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922 lines
52 KiB
922 lines
52 KiB
任务指令
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你是一个WorldQuant WebSim因子工程师。你的任务是生成100个用于行业轮动策略的复合型Alpha因子表达式。
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核心规则
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设计维度框架
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维度1：时间序列动量（TM）
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核心概念：捕捉行业价格的趋势、动量和形态变化
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关键函数：
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ts_delta, ts_mean, ts_regression（获取斜率rettype参数）
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ts_decay_linear, ts_zscore, ts_rank
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ts_scale, ts_av_diff, ts_std_dev
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ts_corr, ts_covariance（用于行业内序列）
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设计思路：
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动量的变化率、加速度或平滑度构建
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动量衰减或增强模式识别
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价格与成交量关系的时序分析
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维度2：横截面领导力（CL）
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核心概念：识别行业内部的分化、龙头效应和相对强度
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关键函数：
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group_mean, group_std, group_rank
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group_zscore, group_neutralize, group_scale
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rank, zscore, quantile（横截面）
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bucket（用于龙头股筛选）
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设计思路：
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行业内部龙头股与平均表现的差异
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行业成分股的离散度分析
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相对排名的变化和稳定性
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维度3：市场状态适应性（MS）
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核心概念：根据市场环境动态调整因子逻辑
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关键函数：
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ts_rank, if_else, 条件判断运算符
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ts_std_dev（用于波动率调整）
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ts_regression（不同状态使用不同参数）
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trade_when（条件触发）
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设计思路：
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波动率调整的动量指标
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不同市场状态（高/低波动）使用不同的回顾期
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条件逻辑下的参数动态调整
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维度4：行业间联动（IS）
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核心概念：捕捉行业间的动量溢出和相关性变化
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关键函数：
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ts_corr, ts_covariance（跨行业）
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group_mean（用于行业指数）
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向量操作：vec_avg, vec_sum
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多序列相关性分析
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设计思路：
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领先-滞后行业的相关性分析
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行业间动量传导效应
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板块轮动的早期信号识别
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维度5：交易行为情绪（TS）
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核心概念：基于交易行为和情绪指标的反转信号
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关键函数：
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ts_corr(volume, close, d)（量价关系）
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ts_rank（历史相对位置）
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ts_zscore（极端值识别）
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days_from_last_change（事件驱动）
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设计思路：
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超买超卖状态识别
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交易拥挤度指标
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情绪极端值后的均值回归
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复合因子设计原则
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强制要求：
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每个表达式必须融合至少两个设计维度
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必须使用提供的操作符列表中的函数
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因子应具有经济逻辑解释性
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推荐组合模式：
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TM + CL：时序动量 + 横截面领导力
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示例：行业动量加速度 × 龙头股相对强度
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TM + MS：时序动量 + 状态适应性
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示例：波动率调整后的动量指标
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CL + IS：横截面 + 行业间联动
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示例：龙头股表现与相关行业的领先滞后关系
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MS + TS：状态适应 + 交易情绪
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示例：不同市场状态下的反转信号
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IS + TS：行业联动 + 交易情绪
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示例：行业间相关性变化与交易拥挤度
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参数化建议：
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使用不同的时间窗口组合（短/中/长周期）
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尝试不同的权重分配方式
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考虑非线性变换（log, power, sqrt）
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使用条件逻辑增强鲁棒性
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表达式构建指南
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基本结构：
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text
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复合因子 = 维度A组件 [运算符] 维度B组件 [条件调整]
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运算符使用策略：
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算术运算：add, subtract, multiply, divide
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非线性变换：log, power, sqrt, signed_power
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条件逻辑：if_else, and, or, 比较运算符
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标准化处理：normalize, winsorize, scale
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防止过拟合建议：
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避免过度复杂的嵌套
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使用经济直觉验证逻辑合理性
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考虑实际交易可行性
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包含风险控制元素（如波动率调整）
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*=====*
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操作符限制：只能且必须使用以下列表中提供的操作符。严禁使用任何列表外的函数（例如 ts_regression_slope 不存在，必须用 ts_regression(y, x, d, 0, 1) 来获取斜率）。
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abs, add, divide, multiply, subtract, log, power, sqrt, max, min, sign, reverse
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ts_mean, ts_sum, ts_std_dev, ts_delta, ts_delay, ts_zscore, ts_rank, ts_decay_linear, ts_corr, ts_covariance, ts_av_diff, ts_scale, ts_regression, ts_backfill
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group_mean, group_std, group_rank, group_zscore, group_neutralize, group_scale
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rank, scale, normalize, quantile, zscore, winsorize
