relative index of the max value in the time series for the past d days. If the current day has the max value for the past d days, it returns 0. If previous day has the max value for the past d days, it returns 1 +Operator: ts_arg_min(x, d) +Description: Returns the relative index of the min value in the time series for the past d days; If the current day has the min value for the past d days, it returns 0; If previous day has the min value for the past d days, it returns 1. +Operator: ts_av_diff(x, d) +Description: Returns x - tsmean(x, d), but deals with NaNs carefully. That is NaNs are ignored during mean computation +Operator: ts_backfill(x,lookback = d, k=1, ignore="NAN") +Description: Backfill is the process of replacing the NAN or 0 values by a meaningful value (i.e., a first non-NaN value) +Operator: ts_corr(x, y, d) +Description: Returns correlation of x and y for the past d days +Operator: ts_count_nans(x ,d) +Description: Returns the number of NaN values in x for the past d days +Operator: ts_covariance(y, x, d) +Description: Returns covariance of y and x for the past d days +Operator: ts_decay_linear(x, d, dense = false) +Description: Returns the linear decay on x for the past d days. Dense parameter=false means operator works in sparse mode and we treat NaN as 0. In dense mode we do not. +Operator: ts_delay(x, d) +Description: Returns x value d days ago +Operator: ts_delta(x, d) +Description: Returns x - ts_delay(x, d) +Operator: ts_mean(x, d) +Description: Returns average value of x for the past d days. +Operator: ts_product(x, d) +Description: Returns product of x for the past d days +Operator: ts_quantile(x,d, driver="gaussian" ) +Description: It calculates ts_rank and apply to its value an inverse cumulative density function from driver distribution. Possible values of driver (optional ) are "gaussian", "uniform", "cauchy" distribution where "gaussian" is the default. +Operator: ts_rank(x, d, constant = 0) +Description: Rank the values of x for each instrument over the past d days, then return the rank of the current value + constant. If not specified, by default, constant = 0. +Operator: ts_regression(y, x, d, lag = 0, rettype = 0) +Description: Returns various parameters related to regression function +Operator: ts_scale(x, d, constant = 0) +Description: Returns (x - ts_min(x, d)) / (ts_max(x, d) - ts_min(x, d)) + constant. This operator is similar to scale down operator but acts in time series space +Operator: ts_std_dev(x, d) +Description: Returns standard deviation of x for the past d days +Operator: ts_step(1) +Description: Returns days' counter +Operator: ts_sum(x, d) +Description: Sum values of x for the past d days. +Operator: ts_zscore(x, d) +Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean: (x - tsmean(x,d)) / tsstddev(x,d). This operator may help reduce outliers and drawdown. +Operator: normalize(x, useStd = false, limit = 0.0) +Description: Calculates the mean value of all valid alpha values for a certain date, then subtracts that mean from each element +Operator: quantile(x, driver = gaussian, sigma = 1.0) +Description: Rank the raw vector, shift the ranked Alpha vector, apply distribution (gaussian, cauchy, uniform). If driver is uniform, it simply subtract each Alpha value with the mean of all Alpha values in the Alpha vector +Operator: rank(x, rate=2) +Description: Ranks the input among all the instruments and returns an equally distributed number between 0.0 and 1.0. For precise sort, use the rate as 0 +Operator: scale(x, scale=1, longscale=1, shortscale=1) +Description: Scales input to booksize. We can also scale the long positions and short positions to separate scales by mentioning additional parameters to the operator +Operator: winsorize(x, std=4) +Description: Winsorizes x to make sure that all values in x are between the lower and upper limits, which are specified as multiple of std. +Operator: zscore(x) +Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean +Operator: vec_avg(x) +Description: Taking mean of the vector field x +Operator: vec_sum(x) +Description: Sum of vector field x +Operator: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10") +Description: Convert float values into indexes for user-specified buckets. Bucket is useful for creating group values, which can be passed to GROUP as input +Operator: trade_when(x, y, z) +Description: Used in order to change Alpha values only under a specified condition and to hold Alpha values in other cases. It also allows to close Alpha positions (assign NaN values) under a specified condition +Operator: group_backfill(x, group, d, std = 4.0) +Description: If a certain value for a certain date and instrument is NaN, from the set of same group instruments, calculate winsorized mean of all non-NaN values over last d days +Operator: group_mean(x, weight, group) +Description: All elements in group equals to the mean +Operator: group_neutralize(x, group) +Description: Neutralizes Alpha against groups. These groups can be subindustry, industry, sector, country or a constant +Operator: group_rank(x, group) +Description: Each elements in a group is assigned the corresponding rank in this group +Operator: group_scale(x, group) +Description: Normalizes the values in a group to be between 0 and 1. (x - groupmin) / (groupmax - groupmin) +Operator: group_zscore(x, group) +Description: Calculates group Z-score - numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. zscore = (data - mean) / stddev of x for each instrument within its group. +========================= 操作符结束 ======================================= + +========================= 数据字段开始 ======================================= +注意: data_set_name: 后面的是数据字段(可以使用), description: 此字段后面的是数据字段对应的描述或使用说明(不能使用) + +{'id': 10303, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on value of Q sales'} +{'id': 10190, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on value of Q operating profit'} +{'id': 10271, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on delta of annual pre-tax profit'} +{'id': 9316, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on value of Q operating profit'} +{'id': 9268, 'data_set_name': '可以使用:anl82_nety_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on delta of annual net income'} +{'id': 6767, 'data_set_name': '可以使用:anl49_backfill_1stfiscalquartersalesorrevenuesindicator', 'description': '不可使用,仅供参考:First fiscal quarter sales or revenues indicator'} +{'id': 85756, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_actual_sales_per_empl', 'description': '不可使用,仅供参考:Measure to indicate how much revenue allocates to an employee for the period'} +{'id': 5529, 'data_set_name': '可以使用:est_rd_expense', 'description': '不可使用,仅供参考:Research and Development Expense - mean of estimations'} +{'id': 5510, 'data_set_name': '可以使用:est_cashflow_fin', 'description': '不可使用,仅供参考:Cash Flow From Financing - mean of estimations'} +{'id': 9166, 'data_set_name': '可以使用:anl82_ebty_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on delta of annual EBITDA'} +{'id': 80728, 'data_set_name': '可以使用:selling_general_admin_expense_2', 'description': '不可使用,仅供参考:Total selling, general, and administrative expenses.'} +{'id': 320745, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_b_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Sales'} +{'id': 9370, 'data_set_name': '可以使用:anl82_preq_profitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on value of Q pre-tax profit'} +{'id': 83676, 'data_set_name': '可以使用:fnd3_aacctadj_opeexpenses', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Total Operating Expenses'} +{'id': 9467, 'data_set_name': '可以使用:anl82_saly_profitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on value of annual sales'} +{'id': 9228, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on delta of Q net income'} +{'id': 9238, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on delta of Q net income'} +{'id': 6488, 'data_set_name': '可以使用:forecast_currency_sales_orig', 'description': '不可使用,仅供参考:Currency in which the sales forecast is denominated in the original version module.'} +{'id': 9429, 'data_set_name': '可以使用:anl82_salq_profitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on value of Q sales'} +{'id': 5694, 'data_set_name': '可以使用:sales_estimate_standard_deviation', 'description': '不可使用,仅供参考:Sales - standard deviation of estimations'} +{'id': 10182, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on value of Q operating profit'} +{'id': 78997, 'data_set_name': '可以使用:fn_def_income_tax_expense_a', 'description': '不可使用,仅供参考:Income Tax Expense, Deferred'} +{'id': 9178, 'data_set_name': '可以使用:anl82_ebty_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of annual EBITDA'} +{'id': 84101, 'data_set_name': '可以使用:quarterly_operating_cashflow_amount_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Operating Cash Flow'} +{'id': 6873, 'data_set_name': '可以使用:anl49_backfill_salesorrevenuespershareindicator', 'description': '不可使用,仅供参考:Sales or revenues per share indicator'} +{'id': 320721, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Sales'} +{'id': 9426, 'data_set_name': '可以使用:anl82_salq_profitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on value of Q sales'} +{'id': 9425, 'data_set_name': '可以使用:anl82_salq_profitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on value of Q sales'} +{'id': 5658, 'data_set_name': '可以使用:operating_cashflow_reported_value', 'description': '不可使用,仅供参考:Cash Flow from Operations - Value'} +{'id': 9346, 'data_set_name': '可以使用:anl82_opry_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of annual operating profit'} +{'id': 317756, 'data_set_name': '可以使用:pv20_q_1_ard_accrued_expenses', 'description': '不可使用,仅供参考:ARD Accrued Expenses'} +{'id': 9413, 'data_set_name': '可以使用:anl82_salq_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on delta of Q sales'} +{'id': 324465, 'data_set_name': '可以使用:pv87_qtr_matrix_interest_expense_estimate_number', 'description': '不可使用,仅供参考:Number of analysts of Interest Expense Estimate'} +{'id': 83455, 'data_set_name': '可以使用:fnd3_a_accreceivable_fast_d1', 'description': '不可使用,仅供参考:Annual Accounts receivable'} +{'id': 10288, 'data_set_name': '可以使用:mdl211_salq_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on delta of Q sales'} +{'id': 83130, 'data_set_name': '可以使用:annual_equity_compensation_expense_fast_d1', 'description': '不可使用,仅供参考:Expense from share-based compensation for the year.'} +{'id': 84293, 'data_set_name': '可以使用:cashflow_dividends', 'description': '不可使用,仅供参考:Cash Dividends (Cash Flow)'} +{'id': 6748, 'data_set_name': '可以使用:anl49_4thfiscalquartersalesorrevenuesindicator', 'description': '不可使用,仅供参考:Fourth fiscal quarter sales or revenues indicator'} +{'id': 9284, 'data_set_name': '可以使用:anl82_nety_profitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on value of annual net income'} +{'id': 10154, 'data_set_name': '可以使用:mdl211_nety_profitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on value of annual net income'} +{'id': 85752, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_accounts_receivable_growth', 'description': '不可使用,仅供参考:Percentage growth in inventory from last year to the current year'} +{'id': 7204, 'data_set_name': '可以使用:anl69_best_ni_adj_to_sales', 'description': '不可使用,仅供参考:Profit Margin'} +{'id': 10292, 'data_set_name': '可以使用:mdl211_salq_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on delta of Q sales'} +{'id': 84115, 'data_set_name': '可以使用:quarterly_receivables_change_amount_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 9165, 'data_set_name': '可以使用:anl82_ebty_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:Profitability Measure Type 3 Based on Delta of Annual EBITDA'} +{'id': 9466, 'data_set_name': '可以使用:anl82_saly_profitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on value of annual sales'} +{'id': 84137, 'data_set_name': '可以使用:r_and_d_expense_total_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Research & Development Expense'} +{'id': 5693, 'data_set_name': '可以使用:sales_estimate_minimum_quarterly', 'description': '不可使用,仅供参考:Sales - The lowest estimation'} +{'id': 10185, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on value of Q operating profit'} +{'id': 87605, 'data_set_name': '可以使用:fnd90_us_qes_gamef_cashflow_var', 'description': '不可使用,仅供参考:Cash Flow Variability'} +{'id': 10330, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of annual sales'} +{'id': 83727, 'data_set_name': '可以使用:fnd3_q_accreceivable_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accounts receivable'} +{'id': 86243, 'data_set_name': '可以使用:fnd72_pit_or_is_q_is_pension_expense_income', 'description': '不可使用,仅供参考:The net amount of pension cost that is recognized in the income statement'} +{'id': 79330, 'data_set_name': '可以使用:current_tax_expense', 'description': '不可使用,仅供参考:[Quarterly] Current Tax - Foreign'} +{'id': 320691, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 80734, 'data_set_name': '可以使用:share_capital_expense', 'description': '不可使用,仅供参考:Expenses related to share capital issuance or management.'} +{'id': 321161, 'data_set_name': '可以使用:pv87_customerprivacyindustrypercentile_momentum_mean', 'description': '不可使用,仅供参考:Trailing 12m score of Customer Privacy topic'} +{'id': 6858, 'data_set_name': '可以使用:anl49_backfill_operatingexpenseratioindicator', 'description': '不可使用,仅供参考:Operating expense ratio indicator'} +{'id': 85812, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_ev_to_t12m_sales', 'description': '不可使用,仅供参考:Periodic enterprise value as a multiple of sales'} +{'id': 10142, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on delta of annual net income'} +{'id': 10240, 'data_set_name': '可以使用:mdl211_preq_profitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on value of Q pre-tax profit'} +{'id': 6351, 'data_set_name': '可以使用:anl44_sales_best_cur_fiscal_year_period', 'description': '不可使用,仅供参考:sales best cur fiscal year period'} +{'id': 80720, 'data_set_name': '可以使用:sales_income_net', 'description': '不可使用,仅供参考:Net sales or revenue recognized during the period.'} +{'id': 80861, 'data_set_name': '可以使用:unrealized_investment_expense', 'description': '不可使用,仅供参考:Unrealized expense related to investments.'} +{'id': 9369, 'data_set_name': '可以使用:anl82_preq_profitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on value of Q pre-tax profit'} +{'id': 86276, 'data_set_name': '可以使用:fnd72_q1_cap_expend_to_sales', 'description': '不可使用,仅供参考:Measures the percentage of capital expenditures to sales'} +{'id': 10116, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on value of Q net income'} +{'id': 6447, 'data_set_name': '可以使用:anl44_second_en_sales_value', 'description': '不可使用,仅供参考:sales value'} +{'id': 6510, 'data_set_name': '可以使用:latest_annual_period_end_update_sales_2', 'description': '不可使用,仅供参考:Date or timestamp when the annual period end for sales was last updated.'} +{'id': 10175, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on delta of Q operating profit'} +{'id': 6355, 'data_set_name': '可以使用:anl44_sales_best_fperiod_override', 'description': '不可使用,仅供参考:sales best fperiod override'} +{'id': 9470, 'data_set_name': '可以使用:anl82_saly_profitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on value of annual sales'} +{'id': 83366, 'data_set_name': '可以使用:fnd3_Q_sgaexpense', 'description': '不可使用,仅供参考:Quarterly Selling, General & Administrative Expense'} +{'id': 10187, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on value of Q operating profit'} +{'id': 78998, 'data_set_name': '可以使用:fn_def_income_tax_expense_q', 'description': '不可使用,仅供参考:Income Tax Expense, Deferred'} +{'id': 83259, 'data_set_name': '可以使用:fnd3_Aacctadj_capitalassetsales', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Proceeds from Sale of Productive Assets'} +{'id': 9405, 'data_set_name': '可以使用:anl82_prey_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on delta of annual pre-tax profit'} +{'id': 10213, 'data_set_name': '可以使用:mdl211_opry_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of annual operating profit'} +{'id': 10009, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on value of Q ebitda'} +{'id': 10108, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of Q net income'} +{'id': 6284, 'data_set_name': '可以使用:anl44_orig_en_sales_value', 'description': '不可使用,仅供参考:orig en sales v1 0 0 value'} +{'id': 9300, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on delta of Q operating profit'} +{'id': 5582, 'data_set_name': '可以使用:max_operating_cashflow_guidance', 'description': '不可使用,仅供参考:The maximum guidance value for Cash Flow from Operations.'} +{'id': 80782, 'data_set_name': '可以使用:short_term_investment_cashflow', 'description': '不可使用,仅供参考:Cash flow from short-term investment activities.'} +{'id': 10122, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on value of Q net income'} +{'id': 320713, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_b_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Sales'} +{'id': 9992, 'data_set_name': '可以使用:mdl211_ebtq_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of Q ebitda'} +{'id': 79261, 'data_set_name': '可以使用:accounts_receivable_gross', 'description': '不可使用,仅供参考:Gross amount of accounts receivable outstanding.'} +{'id': 320723, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Sales'} +{'id': 83615, 'data_set_name': '可以使用:fnd3_aacctadj_capitalassetsales_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Proceeds from Sale of Productive Assets'} +{'id': 83596, 'data_set_name': '可以使用:fnd3_aacctadj_accreceivable', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Accounts receivable'} +{'id': 83695, 'data_set_name': '可以使用:fnd3_aacctadj_sgaexpense_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Selling, General & Administrative Expense'} +{'id': 9133, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability10', 'description': '不可使用,仅供参考:Profitability measure type 10 based on value of Q EBITDA'} +{'id': 10104, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on delta of Q net income'} +{'id': 84041, 'data_set_name': '可以使用:quarterly_cost_of_sales_total_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Cost of Revenue'} +{'id': 5704, 'data_set_name': '可以使用:selling_general_admin_expense', 'description': '不可使用,仅供参考:Selling, General & Administrative Expense Value'} +{'id': 79347, 'data_set_name': '可以使用:depreciation_expense', 'description': '不可使用,仅供参考:Expense recognized for the allocation of tangible asset costs over their useful lives.'} +{'id': 5069, 'data_set_name': '可以使用:actual_cashflow_per_share_value_quarterly', 'description': '不可使用,仅供参考:Cash Flow Per Share - actual value for the quarter'} +{'id': 85843, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_invent_to_sales', 'description': '不可使用,仅供参考:Ratio of inventory to sales, a way to estimate the number of times the company can turn over its inventory in 1 year'} +{'id': 321572, 'data_set_name': '可以使用:pv87_datasecurityandcustomerprivacy_insight_mean', 'description': '不可使用,仅供参考:Long-term score of Data Security And Customer Privacy topic'} +{'id': 6494, 'data_set_name': '可以使用:forecasted_value_sales_orig', 'description': '不可使用,仅供参考:Forecasted value for sales for the specified period in the original version module.'} +{'id': 6725, 'data_set_name': '可以使用:anl49_1stfiscalquartersalesorrevenuesindicator', 'description': '不可使用,仅供参考:First fiscal quarter sales or revenues indicator'} +{'id': 5583, 'data_set_name': '可以使用:max_operating_cashflow_guidance_2', 'description': '不可使用,仅供参考:The maximum guidance value for Cash Flow from Operations on an annual basis.'} +{'id': 6944, 'data_set_name': '可以使用:anl49_operatingexpenseratioindicator', 'description': '不可使用,仅供参考:Operating expense ratio indicator'} +{'id': 86918, 'data_set_name': '可以使用:fnd72_s_pit_or_is_a2_is_expense_stock_based_comp', 'description': '不可使用,仅供参考:The expense for stock-based compensation'} +{'id': 9233, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on delta of Q net income'} +{'id': 85446, 'data_set_name': '可以使用:fnd72_a2_sales_to_accum_depr', 'description': '不可使用,仅供参考:Accumulated depreciation turnover ratio represents the amount of sales or revenue generated per dollar of Accumulated Depreciation, in actual'} +{'id': 83675, 'data_set_name': '可以使用:fnd3_aacctadj_opeexpenseexitems_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Operating Expense Extraordinary Items'} +{'id': 320756, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 85452, 'data_set_name': '可以使用:fnd72_a2_sales_to_other_asset', 'description': "不可使用,仅供参考:Other assets turnover ratio measures the efficiency of a company's use of its other assets in generating revenue or income to the company, in actual"} +{'id': 88086, 'data_set_name': '可以使用:oth401_game_prepaid_expense', 'description': '不可使用,仅供参考:Prepaid Expense to Sales'} +{'id': 10102, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on delta of Q net income'} +{'id': 83454, 'data_set_name': '可以使用:fnd3_a_accreceivable', 'description': '不可使用,仅供参考:Annual Accounts receivable'} +{'id': 9229, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:Profitability measure type 10 based on delta of Q net income'} +{'id': 80850, 'data_set_name': '可以使用:total_rental_expense', 'description': '不可使用,仅供参考:Total rental expenses incurred during the period.'} +{'id': 84030, 'data_set_name': '可以使用:quarterly_capital_asset_sales_total', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Proceeds from Sale of Productive Assets'} +{'id': 5686, 'data_set_name': '可以使用:sales_estimate_count_quarterly', 'description': '不可使用,仅供参考:Sales - number of estimations'} +{'id': 5634, 'data_set_name': '可以使用:min_research_development_expense_guidance_2', 'description': '不可使用,仅供参考:Minimum guidance value for Research & Development Expense on an annual basis'} +{'id': 86177, 'data_set_name': '可以使用:fnd72_pit_or_is_a_is_pension_expense_income', 'description': '不可使用,仅供参考:The net amount of pension cost that is recognized in the income statement'} +{'id': 87596, 'data_set_name': '可以使用:fnd90_us_game_receivable_days', 'description': '不可使用,仅供参考:Receivable Days [ Descending] - [Quality.Working capital]'} +{'id': 6008, 'data_set_name': '可以使用:anl44_best_sales_stddev', 'description': '不可使用,仅供参考:best sales stddev'} +{'id': 10101, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on delta of Q net income'} +{'id': 87529, 'data_set_name': '可以使用:fnd90_game_prepaid_expense', 'description': '不可使用,仅供参考:Prepaid Expense to Sales'} +{'id': 83129, 'data_set_name': '可以使用:annual_equity_compensation_expense', 'description': '不可使用,仅供参考:Expense from share-based compensation for the year.'} +{'id': 86285, 'data_set_name': '可以使用:fnd72_q1_cogs_to_net_sales', 'description': '不可使用,仅供参考:Percentage of revenue used to pay costs of goods sold'} +{'id': 86735, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_accounts_receivable_growth', 'description': '不可使用,仅供参考:Percentage growth in inventory from last year to the current year'} +{'id': 10033, 'data_set_name': '可以使用:mdl211_ebty_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on delta of annual ebitda'} +{'id': 6773, 'data_set_name': '可以使用:anl49_backfill_35estd35yrgrowthratecashflowpershare', 'description': '不可使用,仅供参考:The annual compounded growth rate using the average of the three latest base years to the projected 3-5-year Book Value per Share.'} +{'id': 85167, 'data_set_name': '可以使用:sales', 'description': '不可使用,仅供参考:Sales/Turnover (Net)'} +{'id': 83813, 'data_set_name': '可以使用:fnd3_q_opeexpenses_fast_d1', 'description': '不可使用,仅供参考:Quarterly Total Operating Expenses'} +{'id': 84100, 'data_set_name': '可以使用:quarterly_operating_cashflow_amount', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Operating Cash Flow'} +{'id': 10265, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on delta of annual pre-tax profit'} +{'id': 9135, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on value of Q EBITDA'} +{'id': 86391, 'data_set_name': '可以使用:fnd72_q2_sales_per_empl', 'description': '不可使用,仅供参考:Measure of net sales per 1,000 employees'} +{'id': 10335, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of annual sales'} +{'id': 10186, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on value of Q operating profit'} +{'id': 5555, 'data_set_name': '可以使用:investing_cashflow_reported_value', 'description': '不可使用,仅供参考:Cash Flow from Investing - Value'} +{'id': 9458, 'data_set_name': '可以使用:anl82_saly_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on delta of annual sales'} +{'id': 86410, 'data_set_name': '可以使用:fnd72_q2_tot_cash_pfd_dvd_to_net_sales', 'description': '不可使用,仅供参考:Total cash preferred dividends as a percentage of net sales'} +{'id': 83429, 'data_set_name': '可以使用:fnd3_Qacctadj_receivables', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 9336, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on delta of annual operating profit'} +{'id': 86169, 'data_set_name': '可以使用:fnd72_pit_or_is_a_is_net_interest_expense', 'description': '不可使用,仅供参考:Interest expense minus interest income'} +{'id': 5703, 'data_set_name': '可以使用:sales_previous_estimate_value', 'description': '不可使用,仅供参考:The previous estimation of Sales'} +{'id': 9245, 'data_set_name': '可以使用:anl82_netq_profitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on value of Q net income'} +{'id': 10178, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on delta of Q operating profit'} +{'id': 5620, 'data_set_name': '可以使用:min_free_cashflow_per_share_guidance', 'description': '不可使用,仅供参考:Free cash flow per share - minimum guidance value'} +{'id': 83689, 'data_set_name': '可以使用:fnd3_aacctadj_receivables_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 84136, 'data_set_name': '可以使用:r_and_d_expense_total', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Research & Development Expense'} +{'id': 10323, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on delta of annual sales'} +{'id': 9169, 'data_set_name': '可以使用:anl82_ebty_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on delta of annual EBITDA'} +{'id': 9419, 'data_set_name': '可以使用:anl82_salq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on delta of Q sales'} +{'id': 83104, 'data_set_name': '可以使用:annual_accounts_receivable_total_fast_d1', 'description': '不可使用,仅供参考:Total accounts receivable as of the year.'} +{'id': 9342, 'data_set_name': '可以使用:anl82_opry_profitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on value of annual operating profit'} +{'id': 6983, 'data_set_name': '可以使用:anl49_vector_35estd35yrgrowthratecashflowpershare', 'description': '不可使用,仅供参考:The annual compounded growth rate using the average of the three latest base years to the projected 3-5-year Book Value per Share.'} +{'id': 9177, 'data_set_name': '可以使用:anl82_ebty_profitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on value of annual EBITDA'} +{'id': 5678, 'data_set_name': '可以使用:research_development_expense_actual_value', 'description': '不可使用,仅供参考:Research and Development Expense- announced financial value'} +{'id': 6961, 'data_set_name': '可以使用:anl49_salesorrevenuespershare', 'description': '不可使用,仅供参考:Net sales or revenues divided by the number of common shares outstanding at the fiscal year end.'} +{'id': 320742, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_b_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10188, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on value of Q operating profit'} +{'id': 10117, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on value of Q net income'} +{'id': 5695, 'data_set_name': '可以使用:sales_estimate_stddev_quarterly', 'description': '不可使用,仅供参考:Standard deviation of Sales estimations'} +{'id': 83863, 'data_set_name': '可以使用:fnd3_qacctadj_accreceivable_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Accounts receivable'} +{'id': 7648, 'data_set_name': '可以使用:anl69_sales_latest_ann_dt_qtrly', 'description': '不可使用,仅供参考:Latest Announcement Date Quarterly'} +{'id': 85448, 'data_set_name': '可以使用:fnd72_a2_sales_to_cur_asset', 'description': '不可使用,仅供参考:Current Assets turnover ratio measures how well a company is making use of its current assets in generating sales'} +{'id': 6756, 'data_set_name': '可以使用:anl49_annualfiscalsalesorrevenues', 'description': '不可使用,仅供参考:The total fiscal year sales or revenues as reported.'} +{'id': 7001, 'data_set_name': '可以使用:anl49_vector_annualfiscalsalesorrevenues', 'description': '不可使用,仅供参考:The total fiscal year sales or revenues as reported.'} +{'id': 10218, 'data_set_name': '可以使用:mdl211_opry_profitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on value of annual operating profit'} +{'id': 9122, 'data_set_name': '可以使用:anl82_ebtq_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on delta of Q EBITDA'} +{'id': 9175, 'data_set_name': '可以使用:anl82_ebty_profitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on value of annual EBITDA'} +{'id': 6504, 'data_set_name': '可以使用:latest_annual_currency_update_sales', 'description': "不可使用,仅供参考:Date or timestamp when the annual sales value's currency was last updated."} +{'id': 320702, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_all_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Sales'} +{'id': 10041, 'data_set_name': '可以使用:mdl211_ebty_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on delta of annual ebitda'} +{'id': 10336, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on value of annual sales'} +{'id': 86037, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_inventory_growth_to_sales_growth', 'description': '不可使用,仅供参考:Year-over-year growth in inventory as a multiple of year-over-year growth in sales'} +{'id': 9367, 'data_set_name': '可以使用:anl82_preq_profitability_profitability10', 'description': '不可使用,仅供参考:Profitability Measure Type 10 Based on Value of Q Pre-Tax Profit'} +{'id': 6959, 'data_set_name': '可以使用:anl49_salesorrevenues', 'description': '不可使用,仅供参考:Total sales revenue less returns, allowances; and sales discounts; also known as net sales.'} +{'id': 6521, 'data_set_name': '可以使用:latest_quarterly_currency_update_sales', 'description': '不可使用,仅供参考:Date or timestamp when the currency for the quarterly sales value was last updated.'} +{'id': 5539, 'data_set_name': '可以使用:financing_cashflow_reported_value', 'description': '不可使用,仅供参考:Cash Flow From Financing - Value'} +{'id': 9454, 'data_set_name': '可以使用:anl82_saly_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on delta of annual sales'} +{'id': 86401, 'data_set_name': '可以使用:fnd72_q2_sales_to_tot_asset', 'description': '不可使用,仅供参考:Assets turnover ratio represents the amount of sales or revenues generated per dollar of assets'} +{'id': 10297, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on value of Q sales'} +{'id': 86660, 'data_set_name': '可以使用:fnd72_s_pit_or_bs_q_notes_receivable', 'description': "不可使用,仅供参考:Promissory notes written from a bank related to a company's ordinary business transaction"} +{'id': 5683, 'data_set_name': '可以使用:sales_estimate_average_quarterly', 'description': '不可使用,仅供参考:Sales - mean of estimations'} +{'id': 80723, 'data_set_name': '可以使用:sales_revenue_total_3', 'description': '不可使用,仅供参考:Total sales revenue recognized during the period.'} +{'id': 85347, 'data_set_name': '可以使用:fnd72_a1_depr_exp_to_net_sales', 'description': '不可使用,仅供参考:Depreciation expense as a percentage of revenue'} +{'id': 10202, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on delta of annual operating profit'} +{'id': 85934, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_trail_12m_sales_per_sh', 'description': '不可使用,仅供参考:Calculated by adding Sales per Share for the last 4 quarters, 2 semi-annuals, or annual'} +{'id': 320694, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 85883, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_pretax_inc_to_net_sales', 'description': '不可使用,仅供参考:Pre-tax income as a percentage of net sales'} +{'id': 10149, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on delta of annual net income'} +{'id': 6005, 'data_set_name': '可以使用:anl44_best_sales_lo', 'description': '不可使用,仅供参考:best sales lo'} +{'id': 320699, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_all_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Sales'} +{'id': 80553, 'data_set_name': '可以使用:income_tax_expense_3', 'description': '不可使用,仅供参考:[Quarterly] Total Extraordinary Items'} +{'id': 10340, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on value of annual sales'} +{'id': 9137, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on value of Q EBITDA'} +{'id': 85431, 'data_set_name': '可以使用:fnd72_a2_rd_expend_to_net_sales', 'description': '不可使用,仅供参考:No longer supported'} +{'id': 9239, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on delta of Q net income'} +{'id': 9234, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on delta of Q net income'} +{'id': 80853, 'data_set_name': '可以使用:total_tax_expense_2', 'description': '不可使用,仅供参考:Total tax expense recognized during the period.'} +{'id': 5685, 'data_set_name': '可以使用:sales_estimate_count_2', 'description': '不可使用,仅供参考:Number of Sales estimates'} +{'id': 84295, 'data_set_name': '可以使用:cashflow_invst', 'description': '不可使用,仅供参考:Investing Activities - Net Cash Flow'} +{'id': 6771, 'data_set_name': '可以使用:anl49_backfill_2ndfiscalquartersalesorrevenuesindicator', 'description': '不可使用,仅供参考:Second fiscal quarter sales or revenues indicator'} +{'id': 88087, 'data_set_name': '可以使用:oth401_game_receivable_chg', 'description': '不可使用,仅供参考:Change in Receivables'} +{'id': 80819, 'data_set_name': '可以使用:short_term_selling_general_admin_expense', 'description': '不可使用,仅供参考:Short-term selling, general, and administrative expenses.'} +{'id': 10199, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on delta of annual operating profit'} +{'id': 83151, 'data_set_name': '可以使用:annual_operating_cashflow_amount', 'description': '不可使用,仅供参考:Net cash flow from operating activities for the year.'} +{'id': 6441, 'data_set_name': '可以使用:anl44_second_en_sales_broker', 'description': '不可使用,仅供参考:sales broker'} +{'id': 6001, 'data_set_name': '可以使用:anl44_best_sales_4wk_dn', 'description': '不可使用,仅供参考:best sales 4wk dn'} +{'id': 321164, 'data_set_name': '可以使用:pv87_customerwelfare_pulse_mean', 'description': '不可使用,仅供参考:Short-term score of Customer Welfare topic'} +{'id': 324461, 'data_set_name': '可以使用:pv87_qtr_matrix_interest_expense_estimate_high', 'description': '不可使用,仅供参考:High of Interest Expense Estimate'} +{'id': 10325, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of annual sales'} +{'id': 10334, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on value of annual sales'} +{'id': 317757, 'data_set_name': '可以使用:pv20_q_1_ard_accts_receivable_trade', 'description': '不可使用,仅供参考:ARD Accounts Receivable - Trade'} +{'id': 86344, 'data_set_name': '可以使用:fnd72_q1_inc_bef_xo_items_to_net_sales', 'description': '不可使用,仅供参考:Income before extraordinary items as a percentage of net sales'} +{'id': 10298, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on value of Q sales'} +{'id': 83563, 'data_set_name': '可以使用:fnd3_a_sgaexpense_fast_d1', 'description': '不可使用,仅供参考:Annual Selling, General & Administrative Expense'} +{'id': 86310, 'data_set_name': '可以使用:fnd72_q1_geo_grow_cogs_to_net_sales', 'description': '不可使用,仅供参考:Compound 5-year growth rate in cost of goods sold as a percentage of revenue'} +{'id': 5692, 'data_set_name': '可以使用:sales_estimate_minimum', 'description': '不可使用,仅供参考:Sales - The lowest estimation'} +{'id': 320753, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9465, 'data_set_name': '可以使用:anl82_saly_profitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on value of annual sales'} +{'id': 6283, 'data_set_name': '可以使用:anl44_orig_en_sales_prevalue', 'description': '不可使用,仅供参考:orig en sales v1 0 0 prevalue'} +{'id': 86227, 'data_set_name': '可以使用:fnd72_pit_or_is_q_is_expense_stock_based_comp', 'description': '不可使用,仅供参考:The expense for stock-based compensation'} +{'id': 5687, 'data_set_name': '可以使用:sales_estimate_dispersion', 'description': '不可使用,仅供参考:Standard deviation of Sales estimations for the annual period.'} +{'id': 320762, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Sales'} +{'id': 84292, 'data_set_name': '可以使用:cashflow', 'description': '不可使用,仅供参考:Cashflow (Annual)'} +{'id': 320761, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Sales'} +{'id': 6960, 'data_set_name': '可以使用:anl49_salesorrevenuesindicator', 'description': '不可使用,仅供参考:Sales or revenues indicator'} +{'id': 9168, 'data_set_name': '可以使用:anl82_ebty_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on delta of annual EBITDA'} +{'id': 86156, 'data_set_name': '可以使用:fnd72_pit_or_is_a_is_expense_stock_based_comp', 'description': '不可使用,仅供参考:The expense for stock-based compensation'} +{'id': 10176, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of Q operating profit'} +{'id': 80559, 'data_set_name': '可以使用:interest_and_tax_expense', 'description': '不可使用,仅供参考:Total interest and tax expense for the period.'} +{'id': 5701, 'data_set_name': '可以使用:sales_min_guidance_quarterly', 'description': '不可使用,仅供参考:Minimum guidance value for Sales'} +{'id': 10270, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on delta of annual pre-tax profit'} +{'id': 7249, 'data_set_name': '可以使用:anl69_best_sales_chg_pct', 'description': '不可使用,仅供参考:Sales % Chg'} +{'id': 86032, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_invent_to_sales', 'description': '不可使用,仅供参考:Ratio of inventory to sales, a way to estimate the number of times the company can turn over its inventory in 1 year'} +{'id': 87006, 'data_set_name': '可以使用:fnd72_s_pit_or_is_q_is_expense_stock_based_comp', 'description': '不可使用,仅供参考:The expense for stock-based compensation'} +{'id': 10003, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on value of Q ebitda'} +{'id': 10179, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on value of Q operating profit'} +{'id': 6487, 'data_set_name': '可以使用:forecast_currency_sales', 'description': '不可使用,仅供参考:Currency in which the sales forecast is denominated.'} +{'id': 322110, 'data_set_name': '可以使用:pv87_interest_expense_consensus_median_scale', 'description': '不可使用,仅供参考:Scale of Interest Expense Consensus Median'} +{'id': 79259, 'data_set_name': '可以使用:accounts_receivable_current', 'description': '不可使用,仅供参考:Current accounts receivable at period end.'} +{'id': 10048, 'data_set_name': '可以使用:mdl211_ebty_profitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on value of annual ebitda'} +{'id': 9415, 'data_set_name': '可以使用:anl82_salq_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on delta of Q sales'} +{'id': 10290, 'data_set_name': '可以使用:mdl211_salq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of Q sales'} +{'id': 79363, 'data_set_name': '可以使用:equipment_depreciation_expense', 'description': '不可使用,仅供参考:Depreciation expense for equipment during the period.'} +{'id': 10282, 'data_set_name': '可以使用:mdl211_salq_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of Q sales'} +{'id': 85932, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_trail_12m_net_sales', 'description': '不可使用,仅供参考:Calculated by adding Sales/Revenue/Turnover for the last 4 quarters, 2 semi-annuals, or annual'} +{'id': 9247, 'data_set_name': '可以使用:anl82_netq_profitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on value of Q net income'} +{'id': 10233, 'data_set_name': '可以使用:mdl211_preq_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on delta of Q pre-tax profit'} +{'id': 322107, 'data_set_name': '可以使用:pv87_interest_expense_consensus_mean', 'description': '不可使用,仅供参考:Interest Expense Consensus Mean'} +{'id': 85418, 'data_set_name': '可以使用:fnd72_a1_net_sales_to_net_sales', 'description': '不可使用,仅供参考:Net sales as a percentage of net sales'} +{'id': 10115, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on value of Q net income'} +{'id': 85940, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_accounts_receivable_growth', 'description': '不可使用,仅供参考:Percentage growth in inventory from last year to the current year'} +{'id': 85399, 'data_set_name': '可以使用:fnd72_a1_inc_bef_xo_items_to_net_sales', 'description': '不可使用,仅供参考:Income before extraordinary items as a percentage of net sales'} +{'id': 86393, 'data_set_name': '可以使用:fnd72_q2_sales_to_accum_depr', 'description': '不可使用,仅供参考:Accumulated depreciation turnover ratio represents the amount of sales or revenue generated per dollar of accumulated depreciation'} +{'id': 10053, 'data_set_name': '可以使用:mdl211_ebty_profitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on value of annual ebitda'} +{'id': 86124, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_trail_12m_sales_per_sh', 'description': '不可使用,仅供参考:Calculated by adding Sales per Share for the last 4 quarters, 2 semi-annuals, or annual'} +{'id': 9244, 'data_set_name': '可以使用:anl82_netq_profitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on value of Q net income'} +{'id': 10006, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on value of Q ebitda'} +{'id': 320719, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 85389, 'data_set_name': '可以使用:fnd72_a1_geo_grow_sales_per_sh', 'description': '不可使用,仅供参考:Compound 5-year growth rate in sales per share'} +{'id': 6895, 'data_set_name': '可以使用:anl49_cashflowpershare', 'description': '不可使用,仅供参考:Cash flow less preferred dividends (if any) divided by common shares outstanding at year end.'} +{'id': 85447, 'data_set_name': '可以使用:fnd72_a2_sales_to_cash', 'description': '不可使用,仅供参考:Cash and near cash turnover ratio measures how effective a company is utilizing its cash, in actual'} +{'id': 6729, 'data_set_name': '可以使用:anl49_2ndfiscalquartersalesorrevenuesindicator', 'description': '不可使用,仅供参考:Second fiscal quarter sales or revenues indicator'} +{'id': 10204, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on delta of annual operating profit'} +{'id': 10235, 'data_set_name': '可以使用:mdl211_preq_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on delta of Q pre-tax profit'} +{'id': 83941, 'data_set_name': '可以使用:fnd3_qacctadj_opeexpenses_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Total Operating Expenses'} +{'id': 5601, 'data_set_name': '可以使用:median_sales_estimate', 'description': '不可使用,仅供参考:Sales - median of estimations'} +{'id': 10266, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of annual pre-tax profit'} +{'id': 5705, 'data_set_name': '可以使用:selling_general_admin_expense_actual_value', 'description': '不可使用,仅供参考:Selling, General & Administrative Expense - actual value'} +{'id': 9372, 'data_set_name': '可以使用:anl82_preq_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of Q pre-tax profit'} +{'id': 79085, 'data_set_name': '可以使用:fn_prepaid_expense_q', 'description': '不可使用,仅供参考:Carrying amount for an unclassified balance sheet date of expenditures made in advance of when the economic benefit of the cost will be realized, and which will be expensed in future periods with the passage of time or when a triggering event occurs. For a classified balance sheet, represents the noncurrent portion of prepaid expenses (the current portion has a separate concept).'} +{'id': 6871, 'data_set_name': '可以使用:anl49_backfill_salesorrevenuesindicator', 'description': '不可使用,仅供参考:Sales or revenues indicator'} +{'id': 5689, 'data_set_name': '可以使用:sales_estimate_maximum_quarterly', 'description': '不可使用,仅供参考:Sales - The highest estimation'} +{'id': 10225, 'data_set_name': '可以使用:mdl211_preq_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on delta of Q pre-tax profit'} +{'id': 85162, 'data_set_name': '可以使用:receivable', 'description': '不可使用,仅供参考:Receivables - Total'} +{'id': 80662, 'data_set_name': '可以使用:other_current_receivables', 'description': '不可使用,仅供参考:Other receivables classified as current assets.'} +{'id': 9424, 'data_set_name': '可以使用:anl82_salq_profitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on value of Q sales'} +{'id': 9318, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on value of Q operating profit'} +{'id': 320707, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_b_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320712, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_b_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Sales'} +{'id': 9420, 'data_set_name': '可以使用:anl82_salq_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on delta of Q sales'} +{'id': 79333, 'data_set_name': '可以使用:current_tax_receivable', 'description': '不可使用,仅供参考:Amount of tax receivables expected to be collected within one year.'} +{'id': 9317, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on value of Q operating profit'} +{'id': 10321, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on delta of annual sales'} +{'id': 6004, 'data_set_name': '可以使用:anl44_best_sales_hi', 'description': '不可使用,仅供参考:best sales hi'} +{'id': 9291, 'data_set_name': '可以使用:anl82_nety_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of annual net income'} +{'id': 319323, 'data_set_name': '可以使用:pv64_dif_stal_fund_expense_ratio', 'description': '不可使用,仅供参考:The amount investors pay for expenses incurred in operating a mutual fund (after any waivers).'} +{'id': 83554, 'data_set_name': '可以使用:fnd3_a_receivables', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Receivables'} +{'id': 9313, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on value of Q operating profit'} +{'id': 86553, 'data_set_name': '可以使用:fnd72_s_pit_or_bs_q_1_notes_receivable', 'description': "不可使用,仅供参考:Promissory notes written from a bank related to a company's ordinary business transaction"} +{'id': 85341, 'data_set_name': '可以使用:fnd72_a1_cogs_to_net_sales', 'description': '不可使用,仅供参考:Percentage of revenue used to pay costs of goods sold'} +{'id': 5633, 'data_set_name': '可以使用:min_research_development_expense_guidance', 'description': '不可使用,仅供参考:Minimum guidance value for Research & Development Expense'} +{'id': 9373, 'data_set_name': '可以使用:anl82_preq_profitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on value of Q pre-tax profit'} +{'id': 86080, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_px_to_sales_ratio', 'description': "不可使用,仅供参考:The price-to-sales ratio is the ratio of a stock's last price divided by sales per share"} +{'id': 9180, 'data_set_name': '可以使用:anl82_ebty_profitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on value of annual EBITDA'} +{'id': 6986, 'data_set_name': '可以使用:anl49_vector_35estd35yrgrowthratesalespershare', 'description': '不可使用,仅供参考:The annual compounded growth rate using the average of the three latest base years to the projected 3-5-year Sales per Share.'} +{'id': 87020, 'data_set_name': '可以使用:fnd72_s_pit_or_is_q_is_pension_expense_income', 'description': '不可使用,仅供参考:The net amount of pension cost that is recognized in the income statement'} +{'id': 6006, 'data_set_name': '可以使用:anl44_best_sales_median', 'description': '不可使用,仅供参考:best sales median'} +{'id': 5556, 'data_set_name': '可以使用:lowest_sales_estimate', 'description': '不可使用,仅供参考:Sales - The lowest estimation for the annual period'} +{'id': 9335, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on delta of annual operating profit'} +{'id': 83316, 'data_set_name': '可以使用:fnd3_Q_accreceivable', 'description': '不可使用,仅供参考:Quarterly Accounts receivable'} +{'id': 5849, 'data_set_name': '可以使用:anl44_2_sales_lastactvalue', 'description': '不可使用,仅供参考:sales lastactvalue'} +{'id': 5699, 'data_set_name': '可以使用:sales_max_guidance_quarterly', 'description': '不可使用,仅供参考:The maximum guidance value for sales.'} +{'id': 84059, 'data_set_name': '可以使用:quarterly_equity_compensation_expense_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Share Based Compensation'} +{'id': 5629, 'data_set_name': '可以使用:min_operating_cashflow_guidance', 'description': '不可使用,仅供参考:Minimum guidance value for Cash Flow from Operations'} +{'id': 7639, 'data_set_name': '可以使用:anl69_sales_best_cur_fiscal_qtr_period', 'description': '不可使用,仅供参考:Current Fiscal Quarter Period D'} +{'id': 320718, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9281, 'data_set_name': '可以使用:anl82_nety_profitability_profitability10', 'description': '不可使用,仅供参考:Profitability measure type 10 based on value of annual net income'} +{'id': 10338, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on value of annual sales'} +{'id': 9464, 'data_set_name': '可以使用:anl82_saly_profitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on value of annual sales'} +{'id': 5625, 'data_set_name': '可以使用:min_investing_cashflow_guidance_2', 'description': '不可使用,仅供参考:Cash Flow From Investing - Minimum guidance value for the annual period'} +{'id': 79265, 'data_set_name': '可以使用:accounts_receivable_total_6', 'description': '不可使用,仅供参考:Total value of accounts receivable outstanding at period end.'} +{'id': 85450, 'data_set_name': '可以使用:fnd72_a2_sales_to_lt_invest', 'description': '不可使用,仅供参考:Long-Term investments turnover ratio represents the amount of sales or revenues generated per dollar of long-term investments, in actual'} +{'id': 86984, 'data_set_name': '可以使用:fnd72_s_pit_or_is_a_sales_rev_turn', 'description': '不可使用,仅供参考:Sales/Revenue/Turnover'} +{'id': 10140, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of annual net income'} +{'id': 10049, 'data_set_name': '可以使用:mdl211_ebty_profitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on value of annual ebitda'} +{'id': 10341, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on value of annual sales'} +{'id': 9314, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of Q operating profit'} +{'id': 9289, 'data_set_name': '可以使用:anl82_nety_profitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on value of annual net income'} +{'id': 85365, 'data_set_name': '可以使用:fnd72_a1_geo_grow_cogs_to_net_sales', 'description': '不可使用,仅供参考:Compound 5-year growth rate in cost of goods sold as a percentage of revenue'} +{'id': 83160, 'data_set_name': '可以使用:annual_sales_total_fast_d1', 'description': '不可使用,仅供参考:Total revenue recognized during the year.'} +{'id': 320715, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 83358, 'data_set_name': '可以使用:fnd3_Q_opeexpenses', 'description': '不可使用,仅供参考:Quarterly Total Operating Expenses'} +{'id': 320740, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_b_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 6360, 'data_set_name': '可以使用:anl44_sales_value', 'description': '不可使用,仅供参考:Sales D0 value'} +{'id': 78927, 'data_set_name': '可以使用:fn_allocated_share_based_compensation_expense_a', 'description': '不可使用,仅供参考:Represents the expense recognized during the period arising from equity-based compensation arrangements (for example, shares of stock, unit, stock options or other equity instruments) with employees, directors and certain consultants qualifying for treatment as employees.'} +{'id': 9132, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on value of Q EBITDA'} +{'id': 6442, 'data_set_name': '可以使用:anl44_second_en_sales_coveredby', 'description': '不可使用,仅供参考:sales coveredby'} +{'id': 9287, 'data_set_name': '可以使用:anl82_nety_profitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on value of annual net income'} +{'id': 10232, 'data_set_name': '可以使用:mdl211_preq_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on delta of Q pre-tax profit'} +{'id': 10210, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on delta of annual operating profit'} +{'id': 6003, 'data_set_name': '可以使用:anl44_best_sales_chg_pct', 'description': '不可使用,仅供参考:best sales chg pct'} +{'id': 9337, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on delta of annual operating profit'} +{'id': 79392, 'data_set_name': '可以使用:financing_cashflow_net', 'description': '不可使用,仅供参考:Net cash flow from financing activities.'} +{'id': 9183, 'data_set_name': '可以使用:anl82_ebty_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of annual EBITDA'} +{'id': 10000, 'data_set_name': '可以使用:mdl211_ebtq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of Q ebitda'} +{'id': 86396, 'data_set_name': '可以使用:fnd72_q2_sales_to_invent', 'description': '不可使用,仅供参考:Sales to inventory ratio provides critical clues about whether the firm is keeping storage costs under control and achieving the target revenues'} +{'id': 322103, 'data_set_name': '可以使用:pv87_interest_expense_consensus_high', 'description': '不可使用,仅供参考:Interest Expense Consensus High'} +{'id': 80705, 'data_set_name': '可以使用:receivables_premium_total', 'description': '不可使用,仅供参考:Total value of premium receivables.'} +{'id': 320741, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_b_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 87038, 'data_set_name': '可以使用:fnd72_s_pit_or_is_q_sales_rev_turn', 'description': '不可使用,仅供参考:Sales/Revenue/Turnover'} +{'id': 10293, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on value of Q sales'} +{'id': 79264, 'data_set_name': '可以使用:accounts_receivable_total_5', 'description': '不可使用,仅供参考:Total accounts receivable as of the reporting date.'} +{'id': 83103, 'data_set_name': '可以使用:annual_accounts_receivable_total', 'description': '不可使用,仅供参考:Total accounts receivable as of the year.'} +{'id': 10172, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on delta of Q operating profit'} +{'id': 80709, 'data_set_name': '可以使用:rental_expense', 'description': '不可使用,仅供参考:Total rental expense incurred during the period.'} +{'id': 9288, 'data_set_name': '可以使用:anl82_nety_profitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on value of annual net income'} +{'id': 6757, 'data_set_name': '可以使用:anl49_annualfiscalsalesorrevenuesindicator', 'description': '不可使用,仅供参考:Annual fiscal sales or revenues indicator'} +{'id': 83115, 'data_set_name': '可以使用:annual_cost_of_sales_total', 'description': '不可使用,仅供参考:Total cost incurred to generate revenue for the year.'} +{'id': 85161, 'data_set_name': '可以使用:rd_expense', 'description': '不可使用,仅供参考:Research And Development (Quarterly)'} +{'id': 5964, 'data_set_name': '可以使用:anl44_best_opp_to_sales', 'description': '不可使用,仅供参考:best opp to sales'} +{'id': 83597, 'data_set_name': '可以使用:fnd3_aacctadj_accreceivable_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Accounts receivable'} +{'id': 6872, 'data_set_name': '可以使用:anl49_backfill_salesorrevenuespershare', 'description': '不可使用,仅供参考:Net sales or revenues divided by the number of common shares outstanding at the fiscal year end.'} +{'id': 10031, 'data_set_name': '可以使用:mdl211_ebty_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on delta of annual ebitda'} +{'id': 10275, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on delta of annual pre-tax profit'} +{'id': 10012, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on value of Q ebitda'} +{'id': 10054, 'data_set_name': '可以使用:mdl211_ebty_profitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on value of annual ebitda'} +{'id': 10159, 'data_set_name': '可以使用:mdl211_nety_profitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on value of annual net income'} +{'id': 7246, 'data_set_name': '可以使用:anl69_best_sales_4wk_chg', 'description': '不可使用,仅供参考:Sales 4 wk Chg'} +{'id': 10337, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on value of annual sales'} +{'id': 10212, 'data_set_name': '可以使用:mdl211_opry_profitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on value of annual operating profit'} +{'id': 9138, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of Q EBITDA'} +{'id': 10331, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on delta of annual sales'} +{'id': 10327, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on delta of annual sales'} +{'id': 83939, 'data_set_name': '可以使用:fnd3_qacctadj_opeexpenseexitems_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Operating Expense Extraordinary Items'} +{'id': 86395, 'data_set_name': '可以使用:fnd72_q2_sales_to_cur_asset', 'description': '不可使用,仅供参考:Current Assets turnover ratio measures how well a company is making use of its current assets in generating sales'} +{'id': 86263, 'data_set_name': '可以使用:fnd72_pit_or_is_q_sales_rev_turn', 'description': '不可使用,仅供参考:Sales/Revenue/Turnover'} +{'id': 79334, 'data_set_name': '可以使用:customer_securities_investment', 'description': '不可使用,仅供参考:Customer securities held for investment purposes.'} +{'id': 85854, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_low_px_to_sales_ratio', 'description': "不可使用,仅供参考:The low price-to-sales ratio is the ratio of a stock's low price divided by the sales per share"} +{'id': 86089, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_sales_5yr_avg_gr', 'description': '不可使用,仅供参考:Five-year average of sales growth'} +{'id': 10295, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of Q sales'} +{'id': 10272, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on delta of annual pre-tax profit'} +{'id': 6785, 'data_set_name': '可以使用:anl49_backfill_3rdfiscalquartersalesorrevenues', 'description': '不可使用,仅供参考:Third fiscal quarter sales or revenues as reported.'} +{'id': 9296, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on delta of Q operating profit'} +{'id': 10174, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on delta of Q operating profit'} +{'id': 9332, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on delta of annual operating profit'} +{'id': 5616, 'data_set_name': '可以使用:min_financing_cashflow_guidance_2', 'description': '不可使用,仅供参考:Minimum guidance value for Cash Flow From Financing on an annual basis'} +{'id': 9143, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of Q EBITDA'} +{'id': 83828, 'data_set_name': '可以使用:fnd3_q_sgaexpense', 'description': '不可使用,仅供参考:Quarterly Selling, General & Administrative Expense'} +{'id': 7645, 'data_set_name': '可以使用:anl69_sales_expected_report_dt', 'description': '不可使用,仅供参考:Expected Earnings Report Date'} +{'id': 10237, 'data_set_name': '可以使用:mdl211_preq_profitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on value of Q pre-tax profit'} +{'id': 5530, 'data_set_name': '可以使用:est_sales', 'description': '不可使用,仅供参考:Sales - mean of estimations'} +{'id': 10100, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of Q net income'} +{'id': 9272, 'data_set_name': '可以使用:anl82_nety_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on delta of annual net income'} +{'id': 86869, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_sales_5yr_avg_gr', 'description': '不可使用,仅供参考:Five-year average of sales growth'} +{'id': 9468, 'data_set_name': '可以使用:anl82_saly_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of annual sales'} +{'id': 6509, 'data_set_name': '可以使用:latest_annual_period_end_update_sales', 'description': '不可使用,仅供参考:Date or timestamp when the period end for the annual sales value was last updated.'} +{'id': 86090, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_sales_growth', 'description': '不可使用,仅供参考:A percentage increase or decrease in sales revenue by comparing the current period with the same period prior year'} +{'id': 83829, 'data_set_name': '可以使用:fnd3_q_sgaexpense_fast_d1', 'description': '不可使用,仅供参考:Quarterly Selling, General & Administrative Expense'} +{'id': 10326, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on delta of annual sales'} +{'id': 9423, 'data_set_name': '可以使用:anl82_salq_profitability_profitability10', 'description': '不可使用,仅供参考:Profitability measure type 10 based on value of Q sales'} +{'id': 7640, 'data_set_name': '可以使用:anl69_sales_best_cur_fiscal_year_period', 'description': '不可使用,仅供参考:Current Fiscal Year Period Date'} +{'id': 9235, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on delta of Q net income'} +{'id': 79084, 'data_set_name': '可以使用:fn_prepaid_expense_a', 'description': '不可使用,仅供参考:Carrying amount for an unclassified balance sheet date of expenditures made in advance of when the economic benefit of the cost will be realized, and which will be expensed in future periods with the passage of time or when a triggering event occurs. For a classified balance sheet, represents the noncurrent portion of prepaid expenses (the current portion has a separate concept).'} +{'id': 83674, 'data_set_name': '可以使用:fnd3_aacctadj_opeexpenseexitems', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Operating Expense Extraordinary Items'} +{'id': 83137, 'data_set_name': '可以使用:annual_income_tax_expense', 'description': '不可使用,仅供参考:Total income tax expense for the year.'} +{'id': 10299, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on value of Q sales'} +{'id': 79314, 'data_set_name': '可以使用:benefit_expense_total', 'description': '不可使用,仅供参考:Total benefit expense for the period.'} +{'id': 7132, 'data_set_name': '可以使用:anl69_best_ebit_to_sales', 'description': '不可使用,仅供参考:EBIT Margin'} +{'id': 9301, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on delta of Q operating profit'} +{'id': 79262, 'data_set_name': '可以使用:accounts_receivable_gross_2', 'description': '不可使用,仅供参考:[Quarterly] Accounts Receivable - Trade, Gross'} +{'id': 83952, 'data_set_name': '可以使用:fnd3_qacctadj_receivables', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Increase or Decrease in Receivables'} +{'id': 9993, 'data_set_name': '可以使用:mdl211_ebtq_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on delta of Q ebitda'} +{'id': 9134, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on value of Q EBITDA'} +{'id': 320705, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_p1_b_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320738, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_all_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Sales'} +{'id': 86399, 'data_set_name': '可以使用:fnd72_q2_sales_to_other_asset', 'description': "不可使用,仅供参考:Other assets turnover ratio measures the efficiency of a company's use of its other assets in generating revenue or income to the company, in actual"} +{'id': 9450, 'data_set_name': '可以使用:anl82_saly_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on delta of annual sales'} +{'id': 10200, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of annual operating profit'} +{'id': 83223, 'data_set_name': '可以使用:fnd3_A_opeexpenseexitems', 'description': '不可使用,仅供参考:Annual Operating Expense Extraordinary Items'} +{'id': 86818, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_invent_to_sales', 'description': '不可使用,仅供参考:Ratio of inventory to sales, a way to estimate the number of times the company can turn over its inventory in 1 year'} +{'id': 84211, 'data_set_name': '可以使用:fnd31_irttmsalesev', 'description': "不可使用,仅供参考:Industry-relative TTM Sales to Enterprise Value. It is defined as a stock's trailing 12-month sales-to-enterprise (SEV) value less the average of the SEVs of all stocks in the same industry deflated by the standard deviation of the SEVs of all stocks in the same relative universe."} +{'id': 6526, 'data_set_name': '可以使用:latest_quarterly_period_end_update_sales_orig', 'description': '不可使用,仅供参考:Date or timestamp when the period end for the quarterly sales value was last updated in the original version module.'} +{'id': 6786, 'data_set_name': '可以使用:anl49_backfill_3rdfiscalquartersalesorrevenuesindicator', 'description': '不可使用,仅供参考:Third fiscal quarter sales or revenues indicator'} +{'id': 9319, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of Q operating profit'} +{'id': 86164, 'data_set_name': '可以使用:fnd72_pit_or_is_a_is_int_expense', 'description': '不可使用,仅供参考:Interest Expense'} +{'id': 9360, 'data_set_name': '可以使用:anl82_preq_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on delta of Q pre-tax profit'} +{'id': 6282, 'data_set_name': '可以使用:anl44_orig_en_sales_coveredby', 'description': '不可使用,仅供参考:Orig EN sales V1 0 0 covered by'} +{'id': 85535, 'data_set_name': '可以使用:fnd72_pit_or_bs_a_bs_curr_rental_expense', 'description': '不可使用,仅供参考:Operating lease expenses recognized in the income statement for the period'} +{'id': 6525, 'data_set_name': '可以使用:latest_quarterly_period_end_update_sales', 'description': '不可使用,仅供参考:Date or timestamp when the period end for the quarterly sales value was last updated.'} +{'id': 9331, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on delta of annual operating profit'} +{'id': 84086, 'data_set_name': '可以使用:quarterly_investing_cashflow_amount', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Investing Cash Flow'} +{'id': 85332, 'data_set_name': '可以使用:fnd72_a1_cap_expend_to_sales', 'description': '不可使用,仅供参考:Measures the percentage of capital expenditures to sales'} +{'id': 6978, 'data_set_name': '可以使用:anl49_vector_1stfiscalquartersalesorrevenues', 'description': '不可使用,仅供参考:First fiscal quarter sales or revenues as reported.'