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bucket, if_else, and, or, not, >, <, ==
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days_from_last_change, kth_element
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数据字段：假设主要数据字段为 close, high, low, volume, vwap。可安全使用。
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参数逻辑：参数d（回顾期）应在[5, 10, 20, 30, 60, 120]等具有市场意义（周、月、季度、半年）的数值中合理选择并差异化。
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行业隐含：通过group_mean、group_rank等函数或假设表达式在行业指数上运行来体现“行业”逻辑。
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输出格式：
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输出必须是且仅是 100行纯文本。
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每一行是一个完整、独立、语法正确的WebSim表达式。
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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。
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示例思维（仅供理解，不输出）
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一个融合“龙头股趋势加速度(M)”与“行业整体情绪背离(R)”的因子思路，可用你的操作符实现为：
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multiply( ts_delta(group_mean(ts_regression(close, ts_step(1), 20, 0, 1), bucket(rank(close), "0.7,1")), 5), reverse(ts_corr(ts_zscore(volume, 20), ts_zscore(close, 20), 10)) )
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这里，ts_regression(..., rettype=1)获取斜率代替动量，bucket(rank(close), "0.7,1")近似选取市值前30%的龙头股，ts_corr(...)衡量价量情绪，reverse将其转化为背离信号。
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现在，请严格遵守以上所有规则，开始生成100行可立即在WebSim中运行的复合因子表达式。
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**输出格式**(一行一个表达式, 只要表达式本身, 不要解释, 不需要序号, 也不要输出多余的东西)：
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表达式
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表达式
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表达式
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...
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表达式
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请提供具体的WQ表达式。
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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。
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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
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========================= 操作符开始 =======================================注意: Operator: 后面的是操作符,
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Description: 此字段后面的是操作符对应的描述或使用说明, Description字段后面的内容是使用说明, 不是操作符
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Operator: abs(x)
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Description: Absolute value of x
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Operator: add(x, y, filter = false), x + y
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Description: Add all inputs (at least 2 inputs required). If filter = true, filter all input NaN to 0 before adding
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Operator: densify(x)
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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
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Operator: divide(x, y), x / y
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Description: x / y
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Operator: inverse(x)
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Description: 1 / x
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Operator: log(x)
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Description: Natural logarithm. For example: Log(high/low) uses natural logarithm of high/low ratio as stock weights.
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Operator: max(x, y, ..)
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Description: Maximum value of all inputs. At least 2 inputs are required
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Operator: min(x, y ..)
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Description: Minimum value of all inputs. At least 2 inputs are required
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Operator: multiply(x ,y, ... , filter=false), x * y
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Description: Multiply all inputs. At least 2 inputs are required. Filter sets the NaN values to 1
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Operator: power(x, y)
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Description: x ^ y
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Operator: reverse(x)
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Description: - x
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Operator: sign(x)
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Description: if input > 0, return 1; if input < 0, return -1; if input = 0, return 0; if input = NaN, return NaN;
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Operator: signed_power(x, y)
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Description: x raised to the power of y such that final result preserves sign of x
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Operator: sqrt(x)
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Description: Square root of x
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Operator: subtract(x, y, filter=false), x - y
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Description: x-y. If filter = true, filter all input NaN to 0 before subtracting
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Operator: and(input1, input2)
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Description: Logical AND operator, returns true if both operands are true and returns false otherwise
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Operator: if_else(input1, input2, input 3)
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Description: If input1 is true then return input2 else return input3.
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Operator: input1 < input2
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Description: If input1 < input2 return true, else return false
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Operator: input1 <= input2
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Description: Returns true if input1 <= input2, return false otherwise
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Operator: input1 == input2
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Description: Returns true if both inputs are same and returns false otherwise
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Operator: input1 > input2
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Description: Logic comparison operators to compares two inputs
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Operator: input1 >= input2
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Description: Returns true if input1 >= input2, return false otherwise
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Operator: input1!= input2
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Description: Returns true if both inputs are NOT the same and returns false otherwise
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Operator: is_nan(input)
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Description: If (input == NaN) return 1 else return 0
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Operator: not(x)
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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).
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Operator: or(input1, input2)
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Description: Logical OR operator returns true if either or both inputs are true and returns false otherwise
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Operator: days_from_last_change(x)
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Description: Amount of days since last change of x
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Operator: hump(x, hump = 0.01)
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Description: Limits amount and magnitude of changes in input (thus reducing turnover)
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Operator: kth_element(x, d, k)
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Description: Returns K-th value of input by looking through lookback days. This operator can be used to backfill missing data if k=1
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Operator: last_diff_value(x, d)
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Description: Returns last x value not equal to current x value from last d days
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Operator: ts_arg_max(x, d)
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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
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Operator: ts_arg_min(x, d)
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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.
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Operator: ts_av_diff(x, d)
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Description: Returns x - tsmean(x, d), but deals with NaNs carefully. That is NaNs are ignored during mean computation
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Operator: ts_backfill(x,lookback = d, k=1, ignore="NAN")
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Description: Backfill is the process of replacing the NAN or 0 values by a meaningful value (i.e., a first non-NaN value)
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Operator: ts_corr(x, y, d)
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Description: Returns correlation of x and y for the past d days
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Operator: ts_count_nans(x ,d)
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Description: Returns the number of NaN values in x for the past d days
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Operator: ts_covariance(y, x, d)
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Description: Returns covariance of y and x for the past d days
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Operator: ts_decay_linear(x, d, dense = false)
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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.
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Operator: ts_delay(x, d)
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Description: Returns x value d days ago
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Operator: ts_delta(x, d)
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Description: Returns x - ts_delay(x, d)
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Operator: ts_mean(x, d)
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Description: Returns average value of x for the past d days.
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Operator: ts_product(x, d)
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Description: Returns product of x for the past d days
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Operator: ts_quantile(x,d, driver="gaussian" )
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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.
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Operator: ts_rank(x, d, constant = 0)
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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.
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Operator: ts_regression(y, x, d, lag = 0, rettype = 0)
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Description: Returns various parameters related to regression function
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Operator: ts_scale(x, d, constant = 0)
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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
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Operator: ts_std_dev(x, d)
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Description: Returns standard deviation of x for the past d days
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Operator: ts_step(1)
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Description: Returns days' counter
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Operator: ts_sum(x, d)
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Description: Sum values of x for the past d days.
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Operator: ts_zscore(x, d)
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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.
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Operator: normalize(x, useStd = false, limit = 0.0)
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Description: Calculates the mean value of all valid alpha values for a certain date, then subtracts that mean from each element
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Operator: quantile(x, driver = gaussian, sigma = 1.0)
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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
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Operator: rank(x, rate=2)
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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
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Operator: scale(x, scale=1, longscale=1, shortscale=1)
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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
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Operator: winsorize(x, std=4)
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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.
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Operator: zscore(x)
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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
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Operator: vec_avg(x)
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Description: Taking mean of the vector field x
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Operator: vec_sum(x)
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Description: Sum of vector field x
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Operator: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10")
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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
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Operator: trade_when(x, y, z)
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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
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Operator: group_backfill(x, group, d, std = 4.0)
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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
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Operator: group_mean(x, weight, group)
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Description: All elements in group equals to the mean
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Operator: group_neutralize(x, group)
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Description: Neutralizes Alpha against groups. These groups can be subindustry, industry, sector, country or a constant
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Operator: group_rank(x, group)
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Description: Each elements in a group is assigned the corresponding rank in this group
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Operator: group_scale(x, group)
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Description: Normalizes the values in a group to be between 0 and 1. (x - groupmin) / (groupmax - groupmin)
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Operator: group_zscore(x, group)
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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 =======================================
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========================= 数据字段开始 =======================================注意: DataField: 后面的是数据字段, DataFieldDescription: 此字段后面的是数据字段对应的描述或使用说明, DataFieldDescription字段后面的内容是使用说明, 不是数据字段
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DataField: pcr_vol_180
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DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 180 days in the future.
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DataField: option_breakeven_30
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DataFieldDescription: Price at which a stock's options with expiration 30 days in the future break even based on its recent bid/ask mean.