} +{'id': 5571, 'data_set_name': '可以使用:max_financing_cashflow_guidance', 'description': '不可使用,仅供参考:Cash Flow From Financing - Maximum guidance value'} +{'id': 10120, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on value of Q net income'} +{'id': 83959, 'data_set_name': '可以使用:fnd3_qacctadj_sgaexpense_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Selling, General & Administrative Expense'} +{'id': 85339, 'data_set_name': '可以使用:fnd72_a1_cfo_to_sales', 'description': '不可使用,仅供参考:Measures the percentage of Cash from Operations to Sales'} +{'id': 10242, 'data_set_name': '可以使用:mdl211_preq_profitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on value of Q pre-tax profit'} +{'id': 10284, 'data_set_name': '可以使用:mdl211_salq_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on delta of Q sales'} +{'id': 320730, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 85445, 'data_set_name': '可以使用:fnd72_a2_sales_to_acct_rcv', 'description': "不可使用,仅供参考:Accounts receivable turnover ratio indicates the liquidity of the company's receivables, , in actual"} +{'id': 9251, 'data_set_name': '可以使用:anl82_netq_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of Q net income'} +{'id': 86072, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_pretax_inc_to_net_sales', 'description': '不可使用,仅供参考:Pre-tax income as a percentage of net sales'} +{'id': 9351, 'data_set_name': '可以使用:anl82_opry_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of annual operating profit'} +{'id': 10002, 'data_set_name': '可以使用:mdl211_ebtq_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on delta of Q ebitda'} +{'id': 5573, 'data_set_name': '可以使用:max_free_cashflow_guidance', 'description': '不可使用,仅供参考:The maximum guidance value for Free Cash Flow.'} +{'id': 86347, 'data_set_name': '可以使用:fnd72_q1_int_exp_to_net_sales', 'description': '不可使用,仅供参考:Interest expense as a percentage of revenue'} +{'id': 320698, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_all_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Sales'} +{'id': 6796, 'data_set_name': '可以使用:anl49_backfill_annualfiscalsalesorrevenuesindicator', 'description': '不可使用,仅供参考:Annual fiscal sales or revenues indicator'} +{'id': 9303, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on delta of Q operating profit'} +{'id': 10228, 'data_set_name': '可以使用:mdl211_preq_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on delta of Q pre-tax profit'} +{'id': 86793, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_ev_to_t12m_sales', 'description': '不可使用,仅供参考:Periodic enterprise value as a multiple of sales'} +{'id': 319401, 'data_set_name': '可以使用:pv64_out_stal_fund_expense_ratio', 'description': '不可使用,仅供参考:The amount investors pay for expenses incurred in operating a mutual fund (after any waivers).'} +{'id': 10143, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of annual net income'} +{'id': 86297, 'data_set_name': '可以使用:fnd72_q1_ebit_to_net_sales', 'description': '不可使用,仅供参考:Earnings before interest and taxes as a percentage of net sales'} +{'id': 86000, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_ev_to_t12m_sales', 'description': '不可使用,仅供参考:Periodic enterprise value as a multiple of sales'} +{'id': 10181, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of Q operating profit'} +{'id': 5468, 'data_set_name': '可以使用:cashflow_per_share_maximum', 'description': '不可使用,仅供参考:Cash Flow - The highest estimation, per share, with a delay of 1 quarter'} +{'id': 5577, 'data_set_name': '可以使用:max_investing_cashflow_guidance', 'description': '不可使用,仅供参考:The maximum guidance value for Cash Flow from Investing.'} +{'id': 9305, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on delta of Q operating profit'} +{'id': 9356, 'data_set_name': '可以使用:anl82_preq_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on delta of Q pre-tax profit'} +{'id': 86392, 'data_set_name': '可以使用:fnd72_q2_sales_to_acct_rcv', 'description': "不可使用,仅供参考:Accounts receivable turnover ratio indicates the liquidity of the company's receivables"} +{'id': 320746, 'data_set_name': '可以使用:pv87_2_sales_qf_matrix_p1_b_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Sales'} +{'id': 6809, 'data_set_name': '可以使用:anl49_backfill_cashflowpershare', 'description': '不可使用,仅供参考:Cash flow less preferred dividends (if any) divided by common shares outstanding at year end.'} +{'id': 9130, 'data_set_name': '可以使用:anl82_ebtq_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on delta of Q EBITDA'} +{'id': 10241, 'data_set_name': '可以使用:mdl211_preq_profitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on value of Q pre-tax profit'} +{'id': 6359, 'data_set_name': '可以使用:anl44_sales_prevalue', 'description': '不可使用,仅供参考:Sales d0 prevalue'} +{'id': 10145, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on delta of annual net income'} +{'id': 83229, 'data_set_name': '可以使用:fnd3_A_receivables', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Receivables'} +{'id': 10344, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on value of annual sales'} +{'id': 80563, 'data_set_name': '可以使用:interest_income_cashflow', 'description': '不可使用,仅供参考:Cash flow from interest income activities.'} +{'id': 10229, 'data_set_name': '可以使用:mdl211_preq_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of Q pre-tax profit'} +{'id': 80561, 'data_set_name': '可以使用:interest_expense_on_loans', 'description': '不可使用,仅供参考:[Quarterly] Interest Expense on Lease Liabilities, Supplemental'} +{'id': 5702, 'data_set_name': '可以使用:sales_min_guidance_value', 'description': '不可使用,仅供参考:Minimum sales guidance for the annual period.'} +{'id': 9375, 'data_set_name': '可以使用:anl82_preq_profitability_profitability7', 'description': '不可使用,仅供参考:Profitability Measure Type 7 Based on Value of Q Pre-Tax Profit'} +{'id': 6795, 'data_set_name': '可以使用:anl49_backfill_annualfiscalsalesorrevenues', 'description': '不可使用,仅供参考:The total fiscal year sales or revenues as reported.'} +{'id': 9304, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on delta of Q operating profit'} +{'id': 84014, 'data_set_name': '可以使用:quarterly_accounts_receivable_total', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Accounts receivable'} +{'id': 9998, 'data_set_name': '可以使用:mdl211_ebtq_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on delta of Q ebitda'} +{'id': 9141, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on value of Q EBITDA'} +{'id': 324462, 'data_set_name': '可以使用:pv87_qtr_matrix_interest_expense_estimate_low', 'description': '不可使用,仅供参考:Low of Interest Expense Estimate'} +{'id': 6540, 'data_set_name': '可以使用:sales_forecast_currency_code', 'description': '不可使用,仅供参考:Currency in which the sales forecast is reported.'} +{'id': 9349, 'data_set_name': '可以使用:anl82_opry_profitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on value of annual operating profit'} +{'id': 5578, 'data_set_name': '可以使用:max_investing_cashflow_guidance_2', 'description': '不可使用,仅供参考:The maximum guidance value for Cash Flow from Investing activities on an annual basis.'} +{'id': 5707, 'data_set_name': '可以使用:selling_general_admin_expense_reported_value', 'description': '不可使用,仅供参考:Selling, General & Administrative Expense value'} +{'id': 320695, 'data_set_name': '可以使用:pv87_2_sales_af_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Sales *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9315, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on value of Q operating profit'} +{'id': 10168, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of Q operating profit'} +{'id': 10107, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on delta of Q net income'} +{'id': 9994, 'data_set_name': '可以使用:mdl211_ebtq_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on delta of Q ebitda'} +{'id': 83152, 'data_set_name': '可以使用:annual_operating_cashflow_amount_fast_d1', 'description': '不可使用,仅供参考:Net cash flow from operating activities for the year.'} +{'id': 6352, 'data_set_name': '可以使用:anl44_sales_best_eeps_cur_yr', 'description': '不可使用,仅供参考:sales best eeps cur yr'} +{'id': 7644, 'data_set_name': '可以使用:anl69_sales_best_fperiod_override', 'description': '不可使用,仅供参考:Fiscal Period Override'} +{'id': 5899, 'data_set_name': '可以使用:anl44_best_ebit_to_sales', 'description': '不可使用,仅供参考:best ebit to sales'} +{'id': 9377, 'data_set_name': '可以使用:anl82_preq_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of Q pre-tax profit'} +{'id': 83156, 'data_set_name': '可以使用:annual_receivables_change_amount_fast_d1', 'description': '不可使用,仅供参考:Change in accounts receivable during the year.'} +{'id': 83555, 'data_set_name': '可以使用:fnd3_a_receivables_fast_d1', 'description': '不可使用,仅供参考:Annual Increase or Decrease in Receivables'} +{'id': 85463, 'data_set_name': '可以使用:fnd72_a2_tot_com_dvd_to_net_sales', 'description': '不可使用,仅供参考:Total common dividend as a percentage of revenue'} +{'id': 10180, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on value of Q operating profit'} +{'id': 10040, 'data_set_name': '可以使用:mdl211_ebty_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of annual ebitda'} +{'id': 10150, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on delta of annual net income'} +{'id': 85449, 'data_set_name': '可以使用:fnd72_a2_sales_to_invent', 'description': '不可使用,仅供参考:Sales to inventory ratio provides critical clues about whether the firm is keeping storage costs under control and achieving the target revenues'} +{'id': 9306, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on delta of Q operating profit'} +{'id': 6356, 'data_set_name': '可以使用:anl44_sales_coveredby', 'description': '不可使用,仅供参考:Sales d0 coveredby'} +{'id': 86823, 'data_set_name': '可以使用:fnd72_s_pit_or_cr_q_inventory_growth_to_sales_growth', 'description': '不可使用,仅供参考:Year-over-year growth in inventory as a multiple of year-over-year growth in sales'} +{'id': 9471, 'data_set_name': '可以使用:anl82_saly_profitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on value of annual sales'} +{'id': 10304, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on value of Q sales'} +{'id': 10153, 'data_set_name': '可以使用:mdl211_nety_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of annual net income'} +========================= 数据字段结束 ======================================= + +以上数据字段和操作符, 按照Description说明组合, 但是每一个 alpha 组合的使用的数据字段和操作符不要过于集中, 在符合语法的情况下, 多尝试不同的组合 + +你再检查一下, 如果你使用了 +Operator abs does not support event inputs +Operator ts_mean does not support event inputs +Operator ts_scale does not support event inputs +Operator add does not support event inputs +Operator sign does not support event inputs +Operator greater does not support event inputs +Operator ts_av_diff does not support event inputs +Operator ts_quantile does not support event inputs +Operator ts_arg_min does not support event inputs +Operator divide does not support event inputs +Operator ts_corr does not support event inputs +Operator ts_decay_linear does not support event inputs +Operator ts_sum does not support event inputs +Operator ts_delay does not support event inputs +Operator ts_arg_max does not support event inputs +Operator ts_std_dev does not support event inputs +Operator ts_regression does not support event inputs +Operator ts_backfill does not support event inputs +Operator signed_power does not support event inputs +Operator ts_product does not support event inputs +Operator ts_zscore does not support event inputs +Operator group_rank does not support event inputs +Operator subtract does not support event inputs +Operator ts_delta does not support event inputs +Operator ts_rank does not support event inputs +Operator ts_count_nans does not support event inputs +Operator ts_covariance does not support event inputs +Operator multiply does not support event inputs +Operator if_else does not support event inputs +Operator group_neutralize does not support event inputs +Operator group_zscore does not support event inputs +Operator winsorize does not support event inputs +注意, 以上操作符不能使用事件类型的数据集, 以上操作符禁止使用事件类型的数据集!! \ No newline at end of file diff --git a/manual_prompt/2026/01/22/manual_prompt_20260122174534.txt b/manual_prompt/2026/01/22/manual_prompt_20260122174534.txt new file mode 100644 index 0000000..9d5b97f --- /dev/null +++ b/manual_prompt/2026/01/22/manual_prompt_20260122174534.txt @@ -0,0 +1,812 @@ +研发资本化激进程度因子 +企业将研发支出过度资本化可短期美化利润，但该会计选择往往反映盈余管理动机，市场未能及时识别其不可持续性，导致股价高估。多空逻辑：做空研发资本化比例高且后续ROA下滑的企业，做多费用化处理、盈利稳健的企业。 +核心指标为资本化研发支出占总研发支出比重，需行业与市值双中性化；使用过去三年均值平滑异常值；引入专利引用数或新申请量作为创新真实性的验证变量。 + +*=========================================================================================* +输出格式： +输出必须是且仅是纯文本。 +每一行是一个完整、独立、语法正确的WebSim表达式。 +严禁任何形式的解释、编号、标点包裹（如引号）、Markdown格式或额外文本。 +===================== !!! 重点(输出方式) !!! ===================== +现在，请严格遵守以上所有规则，开始生成可立即在WebSim中运行的复合因子表达式。 +不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 +**输出格式**(一行一个表达式, 每个表达式中间需要添加一个空行, 只要表达式本身, 不需要赋值, 不要解释, 不需要序号, 也不要输出多余的东西)： +表达式 +表达式 +表达式 +... +表达式 +================================================================= +重申：请确保所有表达式都使用WorldQuant WebSim平台函数，不要使用pandas、numpy或其他Python库函数。输出必须是一行有效的WQ表达式。 +以下是我的账号有权限使用的操作符, 请严格按照操作符, 以及我提供的数据集, 进行生成,组合 50 个 alpha： +不要自行假设, 你需要用到的操作符 和 数据集, 必须从我提供给你的里面查找, 并严格按照里面的使用方法进行组合 +================================================================= +**操作符汇总 +**算术运算符 (Arithmetic): +abs(x) - 绝对值 +add(x, y, filter=false) - 加法 (x + y) +densify(x) - 分组字段稠密化 +divide(x, y) - 除法 (x / y) +inverse(x) - 倒数 (1/x) +log(x) - 自然对数 +max(x, y, ..) - 最大值 +min(x, y, ..) - 最小值 +multiply(x, y, filter=false) - 乘法 (x * y) +power(x, y) - 幂运算 (x^y) +reverse(x) - 取反 (-x) +sign(x) - 符号函数 +signed_power(x, y) - 保留符号的幂运算 +sqrt(x) - 平方根 +subtract(x, y, filter=false) - 减法 (x - y) +to_nan(x, value=0, reverse=false) - 值与NaN转换 +**逻辑运算符 (Logical): +and(input1, input2) - 逻辑与 +if_else(input1, input2, input3) - 条件判断 +input1 < input2 - 小于比较 +input1 <= input2 - 小于等于 +input1 == input2 - 等于比较 +input1 > input2 - 大于比较 +input1 >= input2 - 大于等于 +input1 != input2 - 不等于 +is_nan(input) - 是否为NaN +not(x) - 逻辑非 +or(input1, input2) - 逻辑或 +**时间序列运算符 (Time Series): +days_from_last_change(x) - 上次变化天数 +hump(x, hump=0.01) - 限制变化幅度 +jump_decay(x, d, sensitivity=0.5, force=0.1) - 跳跃衰减 +kth_element(x, d, k) - 第K个值 +last_diff_value(x, d) - 最后一个不同值 +ts_arg_max(x, d) - 最大值相对索引 +ts_arg_min(x, d) - 最小值相对索引 +ts_av_diff(x, d) - 与均值的差 +ts_backfill(x, lookback=d, k=1, ignore="NAN") - 回填 +ts_corr(x, y, d) - 时间序列相关性 +ts_count_nans(x, d) - NaN计数 +ts_covariance(y, x, d) - 协方差 +ts_decay_linear(x, d, dense=false) - 线性衰减 +ts_delay(x, d) - 延迟值 +ts_delta(x, d) - 差值 (x - 延迟值) +ts_max(x, d) - 时间序列最大值 +ts_mean(x, d) - 时间序列均值 +ts_min(x, d) - 时间序列最小值 +ts_product(x, d) - 时间序列乘积 +ts_quantile(x, d, driver="gaussian") - 分位数 +ts_rank(x, d, constant=0) - 时间序列排名 +ts_regression(y, x, d, lag=0, rettype=0) - 回归分析 +ts_scale(x, d, constant=0) - 时间序列缩放 +ts_std_dev(x, d) - 时间序列标准差 +ts_step(1) - 天数计数器 +ts_sum(x, d) - 时间序列求和 +ts_target_tvr_decay(x, lambda_min=0, lambda_max=1, target_tvr=0.1) - 目标换手率衰减 +ts_target_tvr_delta_limit(x, y, lambda_min=0, lambda_max=1, target_tvr=0.1) - 目标换手率差值限制 +ts_zscore(x, d) - 时间序列Z分数 +**横截面运算符 (Cross Sectional): +normalize(x, useStd=false, limit=0.0) - 标准化 +quantile(x, driver=gaussian, sigma=1.0) - 分位数转换 +rank(x, rate=2) - 排名 +scale(x, scale=1, longscale=1, shortscale=1) - 缩放 +scale_down(x, constant=0) - 按比例缩放 +vector_neut(x, y) - 向量中性化 +winsorize(x, std=4) - 缩尾处理 +zscore(x) - Z分数 +**向量运算符 (Vector): +vec_avg(x) - 向量均值 +vec_max(x) - 向量最大值 +vec_min(x) - 向量最小值 +vec_sum(x) - 向量求和 +**变换运算符 (Transformational): +bucket(rank(x), range="0,1,0.1" or buckets="2,5,6,7,10") - 分桶 +generate_stats(alpha) - 生成统计量 +trade_when(x, y, z) - 条件交易 +**分组运算符 (Group): +combo_a(alpha, nlength=250, mode='algo1') - 组合Alpha +group_backfill(x, group, d, std=4.0) - 分组回填 +group_cartesian_product(g1, g2) - 笛卡尔积分组 +group_max(x, group) - 分组最大值 +group_mean(x, weight, group) - 分组均值 +group_min(x, group) - 分组最小值 +group_neutralize(x, group) - 分组中性化 +group_rank(x, group) - 分组排名 +group_scale(x, group) - 分组缩放 +group_zscore(x, group) - 分组Z分数 +**特殊运算符 (Special): +in - 包含判断 +self_corr(input) - 自相关性 +universe_size - 宇宙大小 +**归约运算符 (Reduce): +reduce_avg(input, threshold=0) - 平均值归约 +reduce_choose(input, nth, ignoreNan=true) - 选择归约 +reduce_count(input, threshold) - 计数归约 +reduce_ir(input) - IR归约 +reduce_kurtosis(input) - 峰度归约 +reduce_max(input) - 最大值归约 +reduce_min(input) - 最小值归约 +reduce_norm(input) - 范数归约 +reduce_percentage(input, percentage=0.5) - 百分比归约 +reduce_powersum(input, constant=2, precise=false) - 幂和归约 +reduce_range(input) - 范围归约 +reduce_skewness(input) - 偏度归约 +reduce_stddev(input, threshold=0) - 标准差归约 +reduce_sum(input) - 求和归约 + +以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子 + +========================= 操作符开始 ======================================= +注意: Operator: 后面的是操作符(是可以使用的), +Description: 此字段后面的是操作符对应的描述或使用说明(禁止使用, 仅供参考), Description字段后面的内容是使用说明, 不是操作符 +特别注意!!!! 必须按照操作符字段Operator的使用说明生成 alphaOperator: abs(x) +Description: Absolute value of x +Operator: add(x, y, filter = false) +Description: Add all inputs (at least 2 inputs required). If filter = true, filter all input NaN to 0 before adding +Operator: densify(x) +Description: Converts a grouping field of many buckets into lesser number of only available buckets so as to make working with grouping fields computationally efficient +Operator: divide(x, y) +Description: x / y +Operator: inverse(x) +Description: 1 / x +Operator: log(x) +Description: Natural logarithm. For example: Log(high/low) uses natural logarithm of high/low ratio as stock weights. +Operator: max(x, y, ..) +Description: Maximum value of all inputs. At least 2 inputs are required +Operator: min(x, y ..) +Description: Minimum value of all inputs. At least 2 inputs are required +Operator: multiply(x ,y, ... , filter=false) +Description: Multiply all inputs. At least 2 inputs are required. Filter sets the NaN values to 1 +Operator: power(x, y) +Description: x ^ y +Operator: reverse(x) +Description: - x +Operator: sign(x) +Description: if input > 0, return 1; if input < 0, return -1; if input = 0, return 0; if input = NaN, return NaN; +Operator: signed_power(x, y) +Description: x raised to the power of y such that final result preserves sign of x +Operator: sqrt(x) +Description: Square root of x +Operator: subtract(x, y, filter=false) +Description: x-y. If filter = true, filter all input NaN to 0 before subtracting +Operator: and(input1, input2) +Description: Logical AND operator, returns true if both operands are true and returns false otherwise +Operator: if_else(input1, input2, input 3) +Description: If input1 is true then return input2 else return input3. +Operator: input1 < input2 +Description: If input1 < input2 return true, else return false +Operator: input1 <= input2 +Description: Returns true if input1 <= input2, return false otherwise +Operator: input1 == input2 +Description: Returns true if both inputs are same and returns false otherwise +Operator: input1 > input2 +Description: Logic comparison operators to compares two inputs +Operator: input1 >= input2 +Description: Returns true if input1 >= input2, return false otherwise +Operator: input1!= input2 +Description: Returns true if both inputs are NOT the same and returns false otherwise +Operator: is_nan(input) +Description: If (input == NaN) return 1 else return 0 +Operator: not(x) +Description: Returns the logical negation of x. If x is true (1), it returns false (0), and if input is false (0), it returns true (1). +Operator: or(input1, input2) +Description: Logical OR operator returns true if either or both inputs are true and returns false otherwise +Operator: days_from_last_change(x) +Description: Amount of days since last change of x +Operator: hump(x, hump = 0.01) +Description: Limits amount and magnitude of changes in input (thus reducing turnover) +Operator: kth_element(x, d, k) +Description: Returns K-th value of input by looking through lookback days. This operator can be used to backfill missing data if k=1 +Operator: last_diff_value(x, d) +Description: Returns last x value not equal to current x value from last d days +Operator: ts_arg_max(x, d) +Description: Returns the relative index of the max value in the time series for the past d days. If the current day has the max value for the past d days, it returns 0. If previous day has the max value for the past d days, it returns 1 +Operator: ts_arg_min(x, d) +Description: Returns the relative index of the min value in the time series for the past d days; If the current day has the min value for the past d days, it returns 0; If previous day has the min value for the past d days, it returns 1. +Operator: ts_av_diff(x, d) +Description: Returns x - tsmean(x, d), but deals with NaNs carefully. That is NaNs are ignored during mean computation +Operator: ts_backfill(x,lookback = d, k=1, ignore="NAN") +Description: Backfill is the process of replacing the NAN or 0 values by a meaningful value (i.e., a first non-NaN value) +Operator: ts_corr(x, y, d) +Description: Returns correlation of x and y for the past d days +Operator: ts_count_nans(x ,d) +Description: Returns the number of NaN values in x for the past d days +Operator: ts_covariance(y, x, d) +Description: Returns covariance of y and x for the past d days +Operator: ts_decay_linear(x, d, dense = false) +Description: Returns the linear decay on x for the past d days. Dense parameter=false means operator works in sparse mode and we treat NaN as 0. In dense mode we do not. +Operator: ts_delay(x, d) +Description: Returns x value d days ago +Operator: ts_delta(x, d) +Description: Returns x - ts_delay(x, d) +Operator: ts_mean(x, d) +Description: Returns average value of x for the past d days. +Operator: ts_product(x, d) +Description: Returns product of x for the past d days +Operator: ts_quantile(x,d, driver="gaussian" ) +Description: It calculates ts_rank and apply to its value an inverse cumulative density function from driver distribution. Possible values of driver (optional ) are "gaussian", "uniform", "cauchy" distribution where "gaussian" is the default. +Operator: ts_rank(x, d, constant = 0) +Description: Rank the values of x for each instrument over the past d days, then return the rank of the current value + constant. If not specified, by default, constant = 0. +Operator: ts_regression(y, x, d, lag = 0, rettype = 0) +Description: Returns various parameters related to regression function +Operator: ts_scale(x, d, constant = 0) +Description: Returns (x - ts_min(x, d)) / (ts_max(x, d) - ts_min(x, d)) + constant. This operator is similar to scale down operator but acts in time series space +Operator: ts_std_dev(x, d) +Description: Returns standard deviation of x for the past d days +Operator: ts_step(1) +Description: Returns days' counter +Operator: ts_sum(x, d) +Description: Sum values of x for the past d days. +Operator: ts_zscore(x, d) +Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean: (x - tsmean(x,d)) / tsstddev(x,d). This operator may help reduce outliers and drawdown. +Operator: normalize(x, useStd = false, limit = 0.0) +Description: Calculates the mean value of all valid alpha values for a certain date, then subtracts that mean from each element +Operator: quantile(x, driver = gaussian, sigma = 1.0) +Description: Rank the raw vector, shift the ranked Alpha vector, apply distribution (gaussian, cauchy, uniform). If driver is uniform, it simply subtract each Alpha value with the mean of all Alpha values in the Alpha vector +Operator: rank(x, rate=2) +Description: Ranks the input among all the instruments and returns an equally distributed number between 0.0 and 1.0. For precise sort, use the rate as 0 +Operator: scale(x, scale=1, longscale=1, shortscale=1) +Description: Scales input to booksize. We can also scale the long positions and short positions to separate scales by mentioning additional parameters to the operator +Operator: winsorize(x, std=4) +Description: Winsorizes x to make sure that all values in x are between the lower and upper limits, which are specified as multiple of std. +Operator: zscore(x) +Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean +Operator: vec_avg(x) +Description: Taking mean of the vector field x +Operator: vec_sum(x) +Description: Sum of vector field x +Operator: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10") +Description: Convert float values into indexes for user-specified buckets. Bucket is useful for creating group values, which can be passed to GROUP as input +Operator: trade_when(x, y, z) +Description: Used in order to change Alpha values only under a specified condition and to hold Alpha values in other cases. It also allows to close Alpha positions (assign NaN values) under a specified condition +Operator: group_backfill(x, group, d, std = 4.0) +Description: If a certain value for a certain date and instrument is NaN, from the set of same group instruments, calculate winsorized mean of all non-NaN values over last d days +Operator: group_mean(x, weight, group) +Description: All elements in group equals to the mean +Operator: group_neutralize(x, group) +Description: Neutralizes Alpha against groups. These groups can be subindustry, industry, sector, country or a constant +Operator: group_rank(x, group) +Description: Each elements in a group is assigned the corresponding rank in this group +Operator: group_scale(x, group) +Description: Normalizes the values in a group to be between 0 and 1. (x - groupmin) / (groupmax - groupmin) +Operator: group_zscore(x, group) +Description: Calculates group Z-score - numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. zscore = (data - mean) / stddev of x for each instrument within its group. +========================= 操作符结束 ======================================= + +========================= 数据字段开始 ======================================= +注意: data_set_name: 后面的是数据字段(可以使用), description: 此字段后面的是数据字段对应的描述或使用说明(不能使用) + +{'id': 9368, 'data_set_name': '可以使用:anl82_preq_profitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on value of Q pre-tax profit'} +{'id': 10052, 'data_set_name': '可以使用:mdl211_ebty_profitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on value of annual ebitda'} +{'id': 864, 'data_set_name': '可以使用:anl10_prrinnovation_score_fy1_2565', 'description': '不可使用,仅供参考:Innovation score for price return ratio FY1 (innovate_increase - innovate_decrease)'} +{'id': 79308, 'data_set_name': '可以使用:bad_debt_expense', 'description': '不可使用,仅供参考:Expense recognized for uncollectible accounts receivable.'} +{'id': 9470, 'data_set_name': '可以使用:anl82_saly_profitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on value of annual sales'} +{'id': 320393, 'data_set_name': '可以使用:pv87_2_netprofit_rep_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 6207, 'data_set_name': '可以使用:anl44_netprofit_rep_best_fiscal_period_dt', 'description': '不可使用,仅供参考:netprofit rep best fiscal period dt'} +{'id': 9427, 'data_set_name': '可以使用:anl82_salq_profitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on value of Q sales'} +{'id': 84073, 'data_set_name': '可以使用:quarterly_gross_profit_total_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Gross Profit'} +{'id': 320558, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_p1_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Pretax Profit'} +{'id': 10292, 'data_set_name': '可以使用:mdl211_salq_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on delta of Q sales'} +{'id': 320579, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_p1_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Pretax Profit'} +{'id': 320333, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9333, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on delta of annual operating profit'} +{'id': 6850, 'data_set_name': '可以使用:anl49_backfill_netprofit', 'description': '不可使用,仅供参考:Profit after deduction of all expenses including taxes, minority interests and special charges against (or credits to) operations, but before deduction of preferred dividends paid and accumulated and before any extraordinary gains or losses.'} +{'id': 320380, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_p1_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Net Profit'} +{'id': 10340, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on value of annual sales'} +{'id': 6300, 'data_set_name': '可以使用:anl44_pretaxprofit_rep_coveredby', 'description': '不可使用,仅供参考:Pretaxprofit rep D0 coveredby'} +{'id': 10293, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on value of Q sales'} +{'id': 320433, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_b_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320554, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_p1_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 324463, 'data_set_name': '可以使用:pv87_qtr_matrix_interest_expense_estimate_mean', 'description': '不可使用,仅供参考:Mean of Interest Expense Estimate'} +{'id': 320546, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_all_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Pretax Profit'} +{'id': 320424, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_p1_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Net Profit'} +{'id': 10045, 'data_set_name': '可以使用:mdl211_ebty_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of annual ebitda'} +{'id': 320584, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_p1_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Pretax Profit'} +{'id': 10335, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of annual sales'} +{'id': 5704, 'data_set_name': '可以使用:selling_general_admin_expense', 'description': '不可使用,仅供参考:Selling, General & Administrative Expense Value'} +{'id': 320454, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10219, 'data_set_name': '可以使用:mdl211_opry_profitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on value of annual operating profit'} +{'id': 324466, 'data_set_name': '可以使用:pv87_qtr_matrix_interest_expense_estimate_scale', 'description': '不可使用,仅供参考:Scale of Interest Expense Estimate'} +{'id': 10154, 'data_set_name': '可以使用:mdl211_nety_profitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on value of annual net income'} +{'id': 320408, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 6221, 'data_set_name': '可以使用:anl44_operatingprofit_best_fiscal_period_dt', 'description': '不可使用,仅供参考:operatingprofit best fiscal period dt'} +{'id': 6853, 'data_set_name': '可以使用:anl49_backfill_netprofitmarginindicator', 'description': '不可使用,仅供参考:Net profit margin indicator'} +{'id': 5655, 'data_set_name': '可以使用:net_profit_adjusted_min_guidance', 'description': '不可使用,仅供参考:The minimum guidance value for adjusted net profit on an annual basis.'} +{'id': 78998, 'data_set_name': '可以使用:fn_def_income_tax_expense_q', 'description': '不可使用,仅供参考:Income Tax Expense, Deferred'} +{'id': 10269, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of annual pre-tax profit'} +{'id': 10298, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on value of Q sales'} +{'id': 10147, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on delta of annual net income'} +{'id': 87529, 'data_set_name': '可以使用:fnd90_game_prepaid_expense', 'description': '不可使用,仅供参考:Prepaid Expense to Sales'} +{'id': 320576, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 83677, 'data_set_name': '可以使用:fnd3_aacctadj_opeexpenses_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Total Operating Expenses'} +{'id': 86156, 'data_set_name': '可以使用:fnd72_pit_or_is_a_is_expense_stock_based_comp', 'description': '不可使用,仅供参考:The expense for stock-based compensation'} +{'id': 320337, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 83508, 'data_set_name': '可以使用:fnd3_a_grossprofit', 'description': '不可使用,仅供参考:Annual Gross Profit'} +{'id': 9174, 'data_set_name': '可以使用:anl82_ebty_profitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on value of annual EBITDA'} +{'id': 10276, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on delta of annual pre-tax profit'} +{'id': 320434, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_b_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10037, 'data_set_name': '可以使用:mdl211_ebty_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on delta of annual ebitda'} +{'id': 10139, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on delta of annual net income'} +{'id': 320367, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_all_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Net Profit'} +{'id': 9402, 'data_set_name': '可以使用:anl82_prey_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on delta of annual pre-tax profit'} +{'id': 9229, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:Profitability measure type 10 based on delta of Q net income'} +{'id': 6936, 'data_set_name': '可以使用:anl49_netprofit', 'description': '不可使用,仅供参考:Profit after deduction of all expenses including taxes, minority interests and special charges against (or credits to) operations, but before deduction of preferred dividends paid and accumulated and before any extraordinary gains or losses.'} +{'id': 5824, 'data_set_name': '可以使用:anl44_2_operatingprofit_lastactvalue', 'description': '不可使用,仅供参考:operatingprofit lastactvalue'} +{'id': 6200, 'data_set_name': '可以使用:anl44_netprofit_prevalue', 'description': '不可使用,仅供参考:Netprofit d0 prevalue'} +{'id': 9336, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on delta of annual operating profit'} +{'id': 6291, 'data_set_name': '可以使用:anl44_pretaxprofit_best_cur_fiscal_year_period', 'description': '不可使用,仅供参考:pretaxprofit best cur fiscal year period'} +{'id': 320510, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_p1_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Pretax Profit'} +{'id': 320445, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 84134, 'data_set_name': '可以使用:r_and_d_expense_balance', 'description': '不可使用,仅供参考:Amount spent on research and development activities.'} +{'id': 9397, 'data_set_name': '可以使用:anl82_prey_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on delta of annual pre-tax profit'} +{'id': 6296, 'data_set_name': '可以使用:anl44_pretaxprofit_coveredby', 'description': '不可使用,仅供参考:Pretaxprofit d0 coveredby'} +{'id': 9328, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on delta of annual operating profit'} +{'id': 6262, 'data_set_name': '可以使用:anl44_orig_en_netprofit_prevalue', 'description': '不可使用,仅供参考:orig en netprofit prevalue'} +{'id': 9232, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on delta of Q net income'} +{'id': 6420, 'data_set_name': '可以使用:anl44_second_en_operatingprofit_prevalue', 'description': '不可使用,仅供参考:operatingprofit prevalue'} +{'id': 320412, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_all_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Net Profit'} +{'id': 10009, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on value of Q ebitda'} +{'id': 9132, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on value of Q EBITDA'} +{'id': 80686, 'data_set_name': '可以使用:prepaid_expenses_value', 'description': '不可使用,仅供参考:[Quarterly] Funded Status - Domestic'} +{'id': 320449, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Operating Profit'} +{'id': 6749, 'data_set_name': '可以使用:anl49_alldividendstonetprofit', 'description': '不可使用,仅供参考:The sum of all cash dividends (common and preferred) declared for the calendar or fiscal year expressed as a percentage of the net income for the year'} +{'id': 10006, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on value of Q ebitda'} +{'id': 320474, 'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_all_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Operating Profit'} +{'id': 320522, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_all_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Pretax Profit'} +{'id': 9421, 'data_set_name': '可以使用:anl82_salq_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on delta of Q sales'} +{'id': 10013, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on value of Q ebitda'} +{'id': 10288, 'data_set_name': '可以使用:mdl211_salq_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on delta of Q sales'} +{'id': 320482, 'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_p1_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9337, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on delta of annual operating profit'} +{'id': 9300, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on delta of Q operating profit'} +{'id': 9370, 'data_set_name': '可以使用:anl82_preq_profitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on value of Q pre-tax profit'} +{'id': 86172, 'data_set_name': '可以使用:fnd72_pit_or_is_a_is_oprb_expense_income', 'description': '不可使用,仅供参考:Net amount of other post-employment benefits cost that is recognized in the income statement'} +{'id': 6944, 'data_set_name': '可以使用:anl49_operatingexpenseratioindicator', 'description': '不可使用,仅供参考:Operating expense ratio indicator'} +{'id': 5818, 'data_set_name': '可以使用:anl44_2_netprofit_rep_prevalue', 'description': '不可使用,仅供参考:netprofit rep prevalue'} +{'id': 320352, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_p1_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Net Profit'} +{'id': 320496, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_all_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Pretax Profit'} +{'id': 9271, 'data_set_name': '可以使用:anl82_nety_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on delta of annual net income'} +{'id': 322101, 'data_set_name': '可以使用:pv87_interest_expense_actual', 'description': '不可使用,仅供参考:Interest Expense Actual'} +{'id': 10148, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of annual net income'} +{'id': 6423, 'data_set_name': '可以使用:anl44_second_en_pretaxprofit_lastactccy', 'description': '不可使用,仅供参考:pretaxprofit lastactccy'} +{'id': 10122, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on value of Q net income'} +{'id': 6201, 'data_set_name': '可以使用:anl44_netprofit_rep_best_crncy_iso', 'description': '不可使用,仅供参考:netprofit rep best crncy iso'} +{'id': 87545, 'data_set_name': '可以使用:fnd90_qes_gamef_grossprofit_asset', 'description': '不可使用,仅供参考:Gross Profit Over Asset'} +{'id': 320533, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_p1_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Pretax Profit'} +{'id': 10157, 'data_set_name': '可以使用:mdl211_nety_profitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on value of annual net income'} +{'id': 6298, 'data_set_name': '可以使用:anl44_pretaxprofit_most_recent_period_end_dt', 'description': '不可使用,仅供参考:pretaxprofit most recent period end dt'} +{'id': 6413, 'data_set_name': '可以使用:anl44_second_en_netprofit_rep_coveredby', 'description': '不可使用,仅供参考:netprofit rep coveredby'} +{'id': 9121, 'data_set_name': '可以使用:anl82_ebtq_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:Profitability measure type 10 based on delta of Q EBITDA'} +{'id': 10213, 'data_set_name': '可以使用:mdl211_opry_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of annual operating profit'} +{'id': 10220, 'data_set_name': '可以使用:mdl211_opry_profitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on value of annual operating profit'} +{'id': 10171, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of Q operating profit'} +{'id': 86243, 'data_set_name': '可以使用:fnd72_pit_or_is_q_is_pension_expense_income', 'description': '不可使用,仅供参考:The net amount of pension cost that is recognized in the income statement'} +{'id': 320525, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9454, 'data_set_name': '可以使用:anl82_saly_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on delta of annual sales'} +{'id': 10111, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on value of Q net income'} +{'id': 10109, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on delta of Q net income'} +{'id': 320430, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_b_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9458, 'data_set_name': '可以使用:anl82_saly_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on delta of annual sales'} +{'id': 9129, 'data_set_name': '可以使用:anl82_ebtq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on delta of Q EBITDA'} +{'id': 10121, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on value of Q net income'} +{'id': 83828, 'data_set_name': '可以使用:fnd3_q_sgaexpense', 'description': '不可使用,仅供参考:Quarterly Selling, General & Administrative Expense'} +{'id': 10273, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on delta of annual pre-tax profit'} +{'id': 320471, 'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_all_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Operating Profit'} +{'id': 9419, 'data_set_name': '可以使用:anl82_salq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on delta of Q sales'} +{'id': 10283, 'data_set_name': '可以使用:mdl211_salq_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on delta of Q sales'} +{'id': 5813, 'data_set_name': '可以使用:anl44_2_netprofit_lastactvalue', 'description': '不可使用,仅供参考:netprofit lastactvalue'} +{'id': 10176, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of Q operating profit'} +{'id': 6430, 'data_set_name': '可以使用:anl44_second_en_pretaxprofit_value', 'description': '不可使用,仅供参考:pretaxprofit value'} +{'id': 320382, 'data_set_name': '可以使用:pv87_2_netprofit_rep_af_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9431, 'data_set_name': '可以使用:anl82_salq_profitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on value of Q sales'} +{'id': 320483, 'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_p1_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Operating Profit'} +{'id': 320353, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_p1_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Net Profit'} +{'id': 9357, 'data_set_name': '可以使用:anl82_preq_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on delta of Q pre-tax profit'} +{'id': 320550, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 352, 'data_set_name': '可以使用:anl10_ebtinnovation_score_fy2_1040', 'description': '不可使用,仅供参考:Innovation score for earnings before tax FY2 (innovate_increase - innovate_decrease)'} +{'id': 5831, 'data_set_name': '可以使用:anl44_2_pretaxprofit_rep_coveredby', 'description': '不可使用,仅供参考:pretaxprofit rep coveredby'} +{'id': 10141, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on delta of annual net income'} +{'id': 85959, 'data_set_name': '可以使用:fnd72_pit_or_cr_q_cash_flow_to_int_expense', 'description': '不可使用,仅供参考:Measures the ratio of cash flow from operations to total interest incurred during the period'} +{'id': 322112, 'data_set_name': '可以使用:pv87_interest_expense_of_estimates_scale', 'description': '不可使用,仅供参考:Scale of Interest Expense - # of Estimates'} +{'id': 320573, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320524, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_all_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Pretax Profit'} +{'id': 5833, 'data_set_name': '可以使用:anl44_2_pretaxprofit_rep_lastactvalue', 'description': '不可使用,仅供参考:pretaxprofit rep lastactvalue'} +{'id': 10114, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on value of Q net income'} +{'id': 9361, 'data_set_name': '可以使用:anl82_preq_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on delta of Q pre-tax profit'} +{'id': 83223, 'data_set_name': '可以使用:fnd3_A_opeexpenseexitems', 'description': '不可使用,仅供参考:Annual Operating Expense Extraordinary Items'} +{'id': 6269, 'data_set_name': '可以使用:anl44_orig_en_operatingprofit_value', 'description': '不可使用,仅供参考:orig en operatingprofit value'} +{'id': 10188, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on value of Q operating profit'} +{'id': 10234, 'data_set_name': '可以使用:mdl211_preq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of Q pre-tax profit'} +{'id': 320479, 'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 79084, 'data_set_name': '可以使用:fn_prepaid_expense_a', 'description': '不可使用,仅供参考:Carrying amount for an unclassified balance sheet date of expenditures made in advance of when the economic benefit of the cost will be realized, and which will be expensed in future periods with the passage of time or when a triggering event occurs. For a classified balance sheet, represents the noncurrent portion of prepaid expenses (the current portion has a separate concept).'} +{'id': 9993, 'data_set_name': '可以使用:mdl211_ebtq_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on delta of Q ebitda'} +{'id': 10202, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on delta of annual operating profit'} +{'id': 10206, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on delta of annual operating profit'} +{'id': 320417, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 5356, 'data_set_name': '可以使用:anl4_netprofita_mean', 'description': '不可使用,仅供参考:Adjusted net income - mean of estimations'} +{'id': 9296, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on delta of Q operating profit'} +{'id': 9461, 'data_set_name': '可以使用:anl82_saly_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on delta of annual sales'} +{'id': 5640, 'data_set_name': '可以使用:min_stock_option_expense_guidance', 'description': '不可使用,仅供参考:Stock option expense - minimum guidance value'} +{'id': 320400, 'data_set_name': '可以使用:pv87_2_netprofit_rep_af_matrix_p1_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Net Profit'} +{'id': 320349, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320535, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_p1_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Pretax Profit'} +{'id': 9168, 'data_set_name': '可以使用:anl82_ebty_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on delta of annual EBITDA'} +{'id': 87594, 'data_set_name': '可以使用:fnd90_us_game_prepaid_expense', 'description': '不可使用,仅供参考:Prepaid Expense to Sales [ Descending] - [Quality.Aggressive Accounting]'} +{'id': 320459, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_p1_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Operating Profit'} +{'id': 10101, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on delta of Q net income'} +{'id': 320577, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 88086, 'data_set_name': '可以使用:oth401_game_prepaid_expense', 'description': '不可使用,仅供参考:Prepaid Expense to Sales'} +{'id': 10035, 'data_set_name': '可以使用:mdl211_ebty_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of annual ebitda'} +{'id': 320543, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_all_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Pretax Profit'} +{'id': 320358, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 83545, 'data_set_name': '可以使用:fnd3_a_opeexpenses_fast_d1', 'description': '不可使用,仅供参考:Annual Total Operating Expenses'} +{'id': 80650, 'data_set_name': '可以使用:operating_profit_3', 'description': '不可使用,仅供参考:Profit from core business operations before interest and taxes.'} +{'id': 5836, 'data_set_name': '可以使用:anl44_2_pretaxprofit_value', 'description': '不可使用,仅供参考:pretaxprofit value'} +{'id': 9170, 'data_set_name': '可以使用:anl82_ebty_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on delta of annual EBITDA'} +{'id': 9179, 'data_set_name': '可以使用:anl82_ebty_profitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on value of annual EBITDA'} +{'id': 10105, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on delta of Q net income'} +{'id': 320507, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_p1_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Pretax Profit'} +{'id': 5359, 'data_set_name': '可以使用:anl4_netprofita_std', 'description': '不可使用,仅供参考:Adjusted net income - std of estimations'} +{'id': 83422, 'data_set_name': '可以使用:fnd3_Qacctadj_opeexpenseexitems', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Operating Expense Extraordinary Items'} +{'id': 10100, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of Q net income'} +{'id': 322105, 'data_set_name': '可以使用:pv87_interest_expense_consensus_low', 'description': '不可使用,仅供参考:Interest Expense Consensus Low'} +{'id': 719, 'data_set_name': '可以使用:anl10_netinnovation_score_fq2_2539', 'description': '不可使用,仅供参考:Innovation score for net income Q2 (innovate_increase - innovate_decrease)'} +{'id': 6199, 'data_set_name': '可以使用:anl44_netprofit_gaap_most_recent_period_end_dt', 'description': '不可使用,仅供参考:netprofit gaap most recent period end dt'} +{'id': 80850, 'data_set_name': '可以使用:total_rental_expense', 'description': '不可使用,仅供参考:Total rental expenses incurred during the period.'} +{'id': 10010, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on value of Q ebitda'} +{'id': 320439, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_b_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Operating Profit'} +{'id': 320494, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_all_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9290, 'data_set_name': '可以使用:anl82_nety_profitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on value of annual net income'} +{'id': 9456, 'data_set_name': '可以使用:anl82_saly_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on delta of annual sales'} +{'id': 9162, 'data_set_name': '可以使用:anl82_ebty_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on delta of annual EBITDA'} +{'id': 87006, 'data_set_name': '可以使用:fnd72_s_pit_or_is_q_is_expense_stock_based_comp', 'description': '不可使用,仅供参考:The expense for stock-based compensation'} +{'id': 322103, 'data_set_name': '可以使用:pv87_interest_expense_consensus_high', 'description': '不可使用,仅供参考:Interest Expense Consensus High'} +{'id': 10229, 'data_set_name': '可以使用:mdl211_preq_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of Q pre-tax profit'} +{'id': 10203, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of annual operating profit'} +{'id': 9133, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability10', 'description': '不可使用,仅供参考:Profitability measure type 10 based on value of Q EBITDA'} +{'id': 83780, 'data_set_name': '可以使用:fnd3_q_grossprofit', 'description': '不可使用,仅供参考:Quarterly Gross Profit'} +{'id': 9429, 'data_set_name': '可以使用:anl82_salq_profitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on value of Q sales'} +{'id': 10246, 'data_set_name': '可以使用:mdl211_preq_profitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on value of Q pre-tax profit'} +{'id': 320405, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10053, 'data_set_name': '可以使用:mdl211_ebty_profitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on value of annual ebitda'} +{'id': 6294, 'data_set_name': '可以使用:anl44_pretaxprofit_best_fiscal_period_dt', 'description': '不可使用,仅供参考:pretaxprofit best fiscal period dt'} +{'id': 10049, 'data_set_name': '可以使用:mdl211_ebty_profitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on value of annual ebitda'} +{'id': 9404, 'data_set_name': '可以使用:anl82_prey_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on delta of annual pre-tax profit'} +{'id': 6484, 'data_set_name': '可以使用:forecast_currency_netprofit', 'description': '不可使用,仅供参考:Currency in which the net profit forecast is denominated.'} +{'id': 9399, 'data_set_name': '可以使用:anl82_prey_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on delta of annual pre-tax profit'} +{'id': 83940, 'data_set_name': '可以使用:fnd3_qacctadj_opeexpenses', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Total Operating Expenses'} +{'id': 9400, 'data_set_name': '可以使用:anl82_prey_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on delta of annual pre-tax profit'} +{'id': 83813, 'data_set_name': '可以使用:fnd3_q_opeexpenses_fast_d1', 'description': '不可使用,仅供参考:Quarterly Total Operating Expenses'} +{'id': 5812, 'data_set_name': '可以使用:anl44_2_netprofit_lastactccy', 'description': '不可使用,仅供参考:netprofit lastactccy'} +{'id': 10181, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of Q operating profit'} +{'id': 320501, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 80679, 'data_set_name': '可以使用:other_unusual_income_expense', 'description': '不可使用,仅供参考:Other unusual income or expense items not classified elsewhere.'} +{'id': 9291, 'data_set_name': '可以使用:anl82_nety_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of annual net income'} +{'id': 320422, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_p1_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9996, 'data_set_name': '可以使用:mdl211_ebtq_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on delta of Q ebitda'} +{'id': 320559, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_p1_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Pretax Profit'} +{'id': 9335, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on delta of annual operating profit'} +{'id': 9233, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on delta of Q net income'} +{'id': 5350, 'data_set_name': '可以使用:anl4_netprofit_median', 'description': '不可使用,仅供参考:Net profit - Median of estimations'} +{'id': 9122, 'data_set_name': '可以使用:anl82_ebtq_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on delta of Q EBITDA'} +{'id': 320464, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_p1_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Operating Profit'} +{'id': 83410, 'data_set_name': '可以使用:fnd3_Qacctadj_grossprofit', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Gross Profit'} +{'id': 83544, 'data_set_name': '可以使用:fnd3_a_opeexpenses', 'description': '不可使用,仅供参考:Annual Total Operating Expenses'} +{'id': 6422, 'data_set_name': '可以使用:anl44_second_en_pretaxprofit_coveredby', 'description': '不可使用,仅供参考:pretaxprofit coveredby'} +{'id': 320511, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_p1_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Pretax Profit'} +{'id': 10156, 'data_set_name': '可以使用:mdl211_nety_profitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on value of annual net income'} +{'id': 5817, 'data_set_name': '可以使用:anl44_2_netprofit_rep_lastactvalue', 'description': '不可使用,仅供参考:netprofit rep lastactvalue'} +{'id': 83941, 'data_set_name': '可以使用:fnd3_qacctadj_opeexpenses_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Total Operating Expenses'} +{'id': 10167, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on delta of Q operating profit'} +{'id': 80546, 'data_set_name': '可以使用:gross_profit_total', 'description': '不可使用,仅供参考:Total gross profit for the period.'} +{'id': 10337, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on value of annual sales'} +{'id': 6214, 'data_set_name': '可以使用:anl44_netprofit_value', 'description': '不可使用,仅供参考:Netprofit d0 value'} +{'id': 10339, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on value of annual sales'} +{'id': 10103, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of Q net income'} +{'id': 320455, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 5584, 'data_set_name': '可以使用:max_pretax_profit_guidance', 'description': '不可使用,仅供参考:The maximum guidance value for Pretax income on an annual basis.'} +{'id': 79346, 'data_set_name': '可以使用:depreciation_and_amortization_expense', 'description': '不可使用,仅供参考:[Quarterly] Deferred Tax - Local'} +{'id': 83915, 'data_set_name': '可以使用:fnd3_qacctadj_grossprofit_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Gross Profit'} +{'id': 320583, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_p1_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Pretax Profit'} +{'id': 320563, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9433, 'data_set_name': '可以使用:anl82_salq_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of Q sales'} +{'id': 152, 'data_set_name': '可以使用:anl10_dpsinnovation_score_fy1_1554', 'description': '不可使用,仅供参考:Innovation score for dividends per share FY1 (innovate_increase - innovate_decrease)'} +{'id': 9416, 'data_set_name': '可以使用:anl82_salq_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on delta of Q sales'} +{'id': 5656, 'data_set_name': '可以使用:net_profit_adjusted_value', 'description': '不可使用,仅供参考:Adjusted net income- announced financial value'} +{'id': 9310, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on value of Q operating profit'} +{'id': 320526, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320557, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_p1_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Pretax Profit'} +{'id': 6426, 'data_set_name': '可以使用:anl44_second_en_pretaxprofit_rep_coveredby', 'description': '不可使用,仅供参考:pretaxprofit rep coveredby'} +{'id': 9369, 'data_set_name': '可以使用:anl82_preq_profitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on value of Q pre-tax profit'} +{'id': 5821, 'data_set_name': '可以使用:anl44_2_netprofit_value', 'description': '不可使用,仅供参考:netprofit value'} +{'id': 320334, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 84075, 'data_set_name': '可以使用:quarterly_income_tax_expense_fast_d1', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Income Tax Provision'} +{'id': 86164, 'data_set_name': '可以使用:fnd72_pit_or_is_a_is_int_expense', 'description': '不可使用,仅供参考:Interest Expense'} +{'id': 320421, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 83509, 'data_set_name': '可以使用:fnd3_a_grossprofit_fast_d1', 'description': '不可使用,仅供参考:Annual Gross Profit'} +{'id': 9304, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on delta of Q operating profit'} +{'id': 10267, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on delta of annual pre-tax profit'} +{'id': 80734, 'data_set_name': '可以使用:share_capital_expense', 'description': '不可使用,仅供参考:Expenses related to share capital issuance or management.'} +{'id': 78928, 'data_set_name': '可以使用:fn_allocated_share_based_compensation_expense_q', 'description': '不可使用,仅供参考:Represents the expense recognized during the period arising from equity-based compensation arrangements (for example, shares of stock, units, stock options, or other equity instruments) with employees, directors, and certain consultants qualifying for treatment as employees.'} +{'id': 320945, 'data_set_name': '可以使用:pv87_ann_matrix_interest_expense_estimate_std', 'description': '不可使用,仅供参考:Standard deviation of Interest Expense Estimate'} +{'id': 83130, 'data_set_name': '可以使用:annual_equity_compensation_expense_fast_d1', 'description': '不可使用,仅供参考:Expense from share-based compensation for the year.'} +{'id': 320521, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_all_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Pretax Profit'} +{'id': 320488, 'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_p1_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Operating Profit'} +{'id': 10143, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of annual net income'} +{'id': 10179, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on value of Q operating profit'} +{'id': 9351, 'data_set_name': '可以使用:anl82_opry_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of annual operating profit'} +{'id': 319323, 'data_set_name': '可以使用:pv64_dif_stal_fund_expense_ratio', 'description': '不可使用,仅供参考:The amount investors pay for expenses incurred in operating a mutual fund (after any waivers).'} +{'id': 80651, 'data_set_name': '可以使用:operating_profit_pre_tax', 'description': '不可使用,仅供参考:Profit from operations before deducting income taxes.'} +{'id': 87020, 'data_set_name': '可以使用:fnd72_s_pit_or_is_q_is_pension_expense_income', 'description': '不可使用,仅供参考:The net amount of pension cost that is recognized in the income statement'} +{'id': 10286, 'data_set_name': '可以使用:mdl211_salq_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on delta of Q sales'} +{'id': 10325, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on delta of annual sales'} +{'id': 320567, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_all_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Pretax Profit'} +{'id': 10168, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of Q operating profit'} +{'id': 83958, 'data_set_name': '可以使用:fnd3_qacctadj_sgaexpense', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Selling, General & Administrative Expense'} +{'id': 320423, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_p1_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Net Profit'} +{'id': 6216, 'data_set_name': '可以使用:anl44_operatingprofit_best_cur_fiscal_qtr_period', 'description': '不可使用,仅供参考:operatingprofit best cur fiscal qtr period'} +{'id': 5811, 'data_set_name': '可以使用:anl44_2_netprofit_coveredby', 'description': '不可使用,仅供参考:netprofit coveredby'} +{'id': 10032, 'data_set_name': '可以使用:mdl211_ebty_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of annual ebitda'} +{'id': 10239, 'data_set_name': '可以使用:mdl211_preq_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of Q pre-tax profit'} +{'id': 6266, 'data_set_name': '可以使用:anl44_orig_en_netprofit_value', 'description': '不可使用,仅供参考:orig en netprofit value'} +{'id': 320364, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_all_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Net Profit'} +{'id': 10108, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of Q net income'} +{'id': 320514, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10113, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability11', 'description': '不可使用,仅供参考:profitability measure type 11 based on value of Q net income'} +{'id': 320460, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_p1_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Operating Profit'} +{'id': 86450, 'data_set_name': '可以使用:fnd72_s_pit_or_bs_a2_bs_curr_rental_expense', 'description': '不可使用,仅供参考:Operating lease expenses recognized in the income statement for the period'} +{'id': 5351, 'data_set_name': '可以使用:anl4_netprofit_number', 'description': '不可使用,仅供参考:Net profit - number of estimations'} +{'id': 6852, 'data_set_name': '可以使用:anl49_backfill_netprofitmargin', 'description': '不可使用,仅供参考:Net income before extraordinary gains or losses expressed as a percentage of sales or revenues.'} +{'id': 320582, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_p1_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Pretax Profit'} +{'id': 320338, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_all_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9450, 'data_set_name': '可以使用:anl82_saly_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on delta of annual sales'} +{'id': 10146, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on delta of annual net income'} +{'id': 320473, 'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_all_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Operating Profit'} +{'id': 5828, 'data_set_name': '可以使用:anl44_2_pretaxprofit_lastactccy', 'description': '不可使用,仅供参考:pretaxprofit lastactccy'} +{'id': 320339, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_all_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Net Profit'} +{'id': 5659, 'data_set_name': '可以使用:operating_profit_before_depr_amort', 'description': '不可使用,仅供参考:EBITDA value - Annual'} +{'id': 6297, 'data_set_name': '可以使用:anl44_pretaxprofit_latest_ann_dt_qtrly', 'description': '不可使用,仅供参考:pretaxprofit latest ann dt qtrly'} +{'id': 9377, 'data_set_name': '可以使用:anl82_preq_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of Q pre-tax profit'} +{'id': 10182, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on value of Q operating profit'} +{'id': 10177, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on delta of Q operating profit'} +{'id': 222, 'data_set_name': '可以使用:anl10_ebiinnovation_score_fq2_2599', 'description': '不可使用,仅供参考:Innovation score for earnings before interest Q2 (innovate_increase - innovate_decrease)'} +{'id': 9457, 'data_set_name': '可以使用:anl82_saly_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on delta of annual sales'} +{'id': 320493, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320387, 'data_set_name': '可以使用:pv87_2_netprofit_rep_af_matrix_all_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Net Profit'} +{'id': 320450, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Operating Profit'} +{'id': 10008, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on value of Q ebitda'} +{'id': 9274, 'data_set_name': '可以使用:anl82_nety_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on delta of annual net income'} +{'id': 320556, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_p1_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Pretax Profit'} +{'id': 86922, 'data_set_name': '可以使用:fnd72_s_pit_or_is_a2_is_oprb_expense_income', 'description': '不可使用,仅供参考:Net amount of other post-employment benefits cost that is recognized in the income statement'} +{'id': 10040, 'data_set_name': '可以使用:mdl211_ebty_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of annual ebitda'} +{'id': 9376, 'data_set_name': '可以使用:anl82_preq_profitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on value of Q pre-tax profit'} +{'id': 10054, 'data_set_name': '可以使用:mdl211_ebty_profitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on value of annual ebitda'} +{'id': 85151, 'data_set_name': '可以使用:interest_expense', 'description': '不可使用,仅供参考:Interest and Related Expense - Total'} +{'id': 5594, 'data_set_name': '可以使用:max_stock_option_expense_guidance', 'description': '不可使用,仅供参考:Stock option expense - Maximum guidance value for the annual period'} +{'id': 5832, 'data_set_name': '可以使用:anl44_2_pretaxprofit_rep_lastactccy', 'description': '不可使用,仅供参考:pretaxprofit rep lastactccy'} +{'id': 320527, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_p1_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 86924, 'data_set_name': '可以使用:fnd72_s_pit_or_is_a2_is_pension_expense_income', 'description': '不可使用,仅供参考:The net amount of pension cost that is recognized in the income statement'} +{'id': 5706, 'data_set_name': '可以使用:selling_general_admin_expense_max_guidance_qtr', 'description': '不可使用,仅供参考:Selling, General & Admin Expenses - Maximum guidance value'} +{'id': 9240, 'data_set_name': '可以使用:anl82_netq_profitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on value of Q net income'} +{'id': 9318, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on value of Q operating profit'} +{'id': 5631, 'data_set_name': '可以使用:min_pretax_profit_guidance_2', 'description': '不可使用,仅供参考:The minimum guidance value for Pretax income on an annual basis.'