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DataField: call_breakeven_30
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DataFieldDescription: Price at which a stock's call options with expiration 30 days in the future break even based on its recent bid/ask mean.
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DataField: pcr_oi_120
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DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 120 days in the future.
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DataField: call_breakeven_180
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DataFieldDescription: Price at which a stock's call options with expiration 180 days in the future break even based on its recent bid/ask mean.
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DataField: call_breakeven_120
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DataFieldDescription: Price at which a stock's call options with expiration 120 days in the future break even based on its recent bid/ask mean.
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DataField: pcr_oi_1080
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DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 1080 days in the future.
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DataField: forward_price_360
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DataFieldDescription: Forward price at 360 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
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DataField: option_breakeven_180
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DataFieldDescription: Price at which a stock's options with expiration 180 days in the future break even based on its recent bid/ask mean.
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DataField: pcr_vol_10
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DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 10 days in the future.
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DataField: option_breakeven_10
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DataFieldDescription: Price at which a stock's options with expiration 10 days in the future break even based on its recent bid/ask mean.
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DataField: pcr_oi_90
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DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 90 days in the future.
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DataField: forward_price_20
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DataFieldDescription: Forward price at 20 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
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DataField: call_breakeven_90
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DataFieldDescription: Price at which a stock's call options with expiration 90 days in the future break even based on its recent bid/ask mean.
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DataField: pcr_vol_60
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DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 60 days in the future.
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DataField: option_breakeven_20
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DataFieldDescription: Price at which a stock's options with expiration 20 days in the future break even based on its recent bid/ask mean.
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DataField: option_breakeven_60
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DataFieldDescription: Price at which a stock's options with expiration 60 days in the future break even based on its recent bid/ask mean.
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DataField: put_breakeven_150
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DataFieldDescription: Price at which a stock's put options with expiration 150 days in the future break even based on its recent bid/ask mean.
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DataField: put_breakeven_30
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DataFieldDescription: Price at which a stock's put options with expiration 30 days in the future break even based on its recent bid/ask mean.
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DataField: pcr_vol_20
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DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 20 days in the future.
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DataField: call_breakeven_360
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DataFieldDescription: Price at which a stock's call options with expiration 360 days in the future break even based on its recent bid/ask mean.
|
|
DataField: option_breakeven_720
|
|
DataFieldDescription: Price at which a stock's options with expiration 720 days in the future break even based on its recent bid/ask mean.
|
|
DataField: forward_price_30
|
|
DataFieldDescription: Forward price at 30 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
|
|
DataField: pcr_oi_30
|
|
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 30 days in the future.
|
|
DataField: forward_price_90
|
|
DataFieldDescription: Forward price at 90 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
|
|
DataField: option_breakeven_1080
|
|
DataFieldDescription: Price at which a stock's options with expiration 1080 days in the future break even based on its recent bid/ask mean.
|
|
DataField: put_breakeven_1080
|
|
DataFieldDescription: Price at which a stock's put options with expiration 1080 days in the future break even based on its recent bid/ask mean.
|
|
DataField: pcr_vol_150
|
|
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 150 days in the future.
|
|
DataField: option_breakeven_150
|
|
DataFieldDescription: Price at which a stock's options with expiration 150 days in the future break even based on its recent bid/ask mean.
|
|
DataField: put_breakeven_20
|
|
DataFieldDescription: Price at which a stock's put options with expiration 20 days in the future break even based on its recent bid/ask mean.