} +{'id': 320520, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_all_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Pretax Profit'} +{'id': 9432, 'data_set_name': '可以使用:anl82_salq_profitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on value of Q sales'} +{'id': 79094, 'data_set_name': '可以使用:fn_profit_loss_a', 'description': '不可使用,仅供参考:The consolidated profit or loss for the period, net of income taxes, including the portion attributable to the noncontrolling interest.'} +{'id': 320518, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_all_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 79348, 'data_set_name': '可以使用:depreciation_expense_total', 'description': '不可使用,仅供参考:Total depreciation expense for the period.'} +{'id': 84058, 'data_set_name': '可以使用:quarterly_equity_compensation_expense', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Share Based Compensation'} +{'id': 5563, 'data_set_name': '可以使用:max_adjusted_net_profit_guidance', 'description': '不可使用,仅供参考:The maximum guidance value for adjusted net profit on an annual basis.'} +{'id': 10205, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on delta of annual operating profit'} +{'id': 9398, 'data_set_name': '可以使用:anl82_prey_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on delta of annual pre-tax profit'} +{'id': 9139, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on value of Q EBITDA'} +{'id': 84137, 'data_set_name': '可以使用:r_and_d_expense_total_fast_d1', 'description': '不可使用,仅供参考:Quarterly Accountance Adjustment Research & Development Expense'} +{'id': 10007, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on value of Q ebitda'} +{'id': 320406, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_all_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320547, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_all_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Pretax Profit'} +{'id': 10326, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on delta of annual sales'} +{'id': 9124, 'data_set_name': '可以使用:anl82_ebtq_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on delta of Q EBITDA'} +{'id': 320484, 'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_p1_high', 'description': '不可使用,仅供参考:highest value of all analysts estimates of Operating Profit'} +{'id': 6213, 'data_set_name': '可以使用:anl44_netprofit_rep_value', 'description': '不可使用,仅供参考:Netprofit rep D0 value'} +{'id': 320500, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_all_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Pretax Profit'} +{'id': 320476, 'data_set_name': '可以使用:pv87_2_operatingprofit_qf_matrix_all_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Operating Profit'} +{'id': 6215, 'data_set_name': '可以使用:anl44_operatingprofit_best_crncy_iso', 'description': '不可使用,仅供参考:operatingprofit best crncy iso'} +{'id': 151, 'data_set_name': '可以使用:anl10_dpsinnovation_score_fq2_1557', 'description': '不可使用,仅供参考:Innovation score for dividends per share Q2 (innovate_increase - innovate_decrease)'} +{'id': 79085, 'data_set_name': '可以使用:fn_prepaid_expense_q', 'description': '不可使用,仅供参考:Carrying amount for an unclassified balance sheet date of expenditures made in advance of when the economic benefit of the cost will be realized, and which will be expensed in future periods with the passage of time or when a triggering event occurs. For a classified balance sheet, represents the noncurrent portion of prepaid expenses (the current portion has a separate concept).'} +{'id': 793, 'data_set_name': '可以使用:anl10_preinnovation_score_fy2_1386', 'description': '不可使用,仅供参考:Innovation score for pre-tax or preliminary FY2 (innovate_increase - innovate_decrease)'} +{'id': 320492, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10297, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on value of Q sales'} +{'id': 320341, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_all_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Net Profit'} +{'id': 79301, 'data_set_name': '可以使用:annual_income_tax_expense_2', 'description': '不可使用,仅供参考:Total income tax expense for the annual period.'} +{'id': 153, 'data_set_name': '可以使用:anl10_dpsinnovation_score_fy2_1544', 'description': '不可使用,仅供参考:Innovation score for dividends per share FY2 (innovate_increase - innovate_decrease)'} +{'id': 10268, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on delta of annual pre-tax profit'} +{'id': 10140, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of annual net income'} +{'id': 320414, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_all_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Net Profit'} +{'id': 83695, 'data_set_name': '可以使用:fnd3_aacctadj_sgaexpense_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Selling, General & Administrative Expense'} +{'id': 10343, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on value of annual sales'} +{'id': 80544, 'data_set_name': '可以使用:gross_profit', 'description': '不可使用,仅供参考:Revenue minus cost of goods sold for the period.'} +{'id': 78927, 'data_set_name': '可以使用:fn_allocated_share_based_compensation_expense_a', 'description': '不可使用,仅供参考:Represents the expense recognized during the period arising from equity-based compensation arrangements (for example, shares of stock, unit, stock options or other equity instruments) with employees, directors and certain consultants qualifying for treatment as employees.'} +{'id': 83675, 'data_set_name': '可以使用:fnd3_aacctadj_opeexpenseexitems_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Operating Expense Extraordinary Items'} +{'id': 83357, 'data_set_name': '可以使用:fnd3_Q_opeexpenseexitems', 'description': '不可使用,仅供参考:Quarterly Operating Expense Extraordinary Items'} +{'id': 9278, 'data_set_name': '可以使用:anl82_nety_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on delta of annual net income'} +{'id': 85771, 'data_set_name': '可以使用:fnd72_pit_or_cr_a_cash_flow_to_int_expense', 'description': '不可使用,仅供参考:Measures the ratio of cash flow from operations to total interest incurred during the period'} +{'id': 9138, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of Q EBITDA'} +{'id': 320350, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_p1_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 6205, 'data_set_name': '可以使用:anl44_netprofit_rep_best_eeps_cur_yr', 'description': '不可使用,仅供参考:netprofit rep best eeps cur yr'} +{'id': 80579, 'data_set_name': '可以使用:liabilities_accrued_expenses', 'description': '不可使用,仅供参考:Accrued expenses classified as liabilities for the interim period.'} +{'id': 320463, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_p1_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Operating Profit'} +{'id': 10332, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on delta of annual sales'} +{'id': 420, 'data_set_name': '可以使用:anl10_epsinnovation_score_fy1', 'description': '不可使用,仅供参考:Innovation score for earnings per share FY1 (innovate_increase - innovate_decrease)'} +{'id': 40, 'data_set_name': '可以使用:anl10_cpsinnovation_score_fy1', 'description': '不可使用,仅供参考:Innovation score for cash per share FY1 (innovate_increase - innovate_decrease)'} +{'id': 6412, 'data_set_name': '可以使用:anl44_second_en_netprofit_broker', 'description': '不可使用,仅供参考:netprofit broker'} +{'id': 1015, 'data_set_name': '可以使用:anl10_salinnovation_score_fq2_1686', 'description': '不可使用,仅供参考:Innovation score for sales Q2 (innovate_increase - innovate_decrease)'} +{'id': 9365, 'data_set_name': '可以使用:anl82_preq_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on delta of Q pre-tax profit'} +{'id': 320363, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_all_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Net Profit'} +{'id': 10099, 'data_set_name': '可以使用:mdl211_netq_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on delta of Q net income'} +{'id': 9348, 'data_set_name': '可以使用:anl82_opry_profitability_profitability6', 'description': '不可使用,仅供参考:Profitability measure type 6 based on value of annual operating profit'} +{'id': 320397, 'data_set_name': '可以使用:pv87_2_netprofit_rep_af_matrix_p1_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320939, 'data_set_name': '可以使用:pv87_ann_matrix_interest_expense_estimate_high', 'description': '不可使用,仅供参考:High of Interest Expense Estimate'} +{'id': 320343, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_all_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Net Profit'} +{'id': 86227, 'data_set_name': '可以使用:fnd72_pit_or_is_q_is_expense_stock_based_comp', 'description': '不可使用,仅供参考:The expense for stock-based compensation'} +{'id': 320420, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10333, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability1', 'description': '不可使用,仅供参考:profitability measure type 1 based on value of annual sales'} +{'id': 9279, 'data_set_name': '可以使用:anl82_nety_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on delta of annual net income'} +{'id': 80853, 'data_set_name': '可以使用:total_tax_expense_2', 'description': '不可使用,仅供参考:Total tax expense recognized during the period.'} +{'id': 84135, 'data_set_name': '可以使用:r_and_d_expense_balance_fast_d1', 'description': '不可使用,仅供参考:Amount spent on research and development activities.'} +{'id': 80553, 'data_set_name': '可以使用:income_tax_expense_3', 'description': '不可使用,仅供参考:[Quarterly] Total Extraordinary Items'} +{'id': 9363, 'data_set_name': '可以使用:anl82_preq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on delta of Q pre-tax profit'} +{'id': 9165, 'data_set_name': '可以使用:anl82_ebty_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:Profitability Measure Type 3 Based on Delta of Annual EBITDA'} +{'id': 647, 'data_set_name': '可以使用:anl10_nerinnovation_score_fq2_1997', 'description': '不可使用,仅供参考:Innovation score for net earnings rate Q2 (innovate_increase - innovate_decrease)'} +{'id': 10334, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on value of annual sales'} +{'id': 80710, 'data_set_name': '可以使用:rental_expense_2', 'description': '不可使用,仅供参考:Total rental expense incurred during the period.'} +{'id': 150, 'data_set_name': '可以使用:anl10_dpsinnovation_score_fq1_1568', 'description': '不可使用,仅供参考:Innovation score for dividends per share Q1 (innovate_increase - innovate_decrease)'} +{'id': 5358, 'data_set_name': '可以使用:anl4_netprofita_number', 'description': '不可使用,仅供参考:Adjusted net income - number of estimations'} +{'id': 10162, 'data_set_name': '可以使用:mdl211_nety_profitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on value of annual net income'} +{'id': 9275, 'data_set_name': '可以使用:anl82_nety_deltaprofitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on delta of annual net income'} +{'id': 84112, 'data_set_name': '可以使用:quarterly_r_and_d_expense_total', 'description': '不可使用,仅供参考:Fiscal period endate of Annual Accountance Adjustment Research & Development Expense'} +{'id': 320391, 'data_set_name': '可以使用:pv87_2_netprofit_rep_af_matrix_all_median', 'description': '不可使用,仅供参考:median value of all analysts estimates of Net Profit'} +{'id': 10215, 'data_set_name': '可以使用:mdl211_opry_profitability_profitability2', 'description': '不可使用,仅供参考:profitability measure type 2 based on value of annual operating profit'} +{'id': 10214, 'data_set_name': '可以使用:mdl211_opry_profitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on value of annual operating profit'} +{'id': 6220, 'data_set_name': '可以使用:anl44_operatingprofit_best_eeps_nxt_yr', 'description': '不可使用,仅供参考:operatingprofit best eeps nxt yr'} +{'id': 320444, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9319, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of Q operating profit'} +{'id': 320545, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_all_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Pretax Profit'} +{'id': 320489, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320447, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Operating Profit'} +{'id': 320431, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_b_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9467, 'data_set_name': '可以使用:anl82_saly_profitability_profitability3', 'description': '不可使用,仅供参考:Profitability measure type 3 based on value of annual sales'} +{'id': 10012, 'data_set_name': '可以使用:mdl211_ebtq_profitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on value of Q ebitda'} +{'id': 320366, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_all_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Net Profit'} +{'id': 10212, 'data_set_name': '可以使用:mdl211_opry_profitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on value of annual operating profit'} +{'id': 6204, 'data_set_name': '可以使用:anl44_netprofit_rep_best_cur_fiscal_year_period', 'description': '不可使用,仅供参考:netprofit rep best cur fiscal year period'} +{'id': 79095, 'data_set_name': '可以使用:fn_profit_loss_q', 'description': '不可使用,仅供参考:The consolidated profit or loss for the period, net of income taxes, including the portion attributable to the noncontrolling interest.'} +{'id': 320502, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10119, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on value of Q net income'} +{'id': 9346, 'data_set_name': '可以使用:anl82_opry_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of annual operating profit'} +{'id': 10275, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on delta of annual pre-tax profit'} +{'id': 6414, 'data_set_name': '可以使用:anl44_second_en_netprofit_rep_lastactccy', 'description': '不可使用,仅供参考:netprofit rep lastactccy'} +{'id': 80652, 'data_set_name': '可以使用:operating_profit_total_2', 'description': '不可使用,仅供参考:Total operating profit earned by the company during the period.'} +{'id': 10266, 'data_set_name': '可以使用:mdl211_prey_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:profitability measure type 10 based on delta of annual pre-tax profit'} +{'id': 10204, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on delta of annual operating profit'} +{'id': 10186, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability5', 'description': '不可使用,仅供参考:profitability measure type 5 based on value of Q operating profit'} +{'id': 10144, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on delta of annual net income'} +{'id': 320402, 'data_set_name': '可以使用:pv87_2_netprofit_rep_af_matrix_p1_mean', 'description': '不可使用,仅供参考:mean value of all analysts estimates of Net Profit'} +{'id': 6792, 'data_set_name': '可以使用:anl49_backfill_alldividendstonetprofitindicator', 'description': '不可使用,仅供参考:All dividends to net profit indicator'} +{'id': 9269, 'data_set_name': '可以使用:anl82_nety_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:Profitability measure type 10 based on delta of annual net income'} +{'id': 5633, 'data_set_name': '可以使用:min_research_development_expense_guidance', 'description': '不可使用,仅供参考:Minimum guidance value for Research & Development Expense'} +{'id': 720, 'data_set_name': '可以使用:anl10_netinnovation_score_fy1_2515', 'description': '不可使用,仅供参考:Innovation score for net income FY1 (innovate_increase - innovate_decrease)'} +{'id': 86233, 'data_set_name': '可以使用:fnd72_pit_or_is_q_is_int_expense', 'description': '不可使用,仅供参考:Interest Expense'} +{'id': 320555, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_p1_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Pretax Profit'} +{'id': 320399, 'data_set_name': '可以使用:pv87_2_netprofit_rep_af_matrix_p1_dts', 'description': '不可使用,仅供参考:std value of all analysts estimates of Net Profit'} +{'id': 9286, 'data_set_name': '可以使用:anl82_nety_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of annual net income'} +{'id': 10208, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of annual operating profit'} +{'id': 10184, 'data_set_name': '可以使用:mdl211_oprq_profitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on value of Q operating profit'} +{'id': 9394, 'data_set_name': '可以使用:anl82_prey_deltaprofitability_profitability1', 'description': '不可使用,仅供参考:Profitability measure type 1 based on delta of annual pre-tax profit'} +{'id': 9332, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on delta of annual operating profit'} +{'id': 6270, 'data_set_name': '可以使用:anl44_orig_en_pretaxprofit_coveredby', 'description': '不可使用,仅供参考:orig en pretaxprofit coveredby'} +{'id': 9244, 'data_set_name': '可以使用:anl82_netq_profitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on value of Q net income'} +{'id': 6937, 'data_set_name': '可以使用:anl49_netprofitindicator', 'description': '不可使用,仅供参考:Net profit indicator'} +{'id': 320369, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9464, 'data_set_name': '可以使用:anl82_saly_profitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on value of annual sales'} +{'id': 320574, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_p1_chngratio_low', 'description': '不可使用,仅供参考:lowest value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 83129, 'data_set_name': '可以使用:annual_equity_compensation_expense', 'description': '不可使用,仅供参考:Expense from share-based compensation for the year.'} +{'id': 9314, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of Q operating profit'} +{'id': 322102, 'data_set_name': '可以使用:pv87_interest_expense_actual_scale', 'description': '不可使用,仅供参考:Scale of Interest Expense Actual'} +{'id': 320548, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_all_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Pretax Profit'} +{'id': 9460, 'data_set_name': '可以使用:anl82_saly_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on delta of annual sales'} +{'id': 320497, 'data_set_name': '可以使用:pv87_2_pretaxprofit_af_matrix_all_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Pretax Profit'} +{'id': 6225, 'data_set_name': '可以使用:anl44_operatingprofit_most_recent_period_end_dt', 'description': '不可使用,仅供参考:operatingprofit most recent period end dt'} +{'id': 83290, 'data_set_name': '可以使用:fnd3_Aacctadj_opeexpenses', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Total Operating Expenses'} +{'id': 9142, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability8', 'description': '不可使用,仅供参考:Profitability measure type 8 based on value of Q EBITDA'} +{'id': 10228, 'data_set_name': '可以使用:mdl211_preq_deltaprofitability_profitability12', 'description': '不可使用,仅供参考:profitability measure type 12 based on delta of Q pre-tax profit'} +{'id': 5715, 'data_set_name': '可以使用:stock_option_expense_max_guidance_qtr', 'description': '不可使用,仅供参考:Stock option expense - maximum guidance value'} +{'id': 5630, 'data_set_name': '可以使用:min_pretax_profit_guidance', 'description': '不可使用,仅供参考:Minimum guidance value for Pretax income'} +{'id': 80578, 'data_set_name': '可以使用:lease_expense_total', 'description': '不可使用,仅供参考:Total lease expenses incurred during the period.'} +{'id': 9428, 'data_set_name': '可以使用:anl82_salq_profitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on value of Q sales'} +{'id': 6415, 'data_set_name': '可以使用:anl44_second_en_netprofit_rep_prevalue', 'description': '不可使用,仅供参考:netprofit rep prevalue'} +{'id': 320425, 'data_set_name': '可以使用:pv87_2_netprofit_rep_qf_matrix_p1_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Net Profit'} +{'id': 320536, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_p1_number', 'description': '不可使用,仅供参考:count number of estimates (once for one analyst) of Pretax Profit'} +{'id': 320441, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320365, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_all_low', 'description': '不可使用,仅供参考:lowest value of all analysts estimates of Net Profit'} +{'id': 320396, 'data_set_name': '可以使用:pv87_2_netprofit_rep_af_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10302, 'data_set_name': '可以使用:mdl211_salq_profitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on value of Q sales'} +{'id': 718, 'data_set_name': '可以使用:anl10_netinnovation_score_fq1_2521', 'description': '不可使用,仅供参考:Innovation score for net income Q1 (innovate_increase - innovate_decrease)'} +{'id': 83138, 'data_set_name': '可以使用:annual_income_tax_expense_fast_d1', 'description': '不可使用,仅供参考:Total income tax expense for the year.'} +{'id': 9270, 'data_set_name': '可以使用:anl82_nety_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on delta of annual net income'} +{'id': 9329, 'data_set_name': '可以使用:anl82_opry_deltaprofitability_profitability10', 'description': '不可使用,仅供参考:Profitability measure type 10 based on delta of annual operating profit'} +{'id': 10344, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on value of annual sales'} +{'id': 6209, 'data_set_name': '可以使用:anl44_netprofit_rep_coveredby', 'description': '不可使用,仅供参考:Netprofit rep d0 coveredby'} +{'id': 9302, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:Profitability measure type 4 based on delta of Q operating profit'} +{'id': 9237, 'data_set_name': '可以使用:anl82_netq_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:Profitability measure type 7 based on delta of Q net income'} +{'id': 322104, 'data_set_name': '可以使用:pv87_interest_expense_consensus_high_scale', 'description': '不可使用,仅供参考:Scale of Interest Expense Consensus High'} +{'id': 9343, 'data_set_name': '可以使用:anl82_opry_profitability_profitability12', 'description': '不可使用,仅供参考:Profitability measure type 12 based on value of annual operating profit'} +{'id': 83781, 'data_set_name': '可以使用:fnd3_q_grossprofit_fast_d1', 'description': '不可使用,仅供参考:Quarterly Gross Profit'} +{'id': 10330, 'data_set_name': '可以使用:mdl211_saly_deltaprofitability_profitability7', 'description': '不可使用,仅供参考:profitability measure type 7 based on delta of annual sales'} +{'id': 320517, 'data_set_name': '可以使用:pv87_2_pretaxprofit_qf_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 320565, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_qf_matrix_all_chngratio_number', 'description': '不可使用,仅供参考:count number of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10145, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability4', 'description': '不可使用,仅供参考:profitability measure type 4 based on delta of annual net income'} +{'id': 320446, 'data_set_name': '可以使用:pv87_2_operatingprofit_af_matrix_all_chngratio_std', 'description': '不可使用,仅供参考:std value of all change ratio of Operating Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 322106, 'data_set_name': '可以使用:pv87_interest_expense_consensus_low_scale', 'description': '不可使用,仅供参考:Scale of Interest Expense Consensus Low'} +{'id': 6418, 'data_set_name': '可以使用:anl44_second_en_operatingprofit_coveredby', 'description': '不可使用,仅供参考:operatingprofit coveredby'} +{'id': 10209, 'data_set_name': '可以使用:mdl211_opry_deltaprofitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on delta of annual operating profit'} +{'id': 10161, 'data_set_name': '可以使用:mdl211_nety_profitability_profitability8', 'description': '不可使用,仅供参考:profitability measure type 8 based on value of annual net income'} +{'id': 9134, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on value of Q EBITDA'} +{'id': 10150, 'data_set_name': '可以使用:mdl211_nety_deltaprofitability_profitability9', 'description': '不可使用,仅供参考:profitability measure type 9 based on delta of annual net income'} +{'id': 10175, 'data_set_name': '可以使用:mdl211_oprq_deltaprofitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on delta of Q operating profit'} +{'id': 6193, 'data_set_name': '可以使用:anl44_netprofit_gaap_best_cur_fiscal_year_period', 'description': '不可使用,仅供参考:netprofit gaap best cur fiscal year period'} +{'id': 320552, 'data_set_name': '可以使用:pv87_2_pretaxprofit_rep_af_matrix_p1_chngratio_median', 'description': '不可使用,仅供参考:median value of all change ratio of Pretax Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 5814, 'data_set_name': '可以使用:anl44_2_netprofit_prevalue', 'description': '不可使用,仅供参考:netprofit prevalue'} +{'id': 6264, 'data_set_name': '可以使用:anl44_orig_en_netprofit_rep_prevalue', 'description': '不可使用,仅供参考:orig en netprofit rep prevalue'} +{'id': 79330, 'data_set_name': '可以使用:current_tax_expense', 'description': '不可使用,仅供参考:[Quarterly] Current Tax - Foreign'} +{'id': 320359, 'data_set_name': '可以使用:pv87_2_netprofit_qf_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9183, 'data_set_name': '可以使用:anl82_ebty_profitability_profitability9', 'description': '不可使用,仅供参考:Profitability measure type 9 based on value of annual EBITDA'} +{'id': 6210, 'data_set_name': '可以使用:anl44_netprofit_rep_latest_ann_dt_qtrly', 'description': '不可使用,仅供参考:netprofit rep latest ann dt qtrly'} +{'id': 320335, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_all_chngratio_mean', 'description': '不可使用,仅供参考:mean value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 10341, 'data_set_name': '可以使用:mdl211_saly_profitability_profitability6', 'description': '不可使用,仅供参考:profitability measure type 6 based on value of annual sales'} +{'id': 9136, 'data_set_name': '可以使用:anl82_ebtq_profitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on value of Q EBITDA'} +{'id': 5634, 'data_set_name': '可以使用:min_research_development_expense_guidance_2', 'description': '不可使用,仅供参考:Minimum guidance value for Research & Development Expense on an annual basis'} +{'id': 9298, 'data_set_name': '可以使用:anl82_oprq_deltaprofitability_profitability11', 'description': '不可使用,仅供参考:Profitability measure type 11 based on delta of Q operating profit'} +{'id': 10116, 'data_set_name': '可以使用:mdl211_netq_profitability_profitability3', 'description': '不可使用,仅供参考:profitability measure type 3 based on value of Q net income'} +{'id': 83649, 'data_set_name': '可以使用:fnd3_aacctadj_grossprofit_fast_d1', 'description': '不可使用,仅供参考:Annual Accountance Adjustment Gross Profit'} +{'id': 41, 'data_set_name': '可以使用:anl10_cpsinnovation_score_fy2', 'description': '不可使用,仅供参考:Innovation score for cash per share FY2 (innovate_increase - innovate_decrease)'} +{'id': 5834, 'data_set_name': '可以使用:anl44_2_pretaxprofit_rep_prevalue', 'description': '不可使用,仅供参考:pretaxprofit rep prevalue'} +{'id': 9315, 'data_set_name': '可以使用:anl82_oprq_profitability_profitability5', 'description': '不可使用,仅供参考:Profitability measure type 5 based on value of Q operating profit'} +{'id': 85535, 'data_set_name': '可以使用:fnd72_pit_or_bs_a_bs_curr_rental_expense', 'description': '不可使用,仅供参考:Operating lease expenses recognized in the income statement for the period'} +{'id': 6271, 'data_set_name': '可以使用:anl44_orig_en_pretaxprofit_prevalue', 'description': '不可使用,仅供参考:orig en pretaxprofit prevalue'} +{'id': 791, 'data_set_name': '可以使用:anl10_preinnovation_score_fq2_1369', 'description': '不可使用,仅供参考:Innovation score for pre-tax or preliminary Q2 (innovate_increase - innovate_decrease)'} +{'id': 320345, 'data_set_name': '可以使用:pv87_2_netprofit_af_matrix_p1_chngratio_high', 'description': '不可使用,仅供参考:highest value of all change ratio of Net Profit *change ratio = ((current value - previous value) / (fabs (current value)/2 + fabs (previous value)/2))'} +{'id': 9284, 'data_set_name': '可以使用:anl82_nety_profitability_profitability2', 'description': '不可使用,仅供参考:Profitability measure type 2 based on value of annual net income'} +========================= 数据字段结束 ======================================= + +以上数据字段和操作符, 按照Description说明组合, 但是每一个 alpha 组合的使用的数据字段和操作符不要过于集中, 在符合语法的情况下, 多尝试不同的组合 + +你再检查一下, 如果你使用了 +Operator abs does not support event inputs +Operator ts_mean does not support event inputs +Operator ts_scale does not support event inputs +Operator add does not support event inputs +Operator sign does not support event inputs +Operator greater does not support event inputs +Operator ts_av_diff does not support event inputs +Operator ts_quantile does not support event inputs +Operator ts_arg_min does not support event inputs +Operator divide does not support event inputs +Operator ts_corr does not support event inputs +Operator ts_decay_linear does not support event inputs +Operator ts_sum does not support event inputs +Operator ts_delay does not support event inputs +Operator ts_arg_max does not support event inputs +Operator ts_std_dev does not support event inputs +Operator ts_regression does not support event inputs +Operator ts_backfill does not support event inputs +Operator signed_power does not support event inputs +Operator ts_product does not support event inputs +Operator ts_zscore does not support event inputs +Operator group_rank does not support event inputs +Operator subtract does not support event inputs +Operator ts_delta does not support event inputs +Operator ts_rank does not support event inputs +Operator ts_count_nans does not support event inputs +Operator ts_covariance does not support event inputs +Operator multiply does not support event inputs +Operator if_else does not support event inputs +Operator group_neutralize does not support event inputs +Operator group_zscore does not support event inputs +Operator winsorize does not support event inputs +注意, 以上操作符不能使用事件类型的数据集, 以上操作符禁止使用事件类型的数据集!! \ No newline at end of file diff --git a/optimize_alpha.py b/optimize_alpha.py deleted file mode 100644 index b01dad8..0000000 --- a/optimize_alpha.py +++ /dev/null @@ -1,58 +0,0 @@ -import os -import sqlite3 -import sys - -sys.path.append(os.path.join(os.path.abspath(__file__).split('AlphaGenerator')[0] + 'AlphaGenerator')) -PROJECT_PATH = os.path.join(os.path.abspath(__file__).split('AlphaGenerator')[0] + 'AlphaGenerator') -PREPARE_PROMPT = os.path.join(str(PROJECT_PATH), 'prepare_prompt') - -input_alpha = 'not(is_nan({}))' - -# 数据库搜索字段 -REGION = 'USA' -UNIVERSE = 'TOP3000' -TARGET = 'pv87_%' - - -def sqliteLoader(file_path): - if not os.path.exists(file_path): - print(f"SQLite数据库文件不存在: {file_path}") - exit(1) - - conn = sqlite3.connect(file_path) - try: - - cursor = conn.cursor() - - # 首先筛选符合 region 和 universe 条件的数据 - cursor.execute("SELECT name FROM data_sets WHERE region=? AND universe=? AND name like ?", - (REGION, UNIVERSE, TARGET)) - rows = cursor.fetchall() - - conn.close() - - if len(rows) > 0: - print(f"找到 {len(rows)} 条符合条件的数据") - return rows - else: - print("未找到符合条件的数据") - exit(1) - - except sqlite3.Error as e: - print(f"SQLite数据库错误: {e}") - exit(1) - finally: - if conn: - conn.close() - -data_sets_path = os.path.join(PREPARE_PROMPT, "data_sets.db") -data_rows = sqliteLoader(data_sets_path) - -start_at = 0 -end_at = 1000 - -for num in range(start_at, end_at): - row = data_rows[num] - new_alpha = input_alpha.format(row[0]) - print(new_alpha) - diff --git a/planning_post_alpha.txt b/planning_post_alpha.txt index 74a327b..a029834 100644 --- a/planning_post_alpha.txt +++ b/planning_post_alpha.txt @@ -1,244 +1,500 @@ -group_neutralize(ts_zscore(management_ethics_sector_rank, 126), "sector") -group_neutralize(ts_mean(fnd28_ratesq_value_08316q, 5), exchange) -group_neutralize(ts_mean(fnd28_ratesq_value_08106q, 5), exchange) -group_neutralize(ts_mean(fnd28_growthratesa_value_08610a, 5), exchange) -ts_delta(pv87_changeinavgdailyvolume, 1) -group_neutralize(ts_delta(anl40_turnoverrate, 1), exchange) -zscore(anl40_turnoverrate) -group_neutralize(ts_mean(fnd28_growthratesa_value_08604a, 5), exchange) -ts_zscore(anl40_turnoverrate, 63) -group_neutralize(ts_mean(fnd28_ratesq_value_08366q, 5), exchange) -group_neutralize(ts_mean(fnd28_growthratesa_value_08646a, 5), exchange) -ts_mean(management_ethics_standards_score, 252) - ts_std_dev(price, 63) -group_neutralize(ts_mean(fnd28_ratesq_value_08326q, 5), exchange) -group_neutralize(ts_mean(fnd28_ratesq_value_08421q, 5), exchange) -group_zscore(ts_mean(anl40_turnoverrate, 252), industry) -group_neutralize(ts_mean(fnd28_growthratesa_value_08636a, 5), exchange) -group_neutralize(ts_zscore(management_ethics_subsector_rank, 252), "subsector") -jump_decay(pv87_holdings, 30, 0.6, 0.2) -quantile(ts_mean(anl40_turnoverrate, 252), driver=gaussian) -group_neutralize(ts_mean(fnd28_growthratesa_value_08605a, 5), exchange) -ts_mean(anl49_35estd35yrgrowthrateearningspershare, 63) -group_scale(anl40_turnoverrate, exchange) -group_neutralize(ts_mean(fnd28_wcratesq_value_08231q, 5), exchange) -group_neutralize(ts_mean(management_ethics_sector_percentile, 252) / ts_std_dev(price, 63), "sector") -group_neutralize(ts_mean(management_ethics_industry_rank, 252) + ts_mean(est_q_roe_mean, 252), "industry") -ts_rank(management_ethics_industry_percentile, 126) -group_neutralize(ts_mean(anl40_turnoverrate, 252), industry) + zscore(fnd17_qroepct) -group_neutralize(ts_mean(fnd28_wcratesq_value_08241q, 5), exchange) -ts_mean(management_ethics_standards_score, 252) / ts_mean(est_q_roe_std_28d, 252) -multiply(group_neutralize(ts_mean(anl40_turnoverrate, 252), industry), zscore(pv87_price_volatility_estimate_high)) -not(is_nan(pv87_holdings)) -group_neutralize(ts_mean(fnd28_ratesq_value_08401q, 5), exchange) -days_from_last_change(pv87_holdings) -group_neutralize(signed_power(ts_mean(anl40_turnoverrate, 252), 2), industry) -rank(ts_mean(anl40_turnoverrate, 252)) -group_cartesian_product(exchange, pv87_holdings) -ts_mean(anl49_standarddeviationofpricechange, 63) -ts_mean(management_ethics_standards_score, 252) * ts_mean(est_12m_roe_high, 63) -group_neutralize(ts_mean(management_ethics_standards_score, 252), "industry") -group_neutralize(ts_mean(pv64_out_stal_fund_turnover, 5), exchange) -ts_mean(pv87_changeinsharesshort, 63) -group_neutralize(ts_mean(fnd28_growthratesa_value_08640a, 5), exchange) -ts_delta(total_shareholding_value, 1) -ts_mean(management_ethics_standards_score, 252) * ts_mean(est_q_roe_mean, 252) -group_neutralize(ts_mean(fnd28_growthratesa_value_08635a, 5), exchange) -normalize(anl40_turnoverrate) -group_neutralize(ts_mean(fnd28_ratesq_value_08676q, 5), exchange) -group_neutralize(ts_mean(fnd28_growthratesa_value_08621a, 5), exchange) -sign(subtract(pv87_holdings, group_mean(pv87_holdings, 1, exchange))) -group_neutralize(ts_mean(fnd28_wcratesq_value_08251q, 5), exchange) -group_neutralize(ts_mean(management_ethics_subsector_rank, 252), "subsector") -multiply(group_neutralize(ts_mean(anl40_turnoverrate, 252), industry), zscore(pv87_price_volatility_estimate_median)) -group_neutralize(ts_mean(pv48_r3000e_amount_change_growth, 5), exchange) -group_neutralize(ts_mean(pv48_r3000_amount_change_value, 5), exchange) -and(pv87_holdings > group_mean(pv87_holdings, 1, exchange), anl40_turnoverrate < ts_mean(anl40_turnoverrate, 90)) -group_neutralize(ts_mean(fnd28_growthratesa_value_08676a, 5), exchange) -group_neutralize(ts_mean(management_ethics_industry_rank, 252) + ts_mean(est_12m_roe_mean, 126), "industry") -ts_quantile(anl40_turnoverrate, 63) -last_diff_value(pv87_holdings, 30) -group_neutralize(ts_mean(fnd28_ratesq_value_08651q, 5), exchange) -ts_mean(management_ethics_standards_score, 252) / ts_mean(est_12m_roe_std_4wks_ago, 252) -group_neutralize(ts_mean(management_ethics_industry_percentile, 63), "industry") -group_neutralize(ts_mean(management_ethics_sector_rank, 252) - ts_mean(est_12m_roe_mean, 252), "sector") -ts_mean(pv87_changeinavgdailyvolume, 63) -group_neutralize(ts_mean(fnd28_ratesq_value_08579q, 5), exchange) -self_corr(pv87_holdings) -group_neutralize(ts_mean(fnd28_growthratesa_value_08680a, 5), exchange) -group_neutralize(ts_mean(fnd28_ratesq_value_08346q, 5), exchange) -group_neutralize(ts_delta(management_ethics_subsector_rank, 252), "subsector") -ts_covariance(anl40_turnoverrate, pv87_changeinsharesshort, 63) -group_neutralize(ts_mean(anl40_turnoverrate, 252), industry) -ts_mean(power(anl40_turnoverrate, 2), 63) -ts_mean(management_ethics_standards_score, 252) - ts_std_dev(price, 126) -divide(ts_mean(pv87_holdings, 90), ts_mean(anl40_netturnoverrate, 90)) -group_neutralize(ts_mean(fnd28_ratesq_value_08606q, 5), exchange) -group_neutralize(ts_mean(fnd28_ratesq_value_08621q, 5), exchange) -group_neutralize(hump(ts_mean(anl40_turnoverrate, 252)), industry) -ts_mean(management_ethics_sector_percentile, 252) * ts_mean(est_q_roe_median, 252) -group_neutralize(ts_mean(anl40_turnoverrate, 126), industry) -group_neutralize(ts_mean(fnd28_wcratesq_value_08236q, 5), exchange) -ts_mean(divide(anl40_turnoverrate, pv87_changeinsharesshort), 63) -ts_mean(subtract(anl40_turnoverrate, pv87_changeinsharesshort), 63) -ts_mean(log(anl40_turnoverrate), 63) -group_neutralize(ts_mean(anl40_turnoverrate, 504), industry) -multiply(group_neutralize(ts_mean(anl40_turnoverrate, 252), industry), rank(pv87_price_volatility_estimate_mean)) -group_neutralize(ts_mean(pv48_r3000_amount_change, 5), exchange) -group_neutralize(ts_mean(management_ethics_sector_rank, 126) - ts_mean(est_q_roe_low, 252), "sector") -ts_av_diff(anl40_turnoverrate, 63) -ts_backfill(anl40_turnoverrate, 63) -divide(group_neutralize(ts_mean(anl40_turnoverrate, 252), industry), group_neutralize(ts_mean(pv87_price_volatility_estimate_mean, 252), industry)) -group_neutralize(ts_mean(fnd28_growthratesa_value_08630a, 5), exchange) -group_neutralize(ts_mean(fnd28_growthratesa_value_08626a, 5), exchange) -ts_mean(management_ethics_sector_percentile, 252) - ts_std_dev(price, 252) -ts_rank(management_ethics_sector_percentile, 63) -ts_mean(fnd28_ratesq_value_08306q, 63) -ts_mean(anl40_turnoverrate, 63) -group_neutralize(ts_mean(fnd28_growthratesa_value_08620a, 5), exchange) -group_neutralize(ts_mean(fnd28_growthratesa_value_08816a, 5), exchange) -ts_mean(abs(anl40_turnoverrate), 63) -group_neutralize(rank(ts_mean(pv87_holdings, 90)), exchange) -group_neutralize(ts_mean(fnd28_growthratesa_value_08650a, 5), exchange) -ts_mean(management_ethics_standards_score, 252) / ts_std_dev(price, 252) -reverse(rank(group_zscore(pv87_holdings, exchange))) -ts_mean(management_ethics_standards_score, 252) / ts_mean(est_q_roe_std_3mth_ago, 252) -combo_a(rank(pv87_holdings), 250, 'algo1') -group_neutralize(ts_mean(fnd28_ratesq_value_08371q, 5), exchange) -multiply(group_neutralize(ts_mean(anl40_turnoverrate, 252), industry), zscore(fnd17_aroepct)) -ts_arg_min(anl40_turnoverrate, 63) -multiply(group_neutralize(ts_mean(anl40_turnoverrate, 252), industry), rank(fnd17_qroepct)) -group_neutralize(ts_mean(management_ethics_industry_percentile, 252) - ts_mean(est_12m_roe_low, 252), "industry") -group_neutralize(ts_mean(fnd28_growthratesa_value_08616a, 5), exchange) -group_neutralize(ts_delta(management_ethics_sector_rank, 126), "sector") -group_neutralize(log(ts_mean(anl40_turnoverrate, 252)), industry) -group_neutralize(ts_delay(anl40_turnoverrate, 21), industry) -group_rank(ts_mean(anl40_turnoverrate, 252), industry) -group_neutralize(ts_mean(fnd28_growthratesa_value_08631a, 5), exchange) -ts_mean(sign(anl40_turnoverrate), 63) -ts_rank(management_ethics_standards_score, 252) -group_neutralize(ts_mean(fnd28_ratesq_value_08311q, 5), exchange) -ts_mean(sqrt(anl40_turnoverrate), 63) -group_neutralize(ts_mean(management_ethics_subsector_percentile, 126), "subsector") -group_neutralize(ts_mean(management_ethics_industry_percentile, 252), "industry") -power(group_scale(pv87_holdings, exchange), 2) -ts_mean(reverse(anl40_turnoverrate), 63) -group_neutralize(ts_mean(fnd28_growthratesa_value_08611a, 5), exchange) -group_neutralize(ts_mean(pv48_r3000e_amount_change, 5), exchange) -group_neutralize(ts_mean(management_ethics_sector_percentile, 252), "sector") -group_neutralize(ts_delta(anl40_turnoverrate, 63), industry) -group_neutralize(ts_decay_linear(ts_mean(anl40_turnoverrate, 252), 252), industry) -trade_when(pv87_holdings > ts_mean(pv87_holdings, 90), anl40_turnoverrate, pv87_holdings) -group_neutralize(ts_mean(pv48_dynamic_amount_change, 5), exchange) -sqrt(abs(subtract(pv87_holdings, ts_mean(pv87_holdings, 90)))) -group_neutralize(ts_rank(anl40_turnoverrate, 252), industry) -winsorize(ts_mean(anl40_turnoverrate, 252), std=4) -ts_regression(anl40_turnoverrate, pv87_changeinsharesshort, 63) -group_neutralize(ts_mean(fnd28_growthratesa_value_08579a, 5), exchange) -group_scale(ts_mean(anl40_turnoverrate, 252), industry) -group_neutralize(ts_mean(management_ethics_sector_percentile, 252) / ts_std_dev(price, 252), "sector") -group_neutralize(ts_mean(fnd28_growthratesa_value_08821a, 5), exchange) -ts_sum(anl40_turnoverrate, 63) -group_neutralize(ts_mean(fnd28_ratesq_value_08616q, 5), exchange) -group_neutralize(ts_mean(anl40_turnoverrate, 252), sector) -quantile(anl40_turnoverrate) -group_neutralize(ts_delta(management_ethics_standards_score, 252), "industry") -group_neutralize(ts_zscore(management_ethics_subsector_rank, 63), "subsector") -min(group_max(pv87_holdings, exchange), ts_max(pv87_holdings, 90)) -group_neutralize(ts_mean(fnd28_ratesq_value_08416q, 5), exchange) -group_neutralize(ts_mean(anl40_turnoverrate, 252) * ts_mean(pv87_price_volatility_estimate_mean, 252), industry) -inverse(add(pv87_holdings, anl40_turnoverrate)) -group_neutralize(ts_mean(fnd28_ratesq_value_08111q, 5), exchange) -ts_count_nans(anl40_turnoverrate, 63) -winsorize(anl40_turnoverrate) -group_neutralize(ts_mean(management_ethics_subsector_percentile, 252) / ts_std_dev(price, 126), "subsector") -trade_when(pv87_price_volatility_estimate_mean < ts_mean(pv87_price_volatility_estimate_mean, 252), group_neutralize(ts_mean(anl40_turnoverrate, 252), industry), NaN) -scale_down(rank(subtract(pv87_holdings, ts_delay(pv87_holdings, 30))), 0.5) -group_neutralize(ts_mean(fnd28_growthratesa_value_08601a, 5), exchange) -normalize(subtract(pv87_holdings, group_mean(pv87_holdings, 1, exchange))) -group_neutralize(ts_mean(anl40_turnoverrate, 63), exchange) -group_neutralize(ts_delta(anl40_turnoverrate, 21), industry) -ts_rank(anl40_turnoverrate, 252) -group_neutralize(ts_mean(pv64_dif_stal_fund_turnover, 5), exchange) -group_neutralize(ts_mean(pv87_changeinavgdailyvolume, 63), exchange) -ts_mean(add(anl40_turnoverrate, pv87_changeinsharesshort), 63) -group_neutralize(ts_mean(anl40_turnoverrate, 252) * inverse(fnd17_qroepct), industry) -group_neutralize(ts_mean(fnd28_wcratesq_value_08801q, 5), exchange) -ts_mean(management_ethics_standards_score, 252) * ts_mean(est_q_roe_high, 126) -group_neutralize(ts_zscore(management_ethics_industry_percentile, 252), "industry") -densify(group_rank(pv87_holdings, exchange)) -normalize(ts_mean(anl40_turnoverrate, 252)) -ts_mean(fnd28_ratesq_value_08106q, 63) -ts_scale(management_ethics_standards_score, 252) -max(group_min(pv87_holdings, exchange), ts_min(pv87_holdings, 90)) -ts_mean(management_ethics_standards_score, 252) / ts_mean(est_12m_roe_std_28d, 252) -group_neutralize(ts_mean(anl40_turnoverrate, 252), country) -group_neutralize(ts_product(anl40_turnoverrate, 21), industry) -group_neutralize(ts_mean(fnd28_wcratesq_value_08226q, 5), exchange) -group_neutralize(ts_mean(fnd28_ratesq_value_08321q, 5), exchange) -ts_scale(anl40_turnoverrate, 63) -ts_mean(pv87_effective_tax_rate_consensus_mean, 63) -ts_arg_max(anl40_turnoverrate, 63) -group_neutralize(ts_mean(pv87_effective_tax_rate_consensus_mean, 63), exchange) -group_neutralize(ts_mean(pv87_changeinsharesshort, 63), exchange) -group_neutralize(ts_mean(fnd28_ratesq_value_08106q, 63), exchange) -if_else(fnd17_qroepct > 0, group_neutralize(ts_mean(anl40_turnoverrate, 252), industry), NaN) -or(pv87_holdings < group_min(pv87_holdings, exchange), anl40_netturnoverrate > ts_max(anl40_netturnoverrate, 90)) -group_backfill(pv87_holdings, exchange, 90, 3.0) -group_neutralize(ts_mean(fnd28_ratesq_value_08601q, 5), exchange) -group_neutralize(ts_mean(fnd28_ratesq_value_08611q, 5), exchange) -group_neutralize(ts_mean(management_ethics_subsector_rank, 63), "subsector") -ts_mean(management_ethics_industry_percentile, 252) * ts_mean(est_12m_roe_median, 252) -quantile(rank(pv87_holdings), driver="uniform") -ts_mean(inverse(anl40_turnoverrate), 63) -if_else(pv87_holdings > ts_quantile(pv87_holdings, 90), reverse(pv87_holdings), pv87_holdings) -ts_product(anl40_turnoverrate, 63) -bucket(rank(pv87_holdings), range="0,1,0.2") -multiply(group_neutralize(ts_mean(anl40_turnoverrate, 252), industry), group_neutralize(ts_mean(fnd17_qroepct, 252), industry)) -zscore(ts_mean(anl40_turnoverrate, 252)) -kth_element(pv87_holdings, 90, 10) -group_neutralize(ts_mean(fnd28_wcratesq_value_08266q, 5), exchange) -ts_rank(anl40_turnoverrate, 63) -ts_decay_linear(anl40_turnoverrate, 63) -ts_rank(management_ethics_subsector_rank, 252) -rank(anl40_turnoverrate) -group_neutralize(power(ts_mean(anl40_turnoverrate, 252), 2), industry) -group_neutralize(ts_mean(fnd28_wcratesq_value_08261q, 5), exchange) -ts_mean(multiply(anl40_turnoverrate, pv87_changeinsharesshort), 63) -group_neutralize(ts_mean(anl40_turnoverrate, 252) * zscore(pv87_price_volatility_estimate_mean), industry) -group_neutralize(ts_mean(anl40_turnoverrate, 252), industry) + group_neutralize(ts_mean(fnd17_qroepct, 252), industry) -ts_delta(anl40_turnoverrate, 1) -group_neutralize(ts_mean(anl40_turnoverrate, 252) / ts_mean(fnd17_qroepct, 252), industry) -group_rank(anl40_turnoverrate, exchange) -group_neutralize(ts_mean(fnd28_ratesq_value_08301q, 5), exchange) -group_neutralize(ts_mean(anl40_turnoverrate, 252), industry) - zscore(pv87_price_volatility_estimate_mean) -group_neutralize(ts_mean(fnd28_growthratesa_value_08625a, 5), exchange) -group_neutralize(ts_av_diff(anl40_turnoverrate, 252), industry) -ts_mean(total_shareholding_value, 63) -ts_scale(management_ethics_subsector_percentile, 252) -zscore(multiply(pv87_holdings, anl40_employmentrate)) -group_neutralize(ts_mean(fnd28_ratesq_value_08381q, 5), exchange) -ts_mean(ts_delta(anl40_turnoverrate, 1), 63) -log(divide(ts_mean(anl40_netturnoverrate, 90), pv87_holdings)) -group_neutralize(inverse(ts_mean(anl40_turnoverrate, 252)), industry) -group_neutralize(ts_zscore(anl40_turnoverrate, 252), industry) -group_neutralize(ts_mean(fnd28_ratesq_value_08631q, 5), exchange) -group_neutralize(sqrt(ts_mean(anl40_turnoverrate, 252)), industry) -group_neutralize(ts_mean(fnd28_wcratesq_value_08287q, 5), exchange) -group_neutralize(ts_mean(management_ethics_industry_rank, 126), "industry") -group_neutralize(ts_delay(anl40_turnoverrate, 63), industry) -group_neutralize(ts_mean(anl40_turnoverrate, 252), industry) - group_neutralize(ts_mean(pv87_price_volatility_estimate_mean, 252), industry) -group_zscore(anl40_turnoverrate, exchange) -group_neutralize(ts_mean(fnd28_growthratesa_value_08581a, 5), exchange) -group_neutralize(ts_mean(management_ethics_industry_rank, 252) - ts_mean(est_q_roe_low, 126), "industry") -group_neutralize(ts_mean(pv64_dif_fund_turnover, 5), exchange) -group_neutralize(ts_mean(fnd28_growthratesa_value_08606a, 5), exchange) -group_neutralize(ts_mean(fnd28_growthratesa_value_08615a, 5), exchange) -group_neutralize(ts_mean(management_ethics_subsector_rank, 252) + ts_mean(est_q_roe_mean, 63), "subsector") -ts_scale(management_ethics_industry_percentile, 126) -group_neutralize(ts_mean(pv48_r3000e_amount_change_value, 5), exchange) -ts_mean(management_ethics_industry_percentile, 252) * ts_mean(est_12m_roe_median, 126) -group_neutralize(ts_mean(fnd28_ratesq_value_08306q, 5), exchange) -group_neutralize(ts_mean(fnd28_ratesq_value_08636q, 5), exchange) -ts_mean(divide(ts_delta(total_shareholding_value, 1), ts_delay(total_shareholding_value, 1)), 63) -hump(pv87_holdings, 0.02) -ts_mean(management_ethics_standards_score, 252) * ts_mean(est_12m_roe_high, 252) +ts_covariance(fnd23_annfv1a_nimv, pv103_lasz_mean, 5) +ts_covariance(earning_fiscal_year_end, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(mdl77_2mqf_niper, pv64_dif_fund_creation_unit_size, 20) +ts_covariance(quarterly_retained_earnings_total, pv87_interval_asksize_median, 5) +ts_covariance(pv87_weightedavg60_group_ess_earnings, pv81_stlh, 20) +ts_covariance(mdl77_2gdna_yoychgaa, mdl177_2_liquidityriskfactor_ohlsonscore, 250) +ts_covariance(fnd72_pit_or_is_a_is_interest_inc, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(fnd28_wsbshtq_value_01551q, pv64_trr_stal_cur_mkt_cap, 20) +ts_covariance(mdl177_v1_400_sue, pv64_dif_stal_fund_creation_unit_size, 5) +ts_covariance(earning_time_type, pv104_lasz_mean, 5) +ts_covariance(anl10_ebismun_2qf_2231, pv52_yse_national_order_size_code, 250) +ts_covariance(mdl264_2l_qic, pv104_tasz_mean, 5) +ts_covariance(mdl262_rasv2splitprofitabilityebitd_q_profitability9, pv87_interval_asksize_median, 60) +ts_covariance(anl14_stddev_opp_fy1, oth551_resret_size, 250) +ts_covariance(mdl116_epsyld_fy2_trendpredict_model_mada, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 20) +ts_covariance(fnd65_us5000_cusip_fqsurstd60dlag, pv81_sasl, 250) +ts_covariance(mdl262_deltapredictni_a_mae, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(pv20_ebt_indicator_n_feature4, pv87_interval_bidsize_std, 5) +ts_covariance(anl10_ebspast_det_excflag, pv104_masz_mean, 5) +ts_covariance(pv20_eps_indicator_4_feature2, pv104_hasz_mean, 20) +ts_covariance(fnd65_us5000_cusip_pfcmtt, pv103_masz_mean, 5) +ts_covariance(mdl262_trkdpitpredictiveebitda_prediction, oth551_r2_size, 250) +ts_covariance(fnd28_ishta_value_01751a, pv64_dif_fund_creation_unit_size, 20) +ts_covariance(est_12m_pre_mean_3mth_ago, pv64_dif_stal_fund_creation_unit_size, 5) +ts_covariance(anl10_ebsfq1_consensus, oth551_r2_size, 250) +ts_covariance(fnd23_icsm_mvb_fbbs, pv103_sasz_mean, 5) +ts_covariance(max_ebit_guidance, mdl230_allcap_sedol_ohlsonscore, 20) +ts_covariance(anl44_orig_en_pretaxprofit_rep_prevalue, pv81_zsbt, 250) +ts_covariance(mdl77_2liquidityriskfactor_impduration, pv103_tlrt_topofbook_tlrt_mean, 60) +ts_covariance(annual_retained_earnings_total_fast_d1, pv103_maus_mean, 60) +ts_covariance(mdl264_usa_compustat_q1_dl8_miiq_l2, pv103_maus_mean, 250) +ts_covariance(anl10_gpspast_det_analyst_1321, pv81_zsbl, 5) +ts_covariance(mdl230_us5000_cusip_pspeghc, pv52_yse_arca_order_size_code, 60) +ts_covariance(anl82_opry_profitability_profitability12, pv87_interval_bidsizeinterval_slippage_rankcorrel, 250) +ts_covariance(anl10_ebsnormal_decrease_fy2, pv64_dif_fund_creation_unit_size, 60) +ts_covariance(mdl264_epspi_class, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 5) +ts_covariance(anl14_stddev_ntp_fp1, pv87_interval_asksize_std, 20) +ts_covariance(earnings_announcement_time_of_day_fast_d1, pv52_asdaq_bx_order_size_code, 20) +ts_covariance(pv87_epsyld_gro_mean, pv103_1m_mbds_mean, 20) +ts_covariance(fnd65_totalcap_cusip_mad3yttmni, pv87_interval_asksize_skewness, 60) +ts_covariance(anl15_ebtgics_ind_12_m_1m_chg, pv81_trlm, 20) +ts_covariance(fnd72_pit_or_cr_a_net_inc_growth, pv52_yse_national_order_size_code, 20) +ts_covariance(anl69_eps_best_eps_lo, pv103_1m_mlrt_mean, 5) +ts_covariance(pv87_2_epsr_qf_matrix_all_high, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(mdl230_totalcap_cusip_rev6fy2, pv81_zsbl, 5) +ts_covariance(fnd28_wcfsq1nbf_value_01401q, mdl248_avg_txn_val, 20) +ts_covariance(mdl177_2_globaldevnorthamerica_v502_fc_epsrm, pv52_asdaq_order_size_code, 250) +ts_covariance(fnd65_totalcap_cusip_mpgghcy3_, pv81_zsbt, 5) +ts_covariance(mdl26_p_yld_pct_stm_fy1, pv104_hbsz_mean, 60) +ts_covariance(mdl230_totalcap_cusip_epschgetr, oth551_resret_size, 20) +ts_covariance(anl69_sales_best_eeps_nxt_yr, pv103_1m_maks_mean, 60) +ts_covariance(anl82_ebty_deltaprofitability_profitability11, fnd72_pit_or_cr_q_debt_to_mkt_cap, 20) +ts_covariance(anl15_cpsgics_s_18_m_pe, pv64_trr_cur_mkt_cap, 5) +ts_covariance(mdl109_d_mtl_dlyspe, pv104_tbsz_mean, 5) +ts_covariance(fnd3_q_ebitda, pv87_interval_bidsizeinterval_volume_correlation, 250) +ts_covariance(anl10_nerpast_det_indicator_913, pv64_dif_fund_creation_unit_size, 5) +ts_covariance(anl4_epsr_value, pv103_mbus_mean, 20) +ts_covariance(anl15_ebt_ind_cal_fy3_6m_chg, fnd65_us5000_cusip_ohlsonscore, 250) +ts_covariance(anl10_epsinnovation_score_fy1, pv103_tbsz_mean, 5) +ts_covariance(mdl264_usa_compustat_q1_dl8_nopiq_l4, pv64_trr_stal_cur_mkt_cap, 250) +ts_covariance(anl49_1stfiscalquarterearningspershare, pv87_interval_bidsize_mean, 250) +ts_covariance(pv87_2_pretaxprofit_rep_af_matrix_p1_chngratio_number, pv87_interval_bidsize_skewness, 250) +ts_covariance(pv87_daily_qtr_matrix_net_income_gaap_consensus_mean_numdown, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(anl10_entfy1_pred_surps_v1_2442, pv87_interval_bidsize_median, 20) +ts_covariance(count_negative_profitability_question, pv104_masz_mean, 60) +ts_covariance(fnd13_cinx, fund_total_size, 20) +ts_covariance(fnd28_annualgrowth_value_08601a, pv81_zsbl, 5) +ts_covariance(mdl26_v14_srprs_pct_lst_y_rnngs, pv87_interval_asksizeinterval_slippage_correlation, 250) +ts_covariance(anl10_gpssmun_1qf_2624, pv103_mbsz_mean, 5) +ts_covariance(fnd72_s_pit_or_cr_q_trail_12m_inc_bef_xo_item, pv103_tbds_mean, 20) +ts_covariance(fnd7_ointfund_qipspe, pv52_yse_arca_order_size_code, 20) +ts_covariance(mdl262_eps_oeps12_mae, pv104_masz_mean, 5) +ts_covariance(pv87_net_income_normalized_of_estimates_scale, pv87_interval_asksize_mean, 5) +ts_covariance(pv20_indicator_4_feature8, mdl77_liquidityriskfactor_ohlsonscore, 20) +ts_covariance(anl10_nersmun_1yf_2417, pv87_interval_bidsize_std, 60) +ts_covariance(anl15_dps_gr_cal_fy1_pe, oth551_r2_size, 5) +ts_covariance(mdl262_rasv2splitprofitabilityebitd_q_profitability10, pv103_1m_maks_mean, 250) +ts_covariance(mdl77_2valuemomemtummodel_reportedearningsmomentummodule, company_size_sentiment_score, 250) +ts_covariance(star_eq_ope_rank, pv98_daily_mean_taks_taks_mean, 5) +ts_covariance(anl10_nerrevise_ratio_to_consensus_fq2_2016, pv103_sbsz_mean, 20) +ts_covariance(earning_time_type_fast_d1, pv103_hbsz_mean, 20) +ts_covariance(pv87_2_pretaxprofit_qf_matrix_all_chngratio_high, pv104_tbsz_mean, 250) +ts_covariance(oth460_usa_compustat_q1_dl8_nopiq_l4, pv103_mlrt_topofbook_mlrt_mean, 250) +ts_covariance(mdl262_che_profitability_profitability9, pv104_mlrt_mean, 5) +ts_covariance(pv87_net_income_normalized_actual, pv103_tlrt_topofbook_tlrt_mean, 20) +ts_covariance(est_q_eps_std_3mth_ago, pv87_interval_bidsize_skewness, 250) +ts_covariance(anl10_ebsfy2_pred_surps_v0, pv87_interval_asksizeinterval_bidsize_rankcorrel, 60) +ts_covariance(anl10_epsinnovate_decrease_fq2, pv52_yse_national_order_size_code, 20) +ts_covariance(mdl26_trailing_4_quarter_pe, pv103_mbsz_mean, 20) +ts_covariance(anl44_netprofit_gaap_best_cur_fiscal_qtr_period, company_offer_total_size, 60) +ts_covariance(est_12m_opr_std, pv87_interval_asksizeinterval_slippage_rankcorrel, 20) +ts_covariance(anl15_ebtgics_gr_cal_fy2_gro, oth551_r2_size, 60) +ts_covariance(mdl262_cheq_profitability_profitability2, pv52_yse_national_order_size_code, 5) +ts_covariance(long_term_dividend_payout_ratio, company_offer_total_size, 60) +ts_covariance(anl49_netprofit, pv81_trlm, 20) +ts_covariance(anl14_high_eps_fp5, pv103_laks_mean, 60) +ts_covariance(rsk62_beta_5_100_spe, pv87_interval_bidsize_median, 5) +ts_covariance(pv87_pos_earnings_matrix_bee_sum, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(oth432_rasv2splitprofitabilityebt_ttm_profitability5, mdl230_totalcap_cusip_ohlsonscore, 20) +ts_covariance(pv20_gps_indicator_q_feature8, oth551_beta_size, 5) +ts_covariance(mdl262_rasv2splitprofitabilityfcf_q_profitability9, nws31_d1_bodysize, 60) +ts_covariance(fnd2_itxreexftfedstyitxrt, mdl230_allcap_sedol_ohlsonscore, 60) +ts_covariance(pv20_pre_indicator_n_feature10, pv104_tlrt_mean, 250) +ts_covariance(pv87_2_operatingprofit_qf_matrix_all_chngratio_mean, pv81_zsbm, 250) +ts_covariance(fnd6_cptmfmq_opepsq, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(pv87_epsyld_ltm_d_mean, pv103_htsz_mean, 60) +ts_covariance(fnd3_Q_interestincome, pv103_sbsz_mean, 5) +ts_covariance(pv20_ebt_indicator_7_feature2, pv104_masz_mean, 60) +ts_covariance(pv87_prv2_expavg60_group_event_sentiment_score_earnings, pv103_hasz_mean, 250) +ts_covariance(mdl26_v14_nnlyst_rvsng_dwn_fq1_rnngs_7, pv64_trr_stal_cur_mkt_cap, 5) +ts_covariance(pv20_ebt_indicator_7_feature6, pv87_interval_asksize_skewness, 60) +ts_covariance(mdl211_saly_deltaprofitability_profitability9, fnd31_ohlsonscore, 250) +ts_covariance(mdl230_us5000_cusip_ebitdadebtchg, fnd31_ohlsonscore, 20) +ts_covariance(pv87_2_eps_af_matrix_p1_chngratio_high, rsk70_mfm2_usfast_size, 20) +ts_covariance(anl14_median_ebit_fy4, pv87_interval_asksize_numintervalsincehigh, 250) +ts_covariance(fnd28_bdea_value_18854a, pv81_sbsl, 60) +ts_covariance(mdl211_preq_profitability_profitability7, company_size_sentiment_score, 5) +ts_covariance(anl10_ebiinnovation_score_fy2_2589, fnd72_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(pv87_2_netprofit_af_matrix_all_dts, pv103_1m_tlrt_mean, 250) +ts_covariance(fnd65_us5000_cusip_divcov, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(pv87_daily_ann_matrix_r1_net_income_normalized_consensus_mean_numup, pv52_yse_arca_order_size_code, 5) +ts_covariance(anl10_nersmun_2yf_2416, pv87_interval_bidsize_skewness, 60) +ts_covariance(anl4_qfv4_eps_number, pv81_stlh, 5) +ts_covariance(pv20_ebt_indicator_2_feature9, pv104_tasz_mean, 60) +ts_covariance(anl82_preq_q4_madp, pv103_lasz_mean, 250) +ts_covariance(mdl26_rvsnclstr_vg_rvsn_pr_fq1_rnngs, mdl77_liquidityriskfactor_ohlsonscore, 5) +ts_covariance(pe_ratio_relative_component_rank_v2, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(fnd72_s_pit_or_cr_q_com_eqy_to_tot_asset, pv103_tlrt_topofbook_tlrt_mean, 250) +ts_covariance(mdl262_rasv2splitprofitabilityebit_ttm_profitability12, pv52_yse_arca_order_size_code, 250) +ts_covariance(anl15_ebt_gr_cal_fy3_cos, im_shares_transacted, 60) +ts_covariance(pv87_2_pretaxprofit_qf_matrix_all_chngratio_median, pv87_interval_bidsizeinterval_slippage_rankcorrel, 60) +ts_covariance(mdl26_7dy_bld_stmt_flg_fq4_rnngs, pv104_lsbs_mean, 250) +ts_covariance(oth460_ttax_l3, pv87_interval_bidsizeinterval_volume_correlation, 60) +ts_covariance(mdl26_nm_stm_nlysts_fy2_rnngs, mdl230_allcap_sedol_ohlsonscore, 250) +ts_covariance(anl15_ebtgics_ind_18_m_cos_dn, pv103_maus_mean, 60) +ts_covariance(mdl177_2_earningsqualityfactor_salegpm, pv104_lsbs_mean, 5) +ts_covariance(act_12m_prr_value, pv87_interval_bidsize_mean, 60) +ts_covariance(fnd3_A_nic, pv87_interval_asksize_numintervalsincehigh, 60) +ts_covariance(fnd31_devnorthamericaadditionalfactor4_divgp, pv81_zsbt, 250) +ts_covariance(fnd3_aacctadj__earbeforetaxes, pv103_tasz_mean, 250) +ts_covariance(anl49_backfill_estdcurrentperatio, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(anl10_nerrevise_value_fq1_2012, pv87_interval_asksizeinterval_slippage_correlation, 60) +ts_covariance(anl15_ebt_gr_18_m_cos_dn, pv104_hbsz_mean, 60) +ts_covariance(anl82_delta_preq_q4_predict, pv81_zsbt, 250) +ts_covariance(anl14_stddev_ebit_fp1, pv81_sasl, 60) +ts_covariance(mdl77_historicalgrowthfactor_pspeghc, oth567_deltascore_company_size_432, 20) +ts_covariance(anl14_high_ntprep_fy3, mdl230_us5000_cusip_ohlsonscore, 5) +ts_covariance(pv20_sal_indicator_2_feature12, mdl77_2liquidityriskfactor_ohlsonscore, 60) +ts_covariance(mdl177_liquidityriskfactor_mad3yttmni_alt, company_offer_total_size, 60) +ts_covariance(oth432_ebit_compustatdeltapredict_annual_funda_predict, pv103_mbsz_mean, 5) +ts_covariance(quarterly_earnings_before_tax_total, pv103_htsz_mean, 20) +ts_covariance(pv87_2_operatingprofit_af_matrix_p1_dts, pv98_tbds_mean, 60) +ts_covariance(fnd28_newa1_value_08385a, pv103_1m_mbds_mean, 250) +ts_covariance(mdl26_lw_stmt_chng_fy1_rnngs_30, pv87_interval_bidsize_mean, 5) +ts_covariance(pv20_eps_indicator_8_feature10, pv81_trlt, 250) +ts_covariance(pv20_opr_indicator_o_feature11, pv87_interval_asksize_std, 60) +ts_covariance(act_q_gps_surprisestd, fund_total_size, 5) +ts_covariance(pv20_net_indicator_q_feature7, pv103_laks_mean, 250) +ts_covariance(mdl230_allcap_sedol_aor, pv81_trlt, 250) +ts_covariance(mdl177_2_globaldevnorthamerica_v502_wcacc, pv87_interval_asksize_mean, 5) +ts_covariance(fnd65_allcap_sedol_bmpo, pv103_masz_mean, 250) +ts_covariance(fnd7_ointfund_qiim, pv103_sbps_mean, 250) +ts_covariance(fnd65_totalcap_cusip_rev3my1std, mdl248_avg_txn_val, 5) +ts_covariance(fnd28_wcfsa1_value_01503a, mdl230_allcap_sedol_ohlsonscore, 250) +ts_covariance(anl15_ebtgics_ind_cal_fy1_6m_chg, company_offer_total_size, 250) +ts_covariance(anl14_median_ntp_fy5, pv81_zsah, 250) +ts_covariance(mdl177_valueanalystmodel_qva_earnval_alt, oth137_avg_txn_val, 250) +ts_covariance(pv87_webv2_expavg20_group_css_earnings, mdl177_2_liquidityriskfactor_ohlsonscore, 60) +ts_covariance(fnd72_s_pit_or_bs_q_2_bs_other_cur_asset_less_prepay, oth567score_company_size, 60) +ts_covariance(mdl77_fa_pge_cf, pv52_yse_order_size_code, 250) +ts_covariance(mdl230_allcap_sedol_perg, fnd14_zs_lf_nlf_drp_ncr, 250) +ts_covariance(anl14_numofests_ntp_fy2, pv87_interval_bidsize_numintervalsincelow, 250) +ts_covariance(oth432_rasv2splitprofitabilityni_ttm_profitability1, pv81_stlh, 250) +ts_covariance(mdl264_usa_compustat_q1_dl8_epspiq_l1, mdl230_us5000_cusip_ohlsonscore, 5) +ts_covariance(mdl77_2mqf_yoychggpm, fnd65_totalcap_cusip_ohlsonscore, 60) +ts_covariance(anl82_delta_netq_q1_predict, pv81_lasz, 250) +ts_covariance(est_12m_gps_std_28d, pv104_lbsz_mean, 20) +ts_covariance(pv20_eps_indicator_1_feature2, pv87_interval_asksize_median, 5) +ts_covariance(fnd72_pit_or_is_q_is_tot_cash_com_dvd, pv87_interval_bidsize_median, 60) +ts_covariance(mdl262_che_profitability_profitability5, pv98_quote_size_mean, 5) +ts_covariance(fnd28_newa2_value_09216a, nws31_d1_bodysize, 60) +ts_covariance(mdl230_us5000_cusip_y5speq4rqsr, pv104_lbsz_mean, 20) +ts_covariance(mdl264_1l_qaeclg, oth567score_company_size_358, 250) +ts_covariance(mdl77_2ccacw, pv98_quote_size_mean, 5) +ts_covariance(mdl264_sani_l3, pv87_interval_bidsize_kurtosis, 60) +ts_covariance(mdl262_cheq_profitability_profitability3, pv103_lbsz_mean, 5) +ts_covariance(anl14_numofests_opp_fp1, fnd14_zs_lf_nlf_drp_ncr, 5) +ts_covariance(pv87_ann_matrix_net_income_gaap_estimate_high, pv52_yse_national_order_size_code, 250) +ts_covariance(mdl109_b_mtl_dlyspe, pv103_1m_mlrt_mean, 60) +ts_covariance(anl4_ptpr_number, pv52_asdaq_psx_order_size_code, 250) +ts_covariance(oth432_ninc_trkdpitdeltapredict_funda_mae, pv81_zsbm, 60) +ts_covariance(fnd17_ttmnichg, pv103_saps_mean, 5) +ts_covariance(est_q_opr_mean_28d, pv103_maks_topofbook_maks_mean, 20) +ts_covariance(anl10_ebiinnovation_score_fy2_2589, fnd65_allcap_sedol_ohlsonscore, 20) +ts_covariance(anl14_low_ntprep_fy2, pv103_laks_mean, 60) +ts_covariance(oth432_che_profitability_profitability2, pv103_sbps_mean, 20) +ts_covariance(fnd72_pit_or_cr_a_trail_12m_oper_inc, pv87_interval_asksizeinterval_bidsize_correlation, 5) +ts_covariance(oth460_usa_compustat_q1_dl8_epsfiq_l5, mdl177_2_liquidityriskfactor_ohlsonscore, 5) +ts_covariance(mdl264_1l_declg, fund_total_size, 5) +ts_covariance(mdl262_compustatpredictivetxtq_prediction, pv104_tbsz_mean, 250) +ts_covariance(pv20_opr_indicator_1_feature1, pv103_sbsz_mean, 60) +ts_covariance(anl44_second_en_netprofit_rep_coveredby, pv103_lasz_mean, 250) +ts_covariance(mdl26_rm02fy_prsprs_fy2_rnngs, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(pv87_daily_qtr_matrix_net_income_gaap_consensus_mean_numup, pv87_interval_bidsize_std, 20) +ts_covariance(mdl26_rm02fy_prsprs_fy2_rnngs, pv52_asdaq_order_size_code, 250) +ts_covariance(mdl262_deltapredictebitd_q_predict, pv103_mbds_topofbook_mbds_mean, 60) +ts_covariance(anl69_roe_expected_report_time, pv103_tbds_mean, 5) +ts_covariance(fnd72_s_pit_or_is_q_earn_for_common, pv87_interval_asksizeinterval_volume_correlation, 20) +ts_covariance(anl49_vector_depreciationdepletionamortization, pv103_tbsz_mean, 250) +ts_covariance(anl69_eps_best_eps, fnd72_pit_or_cr_a_debt_to_mkt_cap, 60) +ts_covariance(fnd89_major_11_31, pv81_sasl, 5) +ts_covariance(oth401_game_earning_smooth, oth567score_company_size, 60) +ts_covariance(anl49_valugaugeestimatingdifficultyrank, pv87_interval_asksize_std, 60) +ts_covariance(fnd65_us5000_cusip_min1yopmargin, pv81_zsbl, 60) +ts_covariance(anl14_mean_ntp_fy1, mdl177_2_liquidityriskfactor_ohlsonscore, 250) +ts_covariance(mdl230_us5000_cusip_ebitdadebt, pv64_dif_stal_fund_creation_unit_size, 60) +ts_covariance(pv87_2_operatingprofit_qf_matrix_all_low, mdl230_totalcap_cusip_ohlsonscore, 250) +ts_covariance(anl14_mean_ntprep_fp5, pv52_yse_national_order_size_code, 250) +ts_covariance(mdl177_2_earningsqualityfactor_saleeps, nws31_d1_bodysize, 20) +ts_covariance(mdl211_saly_deltaprofitability_profitability9, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(mdl264_viat_l3, mdl230_allcap_sedol_ohlsonscore, 250) +ts_covariance(pv87_2_eps_qf_matrix_all_high, pv87_interval_asksizeinterval_bidsize_rankcorrel, 60) +ts_covariance(fnd23_intfvm_ipos, nws31_bodysize, 5) +ts_covariance(oth460_usa_compustat_q1_dl8_epspxq_l4, pv104_hbsz_mean, 60) +ts_covariance(pv87_2_operatingprofit_af_matrix_p1_chngratio_mean, pv103_sbps_mean, 5) +ts_covariance(pv87_simpleavg20_group_css_earnings, pv87_interval_asksize_std, 60) +ts_covariance(pv20_gps_indicator_n_feature5, mdl77_liquidityriskfactor_ohlsonscore, 60) +ts_covariance(mdl354_sector_pt2net_margin, pv87_interval_asksize_median, 60) +ts_covariance(pv87_2_operatingprofit_qf_matrix_p1_dts, pv81_zsbm, 5) +ts_covariance(mdl77_2spe1yfvc_cf, pv87_interval_bidsizeinterval_slippage_correlation, 250) +ts_covariance(anl15_ebt_ind_cal_fy1_1m_chg, rsk70_mfm2_usfast_size, 5) +ts_covariance(pv20_net_indicator_n_feature3, pv64_dif_fund_creation_unit_size, 250) +ts_covariance(pv87_2_pretaxprofit_rep_af_matrix_all_chngratio_high, pv81_zsbh, 250) +ts_covariance(anl82_oprq_profitability_profitability1, pv52_yse_national_order_size_code, 20) +ts_covariance(oth432_acae_q_profitability_profitability9, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(anl15_ebt_gr_18_m_mean, oth567score_company_size, 250) +ts_covariance(fnd28_wcfsa1_value_01266a, pv103_tbds_mean, 5) +ts_covariance(pv20_net_indicator_q_feature0, company_offer_total_size, 60) +ts_covariance(fnd72_pit_or_cr_q_prof_margin, mdl230_totalcap_cusip_ohlsonscore, 250) +ts_covariance(mdl264_onet_l1, oth137_avg_txn_val, 20) +ts_covariance(mdl211_oprq_deltaprofitability_profitability5, pv87_interval_bidsize_numintervalsincelow, 5) +ts_covariance(est_q_pre_std_4wks_ago, pv52_yse_american_order_size_code, 60) +ts_covariance(anl69_roa_expected_report_time, pv64_dif_stal_fund_creation_unit_size, 5) +ts_covariance(mdl77_ohistoricalgrowthfactor_speghc, pv87_interval_asksizeinterval_slippage_correlation, 20) +ts_covariance(fnd17_margin5yr, rsk70_mfm2_usfast_size, 20) +ts_covariance(fnd89_jones_accrual_pct_major_13, oth567score_company_size, 20) +ts_covariance(oth460_net_margin_l2, mdl177_2_liquidityriskfactor_ohlsonscore, 250) +ts_covariance(anl10_ebtrevise_ratio_to_consensus_fq2_1011, pv81_zsbl, 5) +ts_covariance(anl15_ebtgics_ind_cal_fy3_total, fund_total_size, 250) +ts_covariance(fnd72_pit_or_cr_a_prof_margin, pv81_trlt, 20) +ts_covariance(anl14_stddev_ntp_fy1, pv103_sbsz_mean, 5) +ts_covariance(fnd31_qsg5additionalfactor3_backfilled_apg, pv103_sbps_mean, 250) +ts_covariance(mdl26_v14_mstchg_pct_f12m_rnngs_90, pv103_maks_topofbook_maks_mean, 20) +ts_covariance(mdl230_totalcap_cusip_pfgmtt, pv103_htsz_mean, 20) +ts_covariance(mdl138_in_3idp, pv52_yse_chicago_order_size_code, 20) +ts_covariance(fnd65_totalcap_cusip_pe_wt, pv87_interval_bidsize_kurtosis, 250) +ts_covariance(oth553_ptg_wordcnt, pv52_yse_arca_order_size_code, 250) +ts_covariance(anl82_oprq_profitability_profitability10, pv103_mbds_topofbook_mbds_mean, 60) +ts_covariance(anl14_numofests_ebitda_fp4, pv104_masz_mean, 5) +ts_covariance(mdl262_txtq_compustatdeltapredict_funda_madp, fnd65_allcap_sedol_ohlsonscore, 250) +ts_covariance(anl44_netprofit_gaap_best_eeps_nxt_yr, pv104_lsas_mean, 60) +ts_covariance(mdl264_opepsq_l2, pv104_tasz_mean, 250) +ts_covariance(pv20_eps_indicator_2_feature0, nws31_bodysize, 5) +ts_covariance(fnd28_value_18841a, pv104_lbsz_mean, 20) +ts_covariance(mdl26_v14_nnlyst_rvsng_dwn_fy1_rnngs_14, pv104_tasz_mean, 60) +ts_covariance(fnd28_wcfsq1nbf_value_01706q, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(est_12m_opr_mean_3mth_ago, pv81_zsbm, 60) +ts_covariance(oth460_berry_l2, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(mdl211_salq_deltaprofitability_profitability7, pv87_interval_asksize_std, 60) +ts_covariance(est_q_ner_median_3mth_ago, pv103_masz_mean, 250) +ts_covariance(est_q_opr_num_28d, fund_total_size, 250) +ts_covariance(fnd72_s_pit_or_cr_q_trail_12m_eps, pv52_asdaq_order_size_code, 5) +ts_covariance(anl82_nety_profitability_profitability10, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(anl15_ebtgics_s_fy3_cos_dn, pv87_interval_asksizeinterval_volume_correlation, 60) +ts_covariance(pv87_2_netprofit_rep_af_matrix_all_low, pv103_mbsz_mean, 60) +ts_covariance(anl14_high_ntprep_fy5, fnd65_totalcap_cusip_ohlsonscore, 5) +ts_covariance(fnd89_jones_accrual_major_11, pv87_interval_asksize_mean, 60) +ts_covariance(est_ptpr, pv52_yse_chicago_order_size_code, 60) +ts_covariance(mdl262_compustat_models_profitability7, pv103_mlrt_topofbook_mlrt_mean, 250) +ts_covariance(mdl211_ebtq_profitability_profitability5, pv103_mbds_topofbook_mbds_mean, 20) +ts_covariance(mdl262_compustatpredictiveoiadpq_mad_pred, pv104_tbsz_mean, 60) +ts_covariance(fnd72_q1_geo_grow_ebitda_cap_exp_to_int, pv81_trlm, 250) +ts_covariance(mdl26_v14_prsprise_pct_fq2_earnings, rsk70_mfm2_usfast_size, 250) +ts_covariance(mdl77_omomemtumanalystmodel_qma_repearnmom, pv87_interval_asksizeinterval_slippage_correlation, 20) +ts_covariance(mdl262_sbda_a_profitability_profitability2, pv103_laks_mean, 20) +ts_covariance(fnd3_a__earbeforetaxes, pv52_yse_order_size_code, 250) +ts_covariance(fnd6_newa2v1300_ni, pv104_mlrt_mean, 60) +ts_covariance(pv87_2_epsr_af_matrix_all_chngratio_low, pv81_zsbl, 5) +ts_covariance(pv87_2_epsr_af_matrix_p1_dts, pv103_tasz_mean, 5) +ts_covariance(mdl262_oiadpq_profitability_profitability3, pv103_1m_tlrt_mean, 5) +ts_covariance(anl10_nerinnovate_increase_fy1_1995, mdl230_us5000_cusip_ohlsonscore, 5) +ts_covariance(oth460_ciac_class, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(fnd72_pit_or_cr_a_ev_to_t12m_ebitda, pv103_laks_mean, 250) +ts_covariance(oth460_unopincq_l3, fund_total_size, 250) +ts_covariance(eps_fiscal_quarter, nws31_d1_bodysize, 60) +ts_covariance(anl14_numofests_ntprep_fp1, pv87_interval_asksize_mean, 250) +ts_covariance(anl15_ebtgics_gr_cal_fy1_3m_chg, pv104_masz_mean, 250) +ts_covariance(fnd72_s_pit_or_is_q_is_pension_expense_income, pv87_interval_asksizeinterval_volume_correlation, 5) +ts_covariance(anl14_low_ntprep_fy2, pv87_interval_asksizeinterval_bidsize_correlation, 250) +ts_covariance(anl15_ebtgics_s_cal_fy3_pe, pv104_insm_mean, 20) +ts_covariance(fnd6_cibegni, pv52_yse_national_order_size_code, 250) +ts_covariance(rsk62_id_spe, pv104_tasz_mean, 250) +ts_covariance(pv20_indicator_0_feature0_121, pv103_lbsz_mean, 5) +ts_covariance(pv20_ebt_indicator_q_feature11, oth567_deltascore_company_size_432, 60) +ts_covariance(mdl264_uopiq_class, fnd72_pit_or_cr_q_debt_to_mkt_cap, 250) +ts_covariance(pv87_web_weightedavg60_group_v2_0_1_css_earnings, mdl230_totalcap_cusip_ohlsonscore, 20) +ts_covariance(pv87_neg_earnings_matrix_css_sum, pv103_1m_maks_mean, 60) +ts_covariance(oth432_accruals_oeps12_predict, pv52_yse_american_order_size_code, 60) +ts_covariance(anl69_dps_expected_report_time, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(research_development_expense_reported_value, pv103_laks_mean, 250) +ts_covariance(fnd23_annfvmfm_rltr, pv103_lask_topofbook_lask_mean, 250) +ts_covariance(mdl77_historicalgrowthfactor_chg3yepsast, pv103_1m_mlrt_mean, 250) +ts_covariance(count_neutral_profitability_summary_fast_d1, pv87_interval_asksizeinterval_slippage_rankcorrel, 20) +ts_covariance(fnd6_txs, pv52_yse_arca_order_size_code, 250) +ts_covariance(fnd3_aacctadj_ebit, pv52_yse_national_order_size_code, 20) +ts_covariance(pv20_gps_indicator_7_feature11, pv87_interval_asksizeinterval_bidsize_correlation, 250) +ts_covariance(pv20_pre_indicator_6_feature10, fund_total_size, 20) +ts_covariance(anl82_oprq_q4_madp, fnd31_ohlsonscore, 20) +ts_covariance(pv87_2_netprofit_af_matrix_p1_chngratio_std, pv104_hbsz_mean, 60) +ts_covariance(mdl262_txtq_compustatdeltapredict_funda_predict, pv98_tbds_mean, 5) +ts_covariance(anl82_salq_profitability_profitability1, pv103_maus_mean, 5) +ts_covariance(pretax_income_total, pv104_tasz_mean, 250) +ts_covariance(oth460_uniamiq_l3, company_offer_total_size, 60) +ts_covariance(pv87_daily_ann_matrix_r1_net_income_normalized_consensus_mean_numnochangeunfiltered, oth567score_company_size, 250) +ts_covariance(oth432_oibdpq_profitability_profitability4, pv103_tbds_mean, 250) +ts_covariance(pv20_gps_indicator_9_feature8, oth551_beta_size, 60) +ts_covariance(mdl211_ebtq_deltaprofitability_profitability12, pv103_hasz_mean, 5) +ts_covariance(est_q_gps_mean_3mth_ago, nws31_bodysize, 60) +ts_covariance(fnd65_allcap_sedol_fqsurstd60dlag, pv98_daily_mean_taks_taks_mean, 5) +ts_covariance(fnd65_allcap_sedol_pspeghc, pv87_interval_asksize_mean, 20) +ts_covariance(pv20_eps_indicator_1_feature7, fund_total_size, 250) +ts_covariance(mdl77_earningsmomemtummodel_fc_fqsurstd, oth551_beta_size, 250) +ts_covariance(anl14_high_ebit_fp4, pv87_interval_bidsizeinterval_slippage_rankcorrel, 20) +ts_covariance(anl15_ebt_gr_cal_fy3_gro, pv103_masz_mean, 5) +ts_covariance(anl15_cpsgics_gr_cal_fy3_pe, pv81_msni, 20) +ts_covariance(gross_profit_total, pv103_tasz_mean, 250) +ts_covariance(mdl262_ninc_trkdpitdeltapredict_funda_mae, pv87_interval_asksizeinterval_bidsize_correlation, 5) +ts_covariance(pv20_pre_indicator_1_feature11, pv103_tbsz_mean, 60) +ts_covariance(pv20_opr_indicator_n_feature2, pv52_yse_order_size_code, 250) +ts_covariance(est_12m_ner_std_28d, pv81_lasz, 250) +ts_covariance(anl82_preq_profitability_profitability12, pv103_tbsz_mean, 250) +ts_covariance(pv20_gps_indicator_9_feature11, pv104_lsbs_mean, 20) +ts_covariance(mdl264_3l_21fspe, pv103_tbsz_mean, 250) +ts_covariance(pv20_net_indicator_n_feature6, pv52_yse_american_order_size_code, 20) +ts_covariance(mdl262_rasv2splitprofitabilityni_q_profitability3, pv64_trr_cur_mkt_cap, 250) +ts_covariance(mdl77_2deepvaluefactor_vesspem21f, pv103_sasz_mean, 5) +ts_covariance(anl15_ebtgics_ind_cal_fy3_3m_chg, pv103_1m_mlrt_mean, 20) +ts_covariance(pv20_opr_indicator_o_feature7, pv104_insm_mean, 5) +ts_covariance(anl14_high_ntp_fp2, pv87_interval_bidsizeinterval_volume_correlation, 20) +ts_covariance(oth432_deltapredictni_a_predict, mdl177_2_liquidityriskfactor_ohlsonscore, 20) +ts_covariance(anl4_epsr_high, nws31_d1_bodysize, 20) +ts_covariance(fnd72_s_pit_or_cr_q_ev_to_t12m_ebit, pv104_tlrt_mean, 20) +ts_covariance(mdl77_earningmomentumfactor_stdevfy1epsp, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(mdl262_predictiveebt_a_predict, mdl177_liquidityriskfactor_ohlsonscore_alt, 5) +ts_covariance(mdl177_valanalystmodel_qva_earnquality, pv52_asdaq_psx_order_size_code, 60) +ts_covariance(anl10_ebtfq1_smart_ests_v1_936, pv87_interval_bidsize_std, 60) +ts_covariance(fnd14_hiwater_incmst_net_income_fy, pv104_lsts_mean, 5) +ts_covariance(mdl211_ebty_deltaprofitability_profitability5, pv103_1m_mlrt_mean, 20) +ts_covariance(gross_profit_to_assets_ratio, pv98_tbds_mean, 250) +ts_covariance(ern6_actual_period, pv103_hasz_mean, 20) +ts_covariance(mdl77_liquidityriskfactor_impduration, pv52_asdaq_psx_order_size_code, 60) +ts_covariance(mdl262_deltapredictebt_q_predict, pv104_hasz_mean, 5) +ts_covariance(anl14_mean_eps_fp5, pv64_trr_cur_mkt_cap, 20) +ts_covariance(pv87_ann_matrix_net_income_normalized_estimate_low, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(pv20_ebt_indicator_4_feature7, pv52_asdaq_order_size_code, 250) +ts_covariance(mdl264_net_margin_l2, pv52_yse_arca_order_size_code, 60) +ts_covariance(fnd72_q1_inc_tax_exp_to_net_sales, pv103_lbsz_mean, 60) +ts_covariance(oth460_3l_qacf, pv104_tbsz_mean, 20) +ts_covariance(anl14_high_ebitda_fp5, pv104_lasz_mean, 250) +ts_covariance(pv20_ebt_indicator_q_feature5, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(mdl138_qpdi3_net_margin, mdl248_avg_txn_val, 5) +ts_covariance(mdl211_netq_profitability_profitability7, fund_total_size, 250) +ts_covariance(anl15_dps_gr_12_m_pe, nws31_d1_bodysize, 60) +ts_covariance(anl14_high_eps_fy2, pv87_interval_bidsize_skewness, 250) +ts_covariance(est_12m_ner_median, pv103_1m_tlrt_mean, 5) +ts_covariance(mdl262_sbda_a_profitability_profitability4, pv87_interval_asksize_numintervalsincehigh, 5) +ts_covariance(oth460_2l_eiuv, pv103_maus_mean, 5) +ts_covariance(anl82_opry_y1_madp, pv64_trr_cur_mkt_cap, 60) +ts_covariance(anl10_ebiinnovate_decrease_fq2_2606, pv81_zsah, 250) +ts_covariance(fnd7_ointfund_rq21hsc, company_offer_total_size, 5) +ts_covariance(fnd89_csjones_industry_major_14, pv87_interval_bidsize_skewness, 20) +ts_covariance(anl15_bps_ind_12_m_pe, oth551_resret_size, 60) +ts_covariance(fnd65_allcap_sedol_lagegp, pv104_lasz_mean, 20) +ts_covariance(mdl262_txtq_compustatdeltapredict_funda_mada, im_shares_transacted, 5) +ts_covariance(mdl230_us5000_cusip_altmanz, pv103_htsz_mean, 20) +ts_covariance(anl49_backfill_typeofearningspershare, pv104_tbsz_mean, 20) +ts_covariance(anl49_earningspershare, pv103_mbus_mean, 250) +ts_covariance(oth432_txtq_mae, oth551_resret_size, 60) +ts_covariance(fnd28_wsfsq_value_01451q, company_offer_size_value, 5) +ts_covariance(pv20_ebt_indicator_4_feature7, fnd72_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(pv20_ebt_indicator_7_feature2, pv87_interval_bidsize_kurtosis, 5) +ts_covariance(anl82_saly_deltaprofitability_profitability8, fnd72_pit_or_cr_a_debt_to_mkt_cap, 60) +ts_covariance(pe_ratio_relative_component_rank, company_size_sentiment_score, 250) +ts_covariance(est_q_eps_std_4wks_ago, pv87_interval_bidsize_skewness, 5) +ts_covariance(anl82_netq_deltaprofitability_profitability2, mdl230_totalcap_cusip_ohlsonscore, 20) +ts_covariance(pv20_pre_indicator_8_feature11, pv103_tbsz_mean, 250) +ts_covariance(mdl77_ooearningsmomemtummodel_fc_y2repsg, pv87_interval_asksizeinterval_slippage_correlation, 60) +ts_covariance(pv87_2_operatingprofit_qf_matrix_p1_median, pv52_asdaq_bx_order_size_code, 5) +ts_covariance(anl14_high_eps_fy4, company_size_sentiment_score, 20) +ts_covariance(mdl26_mstchg_pct_f12m_rnngs_14, pv52_asdaq_order_size_code, 5) +ts_covariance(pv20_ebt_indicator_6_feature6, pv103_lbsz_mean, 5) +ts_covariance(mdl77_omomemtumanalystmodel_qma_mktresponse, pv64_dif_stal_fund_creation_unit_size, 250) +ts_covariance(mdl211_saly_profitability_profitability5, mdl177_liquidityriskfactor_ohlsonscore_alt, 60) +ts_covariance(oth432_rasv2splitprofitabilityebt_ttm_profitability4, pv87_interval_bidsize_numintervalsincelow, 20) +ts_covariance(pv20_gps_indicator_1_feature8, pv103_tbsz_mean, 250) +ts_covariance(anl15_ebt_gr_18_m_6m_chg, rsk70_mfm2_usfast_size, 60) +ts_covariance(mdl230_totalcap_cusip_spe2yfvc_cf, fnd31_ohlsonscore, 20) +ts_covariance(mdl230_allcap_sedol_saleeps, fund_total_size, 20) +ts_covariance(pv20_sal_indicator_p_feature1, pv87_interval_asksizeinterval_bidsize_rankcorrel, 5) +ts_covariance(anl14_median_ntp_fy5, nws31_d1_bodysize, 5) +ts_covariance(oth432_saleq_profitability_profitability9, pv98_tbds_mean, 20) +ts_covariance(fnd65_us5000_cusip_chgroepct, oth137_avg_txn_val, 250) +ts_covariance(pv87_2_netprofit_rep_qf_matrix_p1_low, pv104_masz_mean, 250) +ts_covariance(mdl262_che_profitability_profitability2, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 5) +ts_covariance(mdl211_preq_deltaprofitability_profitability1, pv87_interval_asksize_kurtosis, 250) +ts_covariance(anl82_opry_deltaprofitability_profitability3, pv104_mbsz_mean, 5) +ts_covariance(mdl177_2_historicalgrowthfactor_chg3yepsp, oth567_deltascore_company_size_432, 250) +ts_covariance(fnd72_s_pit_or_is_a_is_rd_expend, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(mdl262_deltapredictebit_q_predict, pv81_zsat, 5) +ts_covariance(fnd6_newa1v1300_ibadj, oth567score_company_size_358, 20) +ts_covariance(anl82_preq_deltaprofitability_profitability11, company_offer_total_size, 20) +ts_covariance(anl14_high_epsrep_fy3, pv103_mbus_mean, 60) +ts_covariance(fnd31_qsg5additionalfactor3_backfilled_rev6fy2, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(anl82_delta_preq_q2_predict, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 20) +ts_covariance(fnd7_ointfund_qipon, pv103_lbsz_mean, 5) +ts_covariance(anl10_ebtfq2_pred_surps_v0_964, pv103_1m_mlrt_mean, 5) +ts_covariance(act_12m_opr_value, pv98_quote_size_mean, 5) +ts_covariance(pv20_gps_indicator_6_feature10, pv103_maus_mean, 60) +ts_covariance(pv87_ann_matrix_net_income_normalized_estimate_median, pv81_lasz, 5) +ts_covariance(anl69_roe_expected_report_dt, pv52_yse_american_order_size_code, 60) +ts_covariance(mdl354_group_pt12yf_dlyspe, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(fnd28_wcishta_value_18189a, pv103_taks_mean, 20) +ts_covariance(pv20_pre_indicator_3_feature0, pv87_interval_bidsize_median, 250) +ts_covariance(fnd7_ointhstfundfn_hfqspepo, fnd65_totalcap_cusip_ohlsonscore, 60) +ts_covariance(mdl211_nety_y1_mada, mdl177_2_liquidityriskfactor_ohlsonscore, 20) +ts_covariance(oth432_deltapredictebitd_a_mae, pv103_lasz_mean, 5) +ts_covariance(fnd72_a2_retention_ratio, fund_total_size, 250) +ts_covariance(mdl77_ooearningsmomemtummodel_fc_numrevy1, pv81_stlh, 250) +ts_covariance(fnd65_us5000_cusip_aoer, pv103_mlrt_topofbook_mlrt_mean, 250) +ts_covariance(mdl77_put_put_indepsp, pv104_tasz_mean, 5) +ts_covariance(mdl77_momemtumanalystmodel_qma_composite, fnd65_allcap_sedol_ohlsonscore, 20) +ts_covariance(mdl262_acae_q_profitability_profitability8, pv103_tbsz_mean, 60) +ts_covariance(mdl262_niq_compustatdeltapredict_funda_mada, pv87_interval_asksizeinterval_slippage_correlation, 5) +ts_covariance(oth460_ibadjq_l3, pv81_stsl, 20) +ts_covariance(oth432_rasv2splitprofitabilityfcf_ttm_profitability3, mdl77_liquidityriskfactor_ohlsonscore, 60) +ts_covariance(mdl26_bld_stmt_flg_fq2_rnngs, fnd65_totalcap_cusip_ohlsonscore, 60) +ts_covariance(mdl26_mn_f_rvsnclstr_nlysts_fy2_rnngs, oth567_deltascore_company_size_432, 20) +ts_covariance(anl4_netprofit_mean, pv103_maks_topofbook_maks_mean, 250) +ts_covariance(anl82_ebtq_deltaprofitability_profitability5, oth567score_company_size_358, 20) +ts_covariance(oth432_compustatpredictiveepsfiq_mad_pred, pv87_interval_asksize_mean, 5) +ts_covariance(mdl262_oibdpq_profitability_profitability8, pv103_tbds_mean, 250) +ts_covariance(mdl77_2min2ygrossmargin, oth137_avg_txn_val, 20) +ts_covariance(mdl177_2_liquidityriskfactor_oplev, pv87_interval_asksize_kurtosis, 250) +ts_covariance(fnd72_pit_or_cr_a_com_eqy_to_tot_asset, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(mdl177_historicalgrowthfactor_pctchg3yeps, pv81_trlt, 20) +ts_covariance(investment_income_nonoperating, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(mdl264_viat_class, pv81_zsbh, 60) +ts_covariance(ebit_reported_value, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(mdl77_oindustryrrelativevaluefactor_curindcoreepsp_, mdl77_2liquidityriskfactor_ohlsonscore, 5) +ts_covariance(fnd28_pftlta_value_08365a, pv103_1m_maks_mean, 250) +ts_covariance(fnd65_totalcap_cusip_mpoghc, pv104_tasz_mean, 5) +ts_covariance(fnd28_statisticsa_value_05290a, pv103_masz_mean, 60) +ts_covariance(oth432_deltapredictebt_a_predict, oth551_r2_size, 20) +ts_covariance(mdl77_valuemomemtummodel_earningsqualitymodule, pv52_yse_arca_order_size_code, 5) +ts_covariance(pv20_net_indicator_8_feature12, pv104_lbsz_mean, 20) +ts_covariance(gross_profit_current, pv81_stsl, 20) +ts_covariance(mdl26_nnlyst_rvsng_p_fy1_rnngs_7, mdl248_avg_txn_val, 60) +ts_covariance(mdl26_stm_f12m_rnngs, pv103_1m_mbds_mean, 5) +ts_covariance(fnd65_us5000_cusip_ebitdap, oth137_avg_txn_val, 60) +ts_covariance(mdl211_ebtq_deltaprofitability_profitability11, pv103_sbps_mean, 250) +ts_covariance(mdl26_dsnc_prd_srprs_flg_chg_fq4_rnngs, pv104_insm_mean, 60) +ts_covariance(fnd23_icsm_m_caic, pv103_tlrt_topofbook_tlrt_mean, 250) +ts_covariance(oth395_major_12_13, nws31_bodysize, 60) +ts_covariance(mdl264_epsfx_class, pv104_hlts_mean, 60) +ts_covariance(mdl264_einn_l1, pv87_interval_asksize_std, 60) +ts_covariance(anl69_rec_expected_report_time, mdl230_allcap_sedol_ohlsonscore, 5) +ts_covariance(anl49_backfill_earningspershareindicator, pv81_zsbl, 250) +ts_covariance(mdl230_allcap_sedol_yoychgroa, pv103_masz_mean, 60) +ts_covariance(mdl77_earningsmomemtummodel_fc_y2repsg, pv64_dif_stal_fund_creation_unit_size, 250) +ts_covariance(mdl230_us5000_cusip_spe2yfvc_cf, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(anl15_ebt_s_cal_fy3_mean, pv52_asdaq_order_size_code, 5) +ts_covariance(fnd72_pit_or_cr_q_announcement_dt, pv87_interval_asksize_numintervalsincehigh, 250) +ts_covariance(fnd65_totalcap_cusip_fc_numrevq1, rsk70_mfm2_usfast_size, 5) +ts_covariance(pv87_2_netprofit_rep_qf_matrix_p1_median, fnd31_ohlsonscore, 5) +ts_covariance(mdl230_allcap_sedol_pedwf_cf, pv87_interval_asksizeinterval_slippage_rankcorrel, 20) +ts_covariance(oth432_compustatpredictiveniq_prediction, pv103_tasz_mean, 5) +ts_covariance(mdl26_v14_mstchg_pct_fy1_rnngs_14, pv98_tbds_mean, 20) +ts_covariance(oth460_3l_ifpv, oth551_beta_size, 60) +ts_covariance(mdl26_mstchg_pct_fq2_rnngs_60, pv52_yse_order_size_code, 20) +ts_covariance(earnings_news_mention_count, pv104_lsbs_mean, 250) +ts_covariance(anl10_ebsfy2_smart_ests_v1, pv87_interval_bidsizeinterval_slippage_correlation, 60) +ts_covariance(oth460_usa_compustat_q1_dl8_ibadjq_l2, pv87_interval_asksizeinterval_bidsize_correlation, 250) +ts_covariance(mdl264_usa_compustat_q1_dl8_ibadjq_l3, pv64_dif_fund_creation_unit_size, 250) +ts_covariance(fnd90_us_qes_gamef_grossprofit_asset, pv103_tbsz_mean, 60) +ts_covariance(fnd28_dvfq1_value_18264q, fnd65_allcap_sedol_ohlsonscore, 250) +ts_covariance(mdl262_compustatpredictiveepspiq_prediction, pv103_tbds_mean, 20) +ts_covariance(oth432_oiadpq_profitability_profitability1, pv87_interval_asksizeinterval_bidsize_rankcorrel, 250) +ts_covariance(mdl262_rasv2splitprofitabilityebitd_ttm_profitability9, oth567score_company_size_358, 250) +ts_covariance(mdl77_oearningmomentumfactor_rev6, pv103_tasz_mean, 250) +ts_covariance(mdl177_historicalgrowthfactor_chgeps, pv103_sbsz_mean, 20) diff --git a/prepare_prompt/alpha_prompt.txt b/prepare_prompt/alpha_prompt.txt index 326d626..d5afbd6 100644 --- a/prepare_prompt/alpha_prompt.txt +++ b/prepare_prompt/alpha_prompt.txt @@ -1,6 +1,7 @@ -机构持仓集中度溢价 -机构持仓集中度高的股票流动性风险更高，但市场可能忽视此风险，导致集中度高的股票被高估。因此，多空策略中，做多机构持仓分散度高的股票（风险低，被低估），做空集中度高的股票（风险高，被高估），可获取稳定超额收益。 -核心指标为前十大机构持股比例，需进行行业中性化处理；使用滚动3个月平均处理缺失值；引入换手率和机构持股变动作为辅助验证变量。 +研发资本化激进程度因子 +企业将研发支出过度资本化可短期美化利润，但该会计选择往往反映盈余管理动机，市场未能及时识别其不可持续性，导致股价高估。多空逻辑：做空研发资本化比例高且后续ROA下滑的企业，做多费用化处理、盈利稳健的企业。 +核心指标为资本化研发支出占总研发支出比重，需行业与市值双中性化；使用过去三年均值平滑异常值；引入专利引用数或新申请量作为创新真实性的验证变量。 + *=========================================================================================* diff --git a/prepare_prompt/keys_text.txt b/prepare_prompt/keys_text.txt index 88c237c..d4d99cc 100644 --- a/prepare_prompt/keys_text.txt +++ b/prepare_prompt/keys_text.txt @@ -1 +1 @@ -['institution', 'holding', 'concentration', 'turnover', 'rate', 'change'] \ No newline at end of file +['capitalization', 'expense', 'profit', 'patent', 'innovation', 'accounting'] \ No newline at end of file diff --git a/template_output.txt b/template_output.txt new file mode 100644 index 0000000..b3efa96 --- /dev/null +++ b/template_output.txt @@ -0,0 +1,500 @@ +ts_covariance(anl10_nersmun_2yf_2416, pv87_interval_bidsize_skewness, 60) +ts_covariance(fnd65_us5000_cusip_ebitdap, oth137_avg_txn_val, 60) +ts_covariance(anl15_ebtgics_s_cal_fy3_pe, pv104_insm_mean, 20) +ts_covariance(anl10_entfy1_pred_surps_v1_2442, pv87_interval_bidsize_median, 20) +ts_covariance(fnd72_pit_or_is_q_is_tot_cash_com_dvd, pv87_interval_bidsize_median, 60) +ts_covariance(anl15_cpsgics_gr_cal_fy3_pe, pv81_msni, 20) +ts_covariance(mdl211_ebtq_profitability_profitability5, pv103_mbds_topofbook_mbds_mean, 20) +ts_covariance(anl82_preq_profitability_profitability12, pv103_tbsz_mean, 250) +ts_covariance(anl14_mean_eps_fp5, pv64_trr_cur_mkt_cap, 20) +ts_covariance(anl14_high_eps_fy2, pv87_interval_bidsize_skewness, 250) +ts_covariance(anl14_high_ntprep_fy5, fnd65_totalcap_cusip_ohlsonscore, 5) +ts_covariance(anl82_delta_preq_q4_predict, pv81_zsbt, 250) +ts_covariance(mdl138_qpdi3_net_margin, mdl248_avg_txn_val, 5) +ts_covariance(anl15_ebt_gr_cal_fy3_gro, pv103_masz_mean, 5) +ts_covariance(mdl230_us5000_cusip_y5speq4rqsr, pv104_lbsz_mean, 20) +ts_covariance(pv20_ebt_indicator_4_feature7, pv52_asdaq_order_size_code, 250) +ts_covariance(mdl264_1l_qaeclg, oth567score_company_size_358, 250) +ts_covariance(pv20_ebt_indicator_4_feature7, fnd72_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(oth432_acae_q_profitability_profitability9, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(pv87_epsyld_ltm_d_mean, pv103_htsz_mean, 60) +ts_covariance(anl44_orig_en_pretaxprofit_rep_prevalue, pv81_zsbt, 250) +ts_covariance(anl82_ebty_deltaprofitability_profitability11, fnd72_pit_or_cr_q_debt_to_mkt_cap, 20) +ts_covariance(mdl77_2spe1yfvc_cf, pv87_interval_bidsizeinterval_slippage_correlation, 250) +ts_covariance(fnd13_cinx, fund_total_size, 20) +ts_covariance(anl15_ebt_gr_18_m_cos_dn, pv104_hbsz_mean, 60) +ts_covariance(pv20_gps_indicator_9_feature8, oth551_beta_size, 60) +ts_covariance(anl49_valugaugeestimatingdifficultyrank, pv87_interval_asksize_std, 60) +ts_covariance(pv20_opr_indicator_o_feature11, pv87_interval_asksize_std, 60) +ts_covariance(mdl77_2valuemomemtummodel_reportedearningsmomentummodule, company_size_sentiment_score, 250) +ts_covariance(mdl230_allcap_sedol_yoychgroa, pv103_masz_mean, 60) +ts_covariance(fnd72_s_pit_or_bs_q_2_bs_other_cur_asset_less_prepay, oth567score_company_size, 60) +ts_covariance(mdl264_einn_l1, pv87_interval_asksize_std, 60) +ts_covariance(fnd31_devnorthamericaadditionalfactor4_divgp, pv81_zsbt, 250) +ts_covariance(fnd28_dvfq1_value_18264q, fnd65_allcap_sedol_ohlsonscore, 250) +ts_covariance(anl15_ebtgics_ind_12_m_1m_chg, pv81_trlm, 20) +ts_covariance(mdl177_liquidityriskfactor_mad3yttmni_alt, company_offer_total_size, 60) +ts_covariance(mdl77_ooearningsmomemtummodel_fc_y2repsg, pv87_interval_asksizeinterval_slippage_correlation, 60) +ts_covariance(oth432_deltapredictebt_a_predict, oth551_r2_size, 20) +ts_covariance(pv87_daily_ann_matrix_r1_net_income_normalized_consensus_mean_numup, pv52_yse_arca_order_size_code, 5) +ts_covariance(anl69_rec_expected_report_time, mdl230_allcap_sedol_ohlsonscore, 5) +ts_covariance(fnd23_icsm_mvb_fbbs, pv103_sasz_mean, 5) +ts_covariance(pe_ratio_relative_component_rank_v2, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(pv20_eps_indicator_4_feature2, pv104_hasz_mean, 20) +ts_covariance(mdl230_us5000_cusip_pspeghc, pv52_yse_arca_order_size_code, 60) +ts_covariance(fnd3_A_nic, pv87_interval_asksize_numintervalsincehigh, 60) +ts_covariance(anl14_median_ntp_fy5, pv81_zsah, 250) +ts_covariance(mdl211_oprq_deltaprofitability_profitability5, pv87_interval_bidsize_numintervalsincelow, 5) +ts_covariance(anl82_delta_preq_q2_predict, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 20) +ts_covariance(fnd28_wcishta_value_18189a, pv103_taks_mean, 20) +ts_covariance(mdl354_sector_pt2net_margin, pv87_interval_asksize_median, 60) +ts_covariance(anl14_median_ntp_fy5, nws31_d1_bodysize, 5) +ts_covariance(fnd65_us5000_cusip_chgroepct, oth137_avg_txn_val, 250) +ts_covariance(est_q_gps_mean_3mth_ago, nws31_bodysize, 60) +ts_covariance(pv87_2_operatingprofit_qf_matrix_all_chngratio_mean, pv81_zsbm, 250) +ts_covariance(anl49_1stfiscalquarterearningspershare, pv87_interval_bidsize_mean, 250) +ts_covariance(fnd6_cibegni, pv52_yse_national_order_size_code, 250) +ts_covariance(pv87_2_eps_af_matrix_p1_chngratio_high, rsk70_mfm2_usfast_size, 20) +ts_covariance(mdl211_preq_deltaprofitability_profitability1, pv87_interval_asksize_kurtosis, 250) +ts_covariance(mdl26_v14_srprs_pct_lst_y_rnngs, pv87_interval_asksizeinterval_slippage_correlation, 250) +ts_covariance(est_q_pre_std_4wks_ago, pv52_yse_american_order_size_code, 60) +ts_covariance(fnd31_qsg5additionalfactor3_backfilled_rev6fy2, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(mdl230_totalcap_cusip_pfgmtt, pv103_htsz_mean, 20) +ts_covariance(pv20_pre_indicator_8_feature11, pv103_tbsz_mean, 250) +ts_covariance(mdl211_saly_profitability_profitability5, mdl177_liquidityriskfactor_ohlsonscore_alt, 60) +ts_covariance(mdl26_stm_f12m_rnngs, pv103_1m_mbds_mean, 5) +ts_covariance(oth460_3l_ifpv, oth551_beta_size, 60) +ts_covariance(mdl262_oibdpq_profitability_profitability8, pv103_tbds_mean, 250) +ts_covariance(fnd72_s_pit_or_is_q_is_pension_expense_income, pv87_interval_asksizeinterval_volume_correlation, 5) +ts_covariance(fnd3_a__earbeforetaxes, pv52_yse_order_size_code, 250) +ts_covariance(oth432_che_profitability_profitability2, pv103_sbps_mean, 20) +ts_covariance(pv87_2_pretaxprofit_qf_matrix_all_chngratio_high, pv104_tbsz_mean, 250) +ts_covariance(pv20_gps_indicator_9_feature11, pv104_lsbs_mean, 20) +ts_covariance(mdl26_mstchg_pct_f12m_rnngs_14, pv52_asdaq_order_size_code, 5) +ts_covariance(fnd28_wsbshtq_value_01551q, pv64_trr_stal_cur_mkt_cap, 20) +ts_covariance(mdl264_viat_class, pv81_zsbh, 60) +ts_covariance(mdl262_cheq_profitability_profitability3, pv103_lbsz_mean, 5) +ts_covariance(oth460_uniamiq_l3, company_offer_total_size, 60) +ts_covariance(act_q_gps_surprisestd, fund_total_size, 5) +ts_covariance(anl14_low_ntprep_fy2, pv87_interval_asksizeinterval_bidsize_correlation, 250) +ts_covariance(mdl262_deltapredictni_a_mae, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(mdl77_2deepvaluefactor_vesspem21f, pv103_sasz_mean, 5) +ts_covariance(oth432_rasv2splitprofitabilityfcf_ttm_profitability3, mdl77_liquidityriskfactor_ohlsonscore, 60) +ts_covariance(anl69_roa_expected_report_time, pv64_dif_stal_fund_creation_unit_size, 5) +ts_covariance(fnd14_hiwater_incmst_net_income_fy, pv104_lsts_mean, 5) +ts_covariance(anl10_gpspast_det_analyst_1321, pv81_zsbl, 5) +ts_covariance(fnd17_ttmnichg, pv103_saps_mean, 5) +ts_covariance(mdl230_totalcap_cusip_spe2yfvc_cf, fnd31_ohlsonscore, 20) +ts_covariance(fnd3_Q_interestincome, pv103_sbsz_mean, 5) +ts_covariance(anl49_backfill_typeofearningspershare, pv104_tbsz_mean, 20) +ts_covariance(pv20_eps_indicator_1_feature7, fund_total_size, 250) +ts_covariance(count_negative_profitability_question, pv104_masz_mean, 60) +ts_covariance(pv87_daily_qtr_matrix_net_income_gaap_consensus_mean_numdown, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(anl15_ebtgics_ind_cal_fy3_3m_chg, pv103_1m_mlrt_mean, 20) +ts_covariance(mdl77_earningmomentumfactor_stdevfy1epsp, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(mdl77_historicalgrowthfactor_pspeghc, oth567_deltascore_company_size_432, 20) +ts_covariance(fnd65_allcap_sedol_fqsurstd60dlag, pv98_daily_mean_taks_taks_mean, 5) +ts_covariance(mdl138_in_3idp, pv52_yse_chicago_order_size_code, 20) +ts_covariance(mdl77_fa_pge_cf, pv52_yse_order_size_code, 250) +ts_covariance(fnd28_wcfsq1nbf_value_01401q, mdl248_avg_txn_val, 20) +ts_covariance(oth460_unopincq_l3, fund_total_size, 250) +ts_covariance(mdl177_2_globaldevnorthamerica_v502_fc_epsrm, pv52_asdaq_order_size_code, 250) +ts_covariance(fnd28_statisticsa_value_05290a, pv103_masz_mean, 60) +ts_covariance(investment_income_nonoperating, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(fnd65_us5000_cusip_fqsurstd60dlag, pv81_sasl, 250) +ts_covariance(fnd7_ointfund_qipon, pv103_lbsz_mean, 5) +ts_covariance(pv87_webv2_expavg20_group_css_earnings, mdl177_2_liquidityriskfactor_ohlsonscore, 60) +ts_covariance(fnd28_pftlta_value_08365a, pv103_1m_maks_mean, 250) +ts_covariance(mdl264_3l_21fspe, pv103_tbsz_mean, 250) +ts_covariance(fnd72_s_pit_or_cr_q_trail_12m_eps, pv52_asdaq_order_size_code, 5) +ts_covariance(pv20_gps_indicator_q_feature8, oth551_beta_size, 5) +ts_covariance(mdl77_earningsmomemtummodel_fc_y2repsg, pv64_dif_stal_fund_creation_unit_size, 250) +ts_covariance(est_12m_opr_std, pv87_interval_asksizeinterval_slippage_rankcorrel, 20) +ts_covariance(pv87_2_operatingprofit_qf_matrix_p1_dts, pv81_zsbm, 5) +ts_covariance(anl49_netprofit, pv81_trlm, 20) +ts_covariance(mdl77_2min2ygrossmargin, oth137_avg_txn_val, 20) +ts_covariance(oth432_ebit_compustatdeltapredict_annual_funda_predict, pv103_mbsz_mean, 5) +ts_covariance(anl14_high_ebit_fp4, pv87_interval_bidsizeinterval_slippage_rankcorrel, 20) +ts_covariance(pv20_eps_indicator_8_feature10, pv81_trlt, 250) +ts_covariance(anl82_opry_profitability_profitability12, pv87_interval_bidsizeinterval_slippage_rankcorrel, 250) +ts_covariance(fnd65_allcap_sedol_lagegp, pv104_lasz_mean, 20) +ts_covariance(anl15_ebt_gr_18_m_mean, oth567score_company_size, 250) +ts_covariance(mdl26_trailing_4_quarter_pe, pv103_mbsz_mean, 20) +ts_covariance(pv87_2_operatingprofit_qf_matrix_p1_median, pv52_asdaq_bx_order_size_code, 5) +ts_covariance(mdl77_historicalgrowthfactor_chg3yepsast, pv103_1m_mlrt_mean, 250) +ts_covariance(pv20_gps_indicator_n_feature5, mdl77_liquidityriskfactor_ohlsonscore, 60) +ts_covariance(pv20_net_indicator_n_feature3, pv64_dif_fund_creation_unit_size, 250) +ts_covariance(mdl77_omomemtumanalystmodel_qma_repearnmom, pv87_interval_asksizeinterval_slippage_correlation, 20) +ts_covariance(anl14_low_ntprep_fy2, pv103_laks_mean, 60) +ts_covariance(oth460_2l_eiuv, pv103_maus_mean, 5) +ts_covariance(oth432_oibdpq_profitability_profitability4, pv103_tbds_mean, 250) +ts_covariance(anl69_roe_expected_report_time, pv103_tbds_mean, 5) +ts_covariance(fnd65_allcap_sedol_pspeghc, pv87_interval_asksize_mean, 20) +ts_covariance(anl10_ebtfq1_smart_ests_v1_936, pv87_interval_bidsize_std, 60) +ts_covariance(pv87_2_eps_qf_matrix_all_high, pv87_interval_asksizeinterval_bidsize_rankcorrel, 60) +ts_covariance(mdl26_rm02fy_prsprs_fy2_rnngs, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(fnd72_pit_or_cr_a_prof_margin, pv81_trlt, 20) +ts_covariance(pv20_gps_indicator_1_feature8, pv103_tbsz_mean, 250) +ts_covariance(anl4_qfv4_eps_number, pv81_stlh, 5) +ts_covariance(eps_fiscal_quarter, nws31_d1_bodysize, 60) +ts_covariance(pv87_simpleavg20_group_css_earnings, pv87_interval_asksize_std, 60) +ts_covariance(pv87_2_pretaxprofit_qf_matrix_all_chngratio_median, pv87_interval_bidsizeinterval_slippage_rankcorrel, 60) +ts_covariance(mdl177_valanalystmodel_qva_earnquality, pv52_asdaq_psx_order_size_code, 60) +ts_covariance(mdl77_oearningmomentumfactor_rev6, pv103_tasz_mean, 250) +ts_covariance(oth553_ptg_wordcnt, pv52_yse_arca_order_size_code, 250) +ts_covariance(anl14_mean_ntprep_fp5, pv52_yse_national_order_size_code, 250) +ts_covariance(mdl264_sani_l3, pv87_interval_bidsize_kurtosis, 60) +ts_covariance(oth432_accruals_oeps12_predict, pv52_yse_american_order_size_code, 60) +ts_covariance(anl82_nety_profitability_profitability10, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(anl15_ebtgics_s_fy3_cos_dn, pv87_interval_asksizeinterval_volume_correlation, 60) +ts_covariance(pv87_2_pretaxprofit_rep_af_matrix_all_chngratio_high, pv81_zsbh, 250) +ts_covariance(fnd3_aacctadj__earbeforetaxes, pv103_tasz_mean, 250) +ts_covariance(anl10_ebiinnovation_score_fy2_2589, fnd72_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(pv87_2_epsr_qf_matrix_all_high, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(anl49_earningspershare, pv103_mbus_mean, 250) +ts_covariance(fnd72_pit_or_cr_a_net_inc_growth, pv52_yse_national_order_size_code, 20) +ts_covariance(mdl262_niq_compustatdeltapredict_funda_mada, pv87_interval_asksizeinterval_slippage_correlation, 5) +ts_covariance(fnd28_wcfsa1_value_01266a, pv103_tbds_mean, 5) +ts_covariance(fnd65_totalcap_cusip_fc_numrevq1, rsk70_mfm2_usfast_size, 5) +ts_covariance(mdl230_us5000_cusip_ebitdadebtchg, fnd31_ohlsonscore, 20) +ts_covariance(pv87_2_epsr_af_matrix_p1_dts, pv103_tasz_mean, 5) +ts_covariance(anl10_nerpast_det_indicator_913, pv64_dif_fund_creation_unit_size, 5) +ts_covariance(anl44_second_en_netprofit_rep_coveredby, pv103_lasz_mean, 250) +ts_covariance(fnd7_ointfund_rq21hsc, company_offer_total_size, 5) +ts_covariance(pv20_ebt_indicator_2_feature9, pv104_tasz_mean, 60) +ts_covariance(gross_profit_total, pv103_tasz_mean, 250) +ts_covariance(mdl26_v14_nnlyst_rvsng_dwn_fq1_rnngs_7, pv64_trr_stal_cur_mkt_cap, 5) +ts_covariance(oth460_usa_compustat_q1_dl8_ibadjq_l2, pv87_interval_asksizeinterval_bidsize_correlation, 250) +ts_covariance(anl4_epsr_value, pv103_mbus_mean, 20) +ts_covariance(oth460_ibadjq_l3, pv81_stsl, 20) +ts_covariance(pv20_net_indicator_n_feature6, pv52_yse_american_order_size_code, 20) +ts_covariance(anl10_ebspast_det_excflag, pv104_masz_mean, 5) +ts_covariance(fnd89_jones_accrual_major_11, pv87_interval_asksize_mean, 60) +ts_covariance(fnd28_annualgrowth_value_08601a, pv81_zsbl, 5) +ts_covariance(anl14_numofests_ebitda_fp4, pv104_masz_mean, 5) +ts_covariance(mdl177_valueanalystmodel_qva_earnval_alt, oth137_avg_txn_val, 250) +ts_covariance(mdl26_mn_f_rvsnclstr_nlysts_fy2_rnngs, oth567_deltascore_company_size_432, 20) +ts_covariance(pv87_2_netprofit_rep_qf_matrix_p1_median, fnd31_ohlsonscore, 5) +ts_covariance(fnd72_q1_geo_grow_ebitda_cap_exp_to_int, pv81_trlm, 250) +ts_covariance(mdl230_us5000_cusip_ebitdadebt, pv64_dif_stal_fund_creation_unit_size, 60) +ts_covariance(oth460_net_margin_l2, mdl177_2_liquidityriskfactor_ohlsonscore, 250) +ts_covariance(mdl77_valuemomemtummodel_earningsqualitymodule, pv52_yse_arca_order_size_code, 5) +ts_covariance(pv87_epsyld_gro_mean, pv103_1m_mbds_mean, 20) +ts_covariance(mdl262_compustatpredictivetxtq_prediction, pv104_tbsz_mean, 250) +ts_covariance(mdl262_txtq_compustatdeltapredict_funda_predict, pv98_tbds_mean, 5) +ts_covariance(mdl230_allcap_sedol_saleeps, fund_total_size, 20) +ts_covariance(mdl262_rasv2splitprofitabilityebitd_ttm_profitability9, oth567score_company_size_358, 250) +ts_covariance(anl10_ebiinnovation_score_fy2_2589, fnd65_allcap_sedol_ohlsonscore, 20) +ts_covariance(ern6_actual_period, pv103_hasz_mean, 20) +ts_covariance(mdl262_rasv2splitprofitabilityebitd_q_profitability9, pv87_interval_asksize_median, 60) +ts_covariance(mdl262_sbda_a_profitability_profitability4, pv87_interval_asksize_numintervalsincehigh, 5) +ts_covariance(anl69_eps_best_eps, fnd72_pit_or_cr_a_debt_to_mkt_cap, 60) +ts_covariance(fnd28_wcfsq1nbf_value_01706q, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(fnd72_pit_or_cr_a_trail_12m_oper_inc, pv87_interval_asksizeinterval_bidsize_correlation, 5) +ts_covariance(oth460_ttax_l3, pv87_interval_bidsizeinterval_volume_correlation, 60) +ts_covariance(oth432_txtq_mae, oth551_resret_size, 60) +ts_covariance(anl82_preq_deltaprofitability_profitability11, company_offer_total_size, 20) +ts_covariance(fnd6_newa1v1300_ibadj, oth567score_company_size_358, 20) +ts_covariance(star_eq_ope_rank, pv98_daily_mean_taks_taks_mean, 5) +ts_covariance(anl15_dps_gr_cal_fy1_pe, oth551_r2_size, 5) +ts_covariance(mdl26_dsnc_prd_srprs_flg_chg_fq4_rnngs, pv104_insm_mean, 60) +ts_covariance(anl49_backfill_estdcurrentperatio, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(mdl77_2mqf_yoychggpm, fnd65_totalcap_cusip_ohlsonscore, 60) +ts_covariance(pv20_pre_indicator_3_feature0, pv87_interval_bidsize_median, 250) +ts_covariance(anl14_numofests_opp_fp1, fnd14_zs_lf_nlf_drp_ncr, 5) +ts_covariance(anl14_mean_ntp_fy1, mdl177_2_liquidityriskfactor_ohlsonscore, 250) +ts_covariance(mdl211_preq_profitability_profitability7, company_size_sentiment_score, 5) +ts_covariance(fnd65_us5000_cusip_pfcmtt, pv103_masz_mean, 5) +ts_covariance(mdl177_historicalgrowthfactor_chgeps, pv103_sbsz_mean, 20) +ts_covariance(mdl109_b_mtl_dlyspe, pv103_1m_mlrt_mean, 60) +ts_covariance(oth432_compustatpredictiveniq_prediction, pv103_tasz_mean, 5) +ts_covariance(mdl211_nety_y1_mada, mdl177_2_liquidityriskfactor_ohlsonscore, 20) +ts_covariance(pv87_2_operatingprofit_qf_matrix_all_low, mdl230_totalcap_cusip_ohlsonscore, 250) +ts_covariance(pv20_ebt_indicator_7_feature6, pv87_interval_asksize_skewness, 60) +ts_covariance(anl82_preq_q4_madp, pv103_lasz_mean, 250) +ts_covariance(anl82_delta_netq_q1_predict, pv81_lasz, 250) +ts_covariance(mdl230_totalcap_cusip_epschgetr, oth551_resret_size, 20) +ts_covariance(mdl26_7dy_bld_stmt_flg_fq4_rnngs, pv104_lsbs_mean, 250) +ts_covariance(fnd89_jones_accrual_pct_major_13, oth567score_company_size, 20) +ts_covariance(anl4_netprofit_mean, pv103_maks_topofbook_maks_mean, 250) +ts_covariance(act_12m_prr_value, pv87_interval_bidsize_mean, 60) +ts_covariance(fnd72_s_pit_or_cr_q_ev_to_t12m_ebit, pv104_tlrt_mean, 20) +ts_covariance(mdl211_ebtq_deltaprofitability_profitability11, pv103_sbps_mean, 250) +ts_covariance(pv87_2_pretaxprofit_rep_af_matrix_p1_chngratio_number, pv87_interval_bidsize_skewness, 250) +ts_covariance(anl82_oprq_q4_madp, fnd31_ohlsonscore, 20) +ts_covariance(pv87_2_netprofit_rep_af_matrix_all_low, pv103_mbsz_mean, 60) +ts_covariance(anl15_ebt_gr_cal_fy3_cos, im_shares_transacted, 60) +ts_covariance(pv20_indicator_4_feature8, mdl77_liquidityriskfactor_ohlsonscore, 20) +ts_covariance(max_ebit_guidance, mdl230_allcap_sedol_ohlsonscore, 20) +ts_covariance(mdl26_rm02fy_prsprs_fy2_rnngs, pv52_asdaq_order_size_code, 250) +ts_covariance(fnd90_us_qes_gamef_grossprofit_asset, pv103_tbsz_mean, 60) +ts_covariance(anl15_ebt_gr_18_m_6m_chg, rsk70_mfm2_usfast_size, 60) +ts_covariance(gross_profit_to_assets_ratio, pv98_tbds_mean, 250) +ts_covariance(fnd17_margin5yr, rsk70_mfm2_usfast_size, 20) +ts_covariance(fnd23_annfv1a_nimv, pv103_lasz_mean, 5) +ts_covariance(oth395_major_12_13, nws31_bodysize, 60) +ts_covariance(mdl264_2l_qic, pv104_tasz_mean, 5) +ts_covariance(mdl230_us5000_cusip_spe2yfvc_cf, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(anl14_numofests_ntprep_fp1, pv87_interval_asksize_mean, 250) +ts_covariance(mdl262_rasv2splitprofitabilityni_q_profitability3, pv64_trr_cur_mkt_cap, 250) +ts_covariance(pv20_pre_indicator_6_feature10, fund_total_size, 20) +ts_covariance(mdl26_mstchg_pct_fq2_rnngs_60, pv52_yse_order_size_code, 20) +ts_covariance(mdl264_1l_declg, fund_total_size, 5) +ts_covariance(anl14_high_ntprep_fy3, mdl230_us5000_cusip_ohlsonscore, 5) +ts_covariance(pv87_ann_matrix_net_income_gaap_estimate_high, pv52_yse_national_order_size_code, 250) +ts_covariance(pv87_daily_qtr_matrix_net_income_gaap_consensus_mean_numup, pv87_interval_bidsize_std, 20) +ts_covariance(mdl26_nnlyst_rvsng_p_fy1_rnngs_7, mdl248_avg_txn_val, 60) +ts_covariance(mdl26_v14_prsprise_pct_fq2_earnings, rsk70_mfm2_usfast_size, 250) +ts_covariance(pv87_2_operatingprofit_af_matrix_p1_chngratio_mean, pv103_sbps_mean, 5) +ts_covariance(anl14_median_ebit_fy4, pv87_interval_asksize_numintervalsincehigh, 250) +ts_covariance(anl15_dps_gr_12_m_pe, nws31_d1_bodysize, 60) +ts_covariance(mdl77_liquidityriskfactor_impduration, pv52_asdaq_psx_order_size_code, 60) +ts_covariance(pv87_2_netprofit_af_matrix_all_dts, pv103_1m_tlrt_mean, 250) +ts_covariance(oth432_oiadpq_profitability_profitability1, pv87_interval_asksizeinterval_bidsize_rankcorrel, 250) +ts_covariance(fnd72_q1_inc_tax_exp_to_net_sales, pv103_lbsz_mean, 60) +ts_covariance(pv20_ebt_indicator_7_feature2, pv87_interval_bidsize_kurtosis, 5) +ts_covariance(mdl177_2_earningsqualityfactor_saleeps, nws31_d1_bodysize, 20) +ts_covariance(mdl262_txtq_compustatdeltapredict_funda_mada, im_shares_transacted, 5) +ts_covariance(anl10_epsinnovation_score_fy1, pv103_tbsz_mean, 5) +ts_covariance(anl14_high_eps_fy4, company_size_sentiment_score, 20) +ts_covariance(mdl77_ohistoricalgrowthfactor_speghc, pv87_interval_asksizeinterval_slippage_correlation, 20) +ts_covariance(earnings_news_mention_count, pv104_lsbs_mean, 250) +ts_covariance(est_q_opr_num_28d, fund_total_size, 250) +ts_covariance(fnd72_s_pit_or_cr_q_trail_12m_inc_bef_xo_item, pv103_tbds_mean, 20) +ts_covariance(fnd72_a2_retention_ratio, fund_total_size, 250) +ts_covariance(mdl77_oindustryrrelativevaluefactor_curindcoreepsp_, mdl77_2liquidityriskfactor_ohlsonscore, 5) +ts_covariance(mdl262_deltapredictebt_q_predict, pv104_hasz_mean, 5) +ts_covariance(oth432_ninc_trkdpitdeltapredict_funda_mae, pv81_zsbm, 60) +ts_covariance(est_q_opr_mean_28d, pv103_maks_topofbook_maks_mean, 20) +ts_covariance(fnd6_newa2v1300_ni, pv104_mlrt_mean, 60) +ts_covariance(ebit_reported_value, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(pv20_ebt_indicator_n_feature4, pv87_interval_bidsize_std, 5) +ts_covariance(mdl177_v1_400_sue, pv64_dif_stal_fund_creation_unit_size, 5) +ts_covariance(anl49_backfill_earningspershareindicator, pv81_zsbl, 250) +ts_covariance(anl15_ebtgics_gr_cal_fy2_gro, oth551_r2_size, 60) +ts_covariance(anl10_ebsfq1_consensus, oth551_r2_size, 250) +ts_covariance(mdl262_che_profitability_profitability9, pv104_mlrt_mean, 5) +ts_covariance(est_12m_ner_std_28d, pv81_lasz, 250) +ts_covariance(mdl262_sbda_a_profitability_profitability2, pv103_laks_mean, 20) +ts_covariance(rsk62_id_spe, pv104_tasz_mean, 250) +ts_covariance(fnd72_pit_or_cr_a_ev_to_t12m_ebitda, pv103_laks_mean, 250) +ts_covariance(oth432_rasv2splitprofitabilityebt_ttm_profitability4, pv87_interval_bidsize_numintervalsincelow, 20) +ts_covariance(pv87_2_netprofit_af_matrix_p1_chngratio_std, pv104_hbsz_mean, 60) +ts_covariance(anl10_ebismun_2qf_2231, pv52_yse_national_order_size_code, 250) +ts_covariance(pv87_neg_earnings_matrix_css_sum, pv103_1m_maks_mean, 60) +ts_covariance(mdl262_rasv2splitprofitabilityebitd_q_profitability10, pv103_1m_maks_mean, 250) +ts_covariance(mdl264_usa_compustat_q1_dl8_ibadjq_l3, pv64_dif_fund_creation_unit_size, 250) +ts_covariance(oth460_usa_compustat_q1_dl8_epsfiq_l5, mdl177_2_liquidityriskfactor_ohlsonscore, 5) +ts_covariance(mdl77_2ccacw, pv98_quote_size_mean, 5) +ts_covariance(mdl177_2_liquidityriskfactor_oplev, pv87_interval_asksize_kurtosis, 250) +ts_covariance(pv20_net_indicator_q_feature7, pv103_laks_mean, 250) +ts_covariance(pv87_prv2_expavg60_group_event_sentiment_score_earnings, pv103_hasz_mean, 250) +ts_covariance(fnd28_newa1_value_08385a, pv103_1m_mbds_mean, 250) +ts_covariance(mdl177_2_globaldevnorthamerica_v502_wcacc, pv87_interval_asksize_mean, 5) +ts_covariance(fnd6_txs, pv52_yse_arca_order_size_code, 250) +ts_covariance(mdl26_nm_stm_nlysts_fy2_rnngs, mdl230_allcap_sedol_ohlsonscore, 250) +ts_covariance(mdl262_che_profitability_profitability5, pv98_quote_size_mean, 5) +ts_covariance(mdl77_ooearningsmomemtummodel_fc_numrevy1, pv81_stlh, 250) +ts_covariance(fnd65_totalcap_cusip_pe_wt, pv87_interval_bidsize_kurtosis, 250) +ts_covariance(pv20_gps_indicator_6_feature10, pv103_maus_mean, 60) +ts_covariance(fnd28_wcfsa1_value_01503a, mdl230_allcap_sedol_ohlsonscore, 250) +ts_covariance(mdl230_allcap_sedol_pedwf_cf, pv87_interval_asksizeinterval_slippage_rankcorrel, 20) +ts_covariance(mdl262_rasv2splitprofitabilityfcf_q_profitability9, nws31_d1_bodysize, 60) +ts_covariance(mdl77_momemtumanalystmodel_qma_composite, fnd65_allcap_sedol_ohlsonscore, 20) +ts_covariance(anl10_ebsfy2_smart_ests_v1, pv87_interval_bidsizeinterval_slippage_correlation, 60) +ts_covariance(oth432_compustatpredictiveepsfiq_mad_pred, pv87_interval_asksize_mean, 5) +ts_covariance(anl15_ebt_ind_cal_fy1_1m_chg, rsk70_mfm2_usfast_size, 5) +ts_covariance(pv20_net_indicator_8_feature12, pv104_lbsz_mean, 20) +ts_covariance(fnd65_allcap_sedol_bmpo, pv103_masz_mean, 250) +ts_covariance(pv20_eps_indicator_1_feature2, pv87_interval_asksize_median, 5) +ts_covariance(anl14_stddev_opp_fy1, oth551_resret_size, 250) +ts_covariance(anl69_eps_best_eps_lo, pv103_1m_mlrt_mean, 5) +ts_covariance(anl82_netq_deltaprofitability_profitability2, mdl230_totalcap_cusip_ohlsonscore, 20) +ts_covariance(mdl264_net_margin_l2, pv52_yse_arca_order_size_code, 60) +ts_covariance(fnd72_s_pit_or_is_a_is_rd_expend, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(est_12m_opr_mean_3mth_ago, pv81_zsbm, 60) +ts_covariance(mdl177_2_earningsqualityfactor_salegpm, pv104_lsbs_mean, 5) +ts_covariance(anl82_saly_deltaprofitability_profitability8, fnd72_pit_or_cr_a_debt_to_mkt_cap, 60) +ts_covariance(mdl262_compustatpredictiveoiadpq_mad_pred, pv104_tbsz_mean, 60) +ts_covariance(rsk62_beta_5_100_spe, pv87_interval_bidsize_median, 5) +ts_covariance(long_term_dividend_payout_ratio, company_offer_total_size, 60) +ts_covariance(fnd3_aacctadj_ebit, pv52_yse_national_order_size_code, 20) +ts_covariance(pv87_net_income_normalized_actual, pv103_tlrt_topofbook_tlrt_mean, 20) +ts_covariance(anl14_stddev_ebit_fp1, pv81_sasl, 60) +ts_covariance(mdl77_2mqf_niper, pv64_dif_fund_creation_unit_size, 20) +ts_covariance(est_ptpr, pv52_yse_chicago_order_size_code, 60) +ts_covariance(mdl26_v14_mstchg_pct_fy1_rnngs_14, pv98_tbds_mean, 20) +ts_covariance(gross_profit_current, pv81_stsl, 20) +ts_covariance(mdl264_usa_compustat_q1_dl8_miiq_l2, pv103_maus_mean, 250) +ts_covariance(fnd23_annfvmfm_rltr, pv103_lask_topofbook_lask_mean, 250) +ts_covariance(anl49_vector_depreciationdepletionamortization, pv103_tbsz_mean, 250) +ts_covariance(fnd31_qsg5additionalfactor3_backfilled_apg, pv103_sbps_mean, 250) +ts_covariance(est_12m_ner_median, pv103_1m_tlrt_mean, 5) +ts_covariance(pv87_ann_matrix_net_income_normalized_estimate_median, pv81_lasz, 5) +ts_covariance(anl14_high_epsrep_fy3, pv103_mbus_mean, 60) +ts_covariance(est_q_ner_median_3mth_ago, pv103_masz_mean, 250) +ts_covariance(pv87_web_weightedavg60_group_v2_0_1_css_earnings, mdl230_totalcap_cusip_ohlsonscore, 20) +ts_covariance(fnd65_us5000_cusip_min1yopmargin, pv81_zsbl, 60) +ts_covariance(anl15_ebt_ind_cal_fy3_6m_chg, fnd65_us5000_cusip_ohlsonscore, 250) +ts_covariance(mdl262_rasv2splitprofitabilityebit_ttm_profitability12, pv52_yse_arca_order_size_code, 250) +ts_covariance(anl10_gpssmun_1qf_2624, pv103_mbsz_mean, 5) +ts_covariance(mdl262_compustatpredictiveepspiq_prediction, pv103_tbds_mean, 20) +ts_covariance(pv87_2_epsr_af_matrix_all_chngratio_low, pv81_zsbl, 5) +ts_covariance(anl10_nerinnovate_increase_fy1_1995, mdl230_us5000_cusip_ohlsonscore, 5) +ts_covariance(fnd3_q_ebitda, pv87_interval_bidsizeinterval_volume_correlation, 250) +ts_covariance(oth460_berry_l2, pv87_interval_asksizeinterval_bidsize_correlation, 20) +ts_covariance(fnd65_us5000_cusip_aoer, pv103_mlrt_topofbook_mlrt_mean, 250) +ts_covariance(fnd72_s_pit_or_cr_q_com_eqy_to_tot_asset, pv103_tlrt_topofbook_tlrt_mean, 250) +ts_covariance(anl10_ebiinnovate_decrease_fq2_2606, pv81_zsah, 250) +ts_covariance(oth432_deltapredictebitd_a_mae, pv103_lasz_mean, 5) +ts_covariance(mdl264_epsfx_class, pv104_hlts_mean, 60) +ts_covariance(research_development_expense_reported_value, pv103_laks_mean, 250) +ts_covariance(mdl230_allcap_sedol_perg, fnd14_zs_lf_nlf_drp_ncr, 250) +ts_covariance(fnd65_totalcap_cusip_mpgghcy3_, pv81_zsbt, 5) +ts_covariance(mdl77_put_put_indepsp, pv104_tasz_mean, 5) +ts_covariance(mdl264_opepsq_l2, pv104_tasz_mean, 250) +ts_covariance(mdl77_2gdna_yoychgaa, mdl177_2_liquidityriskfactor_ohlsonscore, 250) +ts_covariance(mdl262_cheq_profitability_profitability2, pv52_yse_national_order_size_code, 5) +ts_covariance(mdl262_deltapredictebitd_q_predict, pv103_mbds_topofbook_mbds_mean, 60) +ts_covariance(est_q_eps_std_3mth_ago, pv87_interval_bidsize_skewness, 250) +ts_covariance(anl82_oprq_profitability_profitability10, pv103_mbds_topofbook_mbds_mean, 60) +ts_covariance(anl15_ebt_s_cal_fy3_mean, pv52_asdaq_order_size_code, 5) +ts_covariance(mdl116_epsyld_fy2_trendpredict_model_mada, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 20) +ts_covariance(pv87_2_netprofit_rep_qf_matrix_p1_low, pv104_masz_mean, 250) +ts_covariance(fnd28_value_18841a, pv104_lbsz_mean, 20) +ts_covariance(pv20_sal_indicator_p_feature1, pv87_interval_asksizeinterval_bidsize_rankcorrel, 5) +ts_covariance(anl14_high_ntp_fp2, pv87_interval_bidsizeinterval_volume_correlation, 20) +ts_covariance(mdl109_d_mtl_dlyspe, pv104_tbsz_mean, 5) +ts_covariance(anl14_stddev_ntp_fy1, pv103_sbsz_mean, 5) +ts_covariance(anl69_roe_expected_report_dt, pv52_yse_american_order_size_code, 60) +ts_covariance(mdl77_omomemtumanalystmodel_qma_mktresponse, pv64_dif_stal_fund_creation_unit_size, 250) +ts_covariance(oth460_usa_compustat_q1_dl8_epspxq_l4, pv104_hbsz_mean, 60) +ts_covariance(anl10_ebtfq2_pred_surps_v0_964, pv103_1m_mlrt_mean, 5) +ts_covariance(pv87_daily_ann_matrix_r1_net_income_normalized_consensus_mean_numnochangeunfiltered, oth567score_company_size, 250) +ts_covariance(quarterly_retained_earnings_total, pv87_interval_asksize_median, 5) +ts_covariance(pv20_ebt_indicator_q_feature5, pv64_trr_stal_cur_mkt_cap, 60) +ts_covariance(fnd72_pit_or_is_a_is_interest_inc, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(mdl77_earningsmomemtummodel_fc_fqsurstd, oth551_beta_size, 250) +ts_covariance(fnd65_totalcap_cusip_mad3yttmni, pv87_interval_asksize_skewness, 60) +ts_covariance(pv20_opr_indicator_o_feature7, pv104_insm_mean, 5) +ts_covariance(earning_time_type, pv104_lasz_mean, 5) +ts_covariance(mdl177_2_historicalgrowthfactor_chg3yepsp, oth567_deltascore_company_size_432, 250) +ts_covariance(mdl211_saly_deltaprofitability_profitability9, fnd31_ohlsonscore, 250) +ts_covariance(mdl262_eps_oeps12_mae, pv104_masz_mean, 5) +ts_covariance(mdl264_uopiq_class, fnd72_pit_or_cr_q_debt_to_mkt_cap, 250) +ts_covariance(annual_retained_earnings_total_fast_d1, pv103_maus_mean, 60) +ts_covariance(anl15_bps_ind_12_m_pe, oth551_resret_size, 60) +ts_covariance(oth401_game_earning_smooth, oth567score_company_size, 60) +ts_covariance(mdl230_us5000_cusip_altmanz, pv103_htsz_mean, 20) +ts_covariance(mdl211_netq_profitability_profitability7, fund_total_size, 250) +ts_covariance(anl15_ebtgics_ind_18_m_cos_dn, pv103_maus_mean, 60) +ts_covariance(mdl264_usa_compustat_q1_dl8_epspiq_l1, mdl230_us5000_cusip_ohlsonscore, 5) +ts_covariance(mdl262_trkdpitpredictiveebitda_prediction, oth551_r2_size, 250) +ts_covariance(pv20_ebt_indicator_7_feature2, pv104_masz_mean, 60) +ts_covariance(pv87_2_operatingprofit_af_matrix_p1_dts, pv98_tbds_mean, 60) +ts_covariance(fnd28_ishta_value_01751a, pv64_dif_fund_creation_unit_size, 20) +ts_covariance(oth460_ciac_class, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(mdl26_v14_mstchg_pct_f12m_rnngs_90, pv103_maks_topofbook_maks_mean, 20) +ts_covariance(anl44_netprofit_gaap_best_cur_fiscal_qtr_period, company_offer_total_size, 60) +ts_covariance(fnd72_pit_or_cr_q_announcement_dt, pv87_interval_asksize_numintervalsincehigh, 250) +ts_covariance(earnings_announcement_time_of_day_fast_d1, pv52_asdaq_bx_order_size_code, 20) +ts_covariance(fnd28_bdea_value_18854a, pv81_sbsl, 60) +ts_covariance(anl82_ebtq_deltaprofitability_profitability5, oth567score_company_size_358, 20) +ts_covariance(pv87_pos_earnings_matrix_bee_sum, mdl77_2liquidityriskfactor_ohlsonscore, 20) +ts_covariance(pv20_ebt_indicator_6_feature6, pv103_lbsz_mean, 5) +ts_covariance(anl15_ebtgics_ind_cal_fy1_6m_chg, company_offer_total_size, 250) +ts_covariance(mdl262_ninc_trkdpitdeltapredict_funda_mae, pv87_interval_asksizeinterval_bidsize_correlation, 5) +ts_covariance(fnd28_wsfsq_value_01451q, company_offer_size_value, 5) +ts_covariance(oth432_deltapredictni_a_predict, mdl177_2_liquidityriskfactor_ohlsonscore, 20) +ts_covariance(mdl354_group_pt12yf_dlyspe, pv98_daily_mean_taks_taks_mean, 20) +ts_covariance(anl15_cpsgics_s_18_m_pe, pv64_trr_cur_mkt_cap, 5) +ts_covariance(mdl262_predictiveebt_a_predict, mdl177_liquidityriskfactor_ohlsonscore_alt, 5) +ts_covariance(mdl262_deltapredictebit_q_predict, pv81_zsat, 5) +ts_covariance(anl10_ebtrevise_ratio_to_consensus_fq2_1011, pv81_zsbl, 5) +ts_covariance(fnd72_pit_or_cr_q_prof_margin, mdl230_totalcap_cusip_ohlsonscore, 250) +ts_covariance(mdl230_totalcap_cusip_rev6fy2, pv81_zsbl, 5) +ts_covariance(mdl211_ebtq_deltaprofitability_profitability12, pv103_hasz_mean, 5) +ts_covariance(mdl26_rvsnclstr_vg_rvsn_pr_fq1_rnngs, mdl77_liquidityriskfactor_ohlsonscore, 5) +ts_covariance(anl15_ebtgics_ind_cal_fy3_total, fund_total_size, 250) +ts_covariance(anl14_stddev_ntp_fp1, pv87_interval_asksize_std, 20) +ts_covariance(fnd72_pit_or_cr_a_com_eqy_to_tot_asset, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(pv87_ann_matrix_net_income_normalized_estimate_low, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(oth460_3l_qacf, pv104_tbsz_mean, 20) +ts_covariance(anl10_epsinnovate_decrease_fq2, pv52_yse_national_order_size_code, 20) +ts_covariance(mdl264_usa_compustat_q1_dl8_nopiq_l4, pv64_trr_stal_cur_mkt_cap, 250) +ts_covariance(anl10_nersmun_1yf_2417, pv87_interval_bidsize_std, 60) +ts_covariance(anl14_high_ebitda_fp5, pv104_lasz_mean, 250) +ts_covariance(fnd7_ointfund_qipspe, pv52_yse_arca_order_size_code, 20) +ts_covariance(anl82_oprq_profitability_profitability1, pv52_yse_national_order_size_code, 20) +ts_covariance(count_neutral_profitability_summary_fast_d1, pv87_interval_asksizeinterval_slippage_rankcorrel, 20) +ts_covariance(est_12m_pre_mean_3mth_ago, pv64_dif_stal_fund_creation_unit_size, 5) +ts_covariance(mdl26_v14_nnlyst_rvsng_dwn_fy1_rnngs_14, pv104_tasz_mean, 60) +ts_covariance(anl10_ebsfy2_pred_surps_v0, pv87_interval_asksizeinterval_bidsize_rankcorrel, 60) +ts_covariance(oth432_rasv2splitprofitabilityebt_ttm_profitability5, mdl230_totalcap_cusip_ohlsonscore, 20) +ts_covariance(fnd7_ointfund_qiim, pv103_sbps_mean, 250) +ts_covariance(mdl262_acae_q_profitability_profitability8, pv103_tbsz_mean, 60) +ts_covariance(fnd89_csjones_industry_major_14, pv87_interval_bidsize_skewness, 20) +ts_covariance(mdl230_allcap_sedol_aor, pv81_trlt, 250) +ts_covariance(mdl262_compustat_models_profitability7, pv103_mlrt_topofbook_mlrt_mean, 250) +ts_covariance(anl10_nerrevise_ratio_to_consensus_fq2_2016, pv103_sbsz_mean, 20) +ts_covariance(fnd65_us5000_cusip_divcov, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(pv87_weightedavg60_group_ess_earnings, pv81_stlh, 20) +ts_covariance(pretax_income_total, pv104_tasz_mean, 250) +ts_covariance(mdl264_onet_l1, oth137_avg_txn_val, 20) +ts_covariance(fnd2_itxreexftfedstyitxrt, mdl230_allcap_sedol_ohlsonscore, 60) +ts_covariance(anl10_ebsnormal_decrease_fy2, pv64_dif_fund_creation_unit_size, 60) +ts_covariance(oth432_rasv2splitprofitabilityni_ttm_profitability1, pv81_stlh, 250) +ts_covariance(anl14_numofests_ntp_fy2, pv87_interval_bidsize_numintervalsincelow, 250) +ts_covariance(mdl211_saly_deltaprofitability_profitability9, pv87_interval_bidsizeinterval_slippage_rankcorrel, 5) +ts_covariance(fnd23_intfvm_ipos, nws31_bodysize, 5) +ts_covariance(mdl211_salq_deltaprofitability_profitability7, pv87_interval_asksize_std, 60) +ts_covariance(fnd89_major_11_31, pv81_sasl, 5) +ts_covariance(pv20_indicator_0_feature0_121, pv103_lbsz_mean, 5) +ts_covariance(pv20_eps_indicator_2_feature0, nws31_bodysize, 5) +ts_covariance(pv87_net_income_normalized_of_estimates_scale, pv87_interval_asksize_mean, 5) +ts_covariance(pv20_ebt_indicator_q_feature11, oth567_deltascore_company_size_432, 60) +ts_covariance(mdl211_ebty_deltaprofitability_profitability5, pv103_1m_mlrt_mean, 20) +ts_covariance(anl10_nerrevise_value_fq1_2012, pv87_interval_asksizeinterval_slippage_correlation, 60) +ts_covariance(act_12m_opr_value, pv98_quote_size_mean, 5) +ts_covariance(pv20_gps_indicator_7_feature11, pv87_interval_asksizeinterval_bidsize_correlation, 250) +ts_covariance(fnd6_cptmfmq_opepsq, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 60) +ts_covariance(anl15_ebtgics_gr_cal_fy1_3m_chg, pv104_masz_mean, 250) +ts_covariance(fnd7_ointhstfundfn_hfqspepo, fnd65_totalcap_cusip_ohlsonscore, 60) +ts_covariance(mdl262_oiadpq_profitability_profitability3, pv103_1m_tlrt_mean, 5) +ts_covariance(pv20_opr_indicator_n_feature2, pv52_yse_order_size_code, 250) +ts_covariance(pv20_sal_indicator_2_feature12, mdl77_2liquidityriskfactor_ohlsonscore, 60) +ts_covariance(quarterly_earnings_before_tax_total, pv103_htsz_mean, 20) +ts_covariance(pv20_pre_indicator_n_feature10, pv104_tlrt_mean, 250) +ts_covariance(fnd72_s_pit_or_is_q_earn_for_common, pv87_interval_asksizeinterval_volume_correlation, 20) +ts_covariance(anl82_salq_profitability_profitability1, pv103_maus_mean, 5) +ts_covariance(fnd65_totalcap_cusip_mpoghc, pv104_tasz_mean, 5) +ts_covariance(mdl177_historicalgrowthfactor_pctchg3yeps, pv81_trlt, 20) +ts_covariance(mdl26_bld_stmt_flg_fq2_rnngs, fnd65_totalcap_cusip_ohlsonscore, 60) +ts_covariance(anl4_ptpr_number, pv52_asdaq_psx_order_size_code, 250) +ts_covariance(earning_fiscal_year_end, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(fnd28_newa2_value_09216a, nws31_d1_bodysize, 60) +ts_covariance(est_q_eps_std_4wks_ago, pv87_interval_bidsize_skewness, 5) +ts_covariance(anl14_high_eps_fp5, pv103_laks_mean, 60) +ts_covariance(mdl264_viat_l3, mdl230_allcap_sedol_ohlsonscore, 250) +ts_covariance(pv20_opr_indicator_1_feature1, pv103_sbsz_mean, 60) +ts_covariance(mdl262_che_profitability_profitability2, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 5) +ts_covariance(anl69_dps_expected_report_time, pv64_out_stal_fund_creation_unit_size, 5) +ts_covariance(mdl26_p_yld_pct_stm_fy1, pv104_hbsz_mean, 60) +ts_covariance(anl82_opry_deltaprofitability_profitability3, pv104_mbsz_mean, 5) +ts_covariance(est_12m_gps_std_28d, pv104_lbsz_mean, 20) +ts_covariance(mdl77_2liquidityriskfactor_impduration, pv103_tlrt_topofbook_tlrt_mean, 60) +ts_covariance(mdl264_epspi_class, fnd72_s_pit_or_cr_q_debt_to_mkt_cap, 5) +ts_covariance(oth460_usa_compustat_q1_dl8_nopiq_l4, pv103_mlrt_topofbook_mlrt_mean, 250) +ts_covariance(earning_time_type_fast_d1, pv103_hbsz_mean, 20) +ts_covariance(anl82_opry_y1_madp, pv64_trr_cur_mkt_cap, 60) +ts_covariance(pv20_net_indicator_q_feature0, company_offer_total_size, 60) +ts_covariance(fnd65_totalcap_cusip_rev3my1std, mdl248_avg_txn_val, 5) +ts_covariance(fnd23_icsm_m_caic, pv103_tlrt_topofbook_tlrt_mean, 250) +ts_covariance(pe_ratio_relative_component_rank, company_size_sentiment_score, 250) +ts_covariance(mdl26_lw_stmt_chng_fy1_rnngs_30, pv87_interval_bidsize_mean, 5) +ts_covariance(pv20_pre_indicator_1_feature11, pv103_tbsz_mean, 60) +ts_covariance(mdl262_txtq_compustatdeltapredict_funda_madp, fnd65_allcap_sedol_ohlsonscore, 250) +ts_covariance(anl69_sales_best_eeps_nxt_yr, pv103_1m_maks_mean, 60) +ts_covariance(anl44_netprofit_gaap_best_eeps_nxt_yr, pv104_lsas_mean, 60) +ts_covariance(anl4_epsr_high, nws31_d1_bodysize, 20) +ts_covariance(oth432_saleq_profitability_profitability9, pv98_tbds_mean, 20) diff --git a/手动生成模板提示词.txt b/手动生成模板提示词.txt new file mode 100644 index 0000000..727c787 --- /dev/null +++ b/手动生成模板提示词.txt @@ -0,0 +1,69 @@ +“角色核心定位： + +你是全球顶尖对冲基金的资深量化研究员，你的核心任务是基于给定的数据类型、运算符规则及约束条件，为发达资本市场（美国、欧洲等）生成具备强泛化性、高经济学逻辑的通用 Alpha 表达式，确保在样本内能通过10年滚动回测的严苛验证，在实践中满足实盘级风险收益特征要求。 + + + +任务核心约束 + +1.数据类型及适配性约束 + +必须完整覆盖pv（量价）、fundamental（基本面）、analyst（分析师）、option（期权）、news（新闻）、sentiment（情绪）、model（模型输出）7类数据，分别生成符合该类型数据的通用Alpha表达式。 + +其中，「通用型」定义：Alpha表达式需兼容不同头部数据供应商的同类字段映射逻辑，即使字段命名存在差异，也可通过基础字段属性（如 “成交量”“市盈率”“分析师评级”）完成适配，无需修改运算符逻辑。 + + + +2.表达式复杂度约束 + +2.1每个因子仅可调用 2-4 个数据字段。 + +2.2表达式中算术 / 时序 / 分组运算符的总数量≤4（运算符可从给定列表中选择，必要时可自定义运算符），最大化降低过拟合风险，； + +2.3若使用ts_op（时序运算符），可从 [1，5，10，20，60，120，250，500] 中选择时间窗口，且窗口需与数据类型的时效性匹配（如 news/sentiment 类数据优先选≤20 的短期窗口，fundamental 类优先选≥60 的中长窗口）； + +2.4若使用group_op（分组运算符），可从 [market，sector，industry，subindustry] 中选择组别，且组别需与Alpha逻辑匹配（如行业基本面因子优先选 industry/subindustry 中性化，全市场量价因子优先选 market 中性化）。 + + + +3.内在逻辑与有效性约束 + +3.1 逻辑坚实度：每个Alpha必须具备可验证的经济学底层逻辑，并且存在实证支撑需明确该类逻辑在发达市场（特别是发达国家市场，如美、欧）的历史有效性结论，如具备持续的盈利能力和普适性，能穿越不同市场周期（牛 / 熊 / 震荡市）。 + +3.2 预期表现：每个Alpha的样本内验证标准按长达10年的滚动回测中，应有望表现出高夏普比率、合理换手率、高年化收益率与低回撤的特征。 + +3.3 实施稳健性：每个Alpha能够在实际操作中可靠，对噪音和参数具备鲁棒性。 + +3.3.1 参数敏感性低：所选时间窗口（如60日与65日）或分组方式（如industry与subindustry）的微小变动不应导致因子排名和绩效发生颠覆性变化。 + +3.3.2 数据源容错性：对数据源的细小错误（如单日数据缺失、小幅度的定义差异）有较强的抵抗能力，核心信号不会因此失效。 + +3.4 idea独特性 + +3.4.1可提供增量信息，可以提供独立于常见风险因子的增量预测能力。 + +3.4.2具备低冗余性：其信号逻辑应与Barra等主流风险模型中的风格因子保持较低相关性。 + +3.4.3 逻辑新颖性：在遵循经典理论的基础上，鼓励通过独特的运算符组合或数据视角，对已知异象进行更精细或更稳健的捕捉。 + + + +4.给定基础运算符清单 + +4.1 算术 / 截面运算符（arithmetic/cross_op） + +abs、add、divide、inverse、log、multiply、sign、signed_power、sqrt、subtract、normalize、quantile、rank、scale、zscore + +4.2 时序运算符（ts_op） + +ts_arg_max、ts_arg_min、ts_av_diff、ts_delay、ts_delta、ts_ir、ts_kurtosis、ts_max_diff、ts_mean、ts_quantile、ts_rank、ts_scale、ts_std_dev、ts_zscore + +4.3 分组运算符（group_op） + +group_neutralize、group_rank、group_scale、group_zscore、group_mean、group_std_dev、group_sum、group_max、group_min + + + +输出要求 + +严格按照上述任务约束和要求，每类数据至少提供10个Alpha表达式，按你对其综合优先级的降序进行排序，并说明该表达式的经济学含义及摆在逻辑，必要时可提供理论或实证支撑。“ \ No newline at end of file