|
|
DataField: fnd6_newqeventv110_pncwiepq
|
|
DataFieldDescription: Core Pension Without Interest Adjustment Basic EPS Effect Preliminary
|
|
DataField: fnd6_ivst
|
|
DataFieldDescription: Short-Term Investments - Total
|
|
DataField: fnd6_newqv1300_invrmq
|
|
DataFieldDescription: Inventory - Raw Materials
|
|
DataField: fnd6_newqv1300_tfvceq
|
|
DataFieldDescription: Total Fair Value Changes including Earnings
|
|
DataField: fnd6_newa2v1300_mii
|
|
DataFieldDescription: Noncontrolling Interest (Income Account)
|
|
DataField: fnd6_newqeventv110_glcedq
|
|
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) Diluted EPS
|
|
DataField: fnd6_npq
|
|
DataFieldDescription: Notes Payable
|
|
DataField: fnd6_newqeventv110_reunaq
|
|
DataFieldDescription: Unadjusted Retained Earnings
|
|
DataField: fnd6_newqeventv110_prcpepsq
|
|
DataFieldDescription: Core Post-Retirement Adjustment Basic EPS Effect Preliminary
|
|
DataField: fnd6_newqeventv110_xidoq
|
|
DataFieldDescription: Extraordinary Items and Discontinued Operations
|
|
DataField: fnd6_newa2v1300_oancf
|
|
DataFieldDescription: Operating Activities - Net Cash Flow
|
|
DataField: fnd6_newqeventv110_esoptq
|
|
DataFieldDescription: Preferred ESOP Obligation - Total
|
|
DataField: fnd6_mfma2_recch
|
|
DataFieldDescription: Accounts Receivable - Decrease (Increase)
|
|
DataField: fnd6_cptrank_gvkeymap
|
|
DataFieldDescription: technical code for a company, no need to use it for research
|
|
DataField: fnd6_newqv1300_reunaq
|
|
DataFieldDescription: Unadjusted Retained Earnings
|
|
DataField: fnd6_newqeventv110_piq
|
|
DataFieldDescription: Pretax Income
|
|
DataField: fnd6_cptnewqeventv110_oibdpq
|
|
DataFieldDescription: Operating Income Before Depreciation - Quarterly
|
|
DataField: fnd6_newqeventv110_miiq
|
|
DataFieldDescription: Noncontrolling Interest - Income Account
|
|
DataField: fnd6_newqv1300_aoq
|
|
DataFieldDescription: Assets - Other - Total
|
|
DataField: fnd6_ranks
|
|
DataFieldDescription: Ranking
|
|
DataField: fnd6_newqeventv110_xoptdqp
|
|
DataFieldDescription: Implied Option EPS Diluted Preliminary
|
|
DataField: fnd6_ceql
|
|
DataFieldDescription: Common Equity - Liquidation Value
|
|
DataField: fnd6_newqeventv110_aqpl1q
|
|
DataFieldDescription: Assets Level 1 (Quoted Prices)
|
|
DataField: fnd6_newqeventv110_seteps12
|
|
DataFieldDescription: Settlement (Litigation/Insurance) Basic EPS Effect 12MM
|
|
DataField: fnd6_eventv110_nrtxtepsq
|
|
DataFieldDescription: Nonrecurring Income Taxes Basic EPS Effect
|
|
DataField: fnd6_esubc
|
|
DataFieldDescription: Equity in Net Loss - Earnings
|
|
DataField: fnd6_msa
|
|
DataFieldDescription: Marketable Securities Adjustment
|
|
DataField: fnd6_newqv1300_ciderglq
|
|
DataFieldDescription: Comp Inc - Derivative Gains/Losses
|
|
DataField: ppent
|
|
DataFieldDescription: Property Plant and Equipment - Total (Net)
|
|
DataField: fnd6_dltp
|
|
DataFieldDescription: Long-Term Debt - Tied to Prime
|
|
DataField: scl12_alltype_buzzvec
|
|
DataFieldDescription: sentiment volume
|
|
DataField: scl12_alltype_sentvec
|
|
DataFieldDescription: sentiment
|
|
DataField: scl12_alltype_typevec
|
|
DataFieldDescription: instrument type index
|
|
DataField: scl12_buzz
|
|
DataFieldDescription: relative sentiment volume
|
|
DataField: scl12_buzz_fast_d1
|
|
DataFieldDescription: relative sentiment volume
|
|
DataField: scl12_buzzvec
|
|
DataFieldDescription: sentiment volume
|
|
DataField: scl12_sentiment
|
|
DataFieldDescription: sentiment
|
|
DataField: scl12_sentiment_fast_d1
|
|
DataFieldDescription: sentiment
|
|
DataField: scl12_sentvec
|
|
DataFieldDescription: sentiment
|
|
DataField: scl12_typevec
|
|
DataFieldDescription: instrument type index
|
|
DataField: snt_buzz
|
|
DataFieldDescription: negative relative sentiment volume, fill nan with 0
|
|
DataField: snt_buzz_bfl
|
|
DataFieldDescription: negative relative sentiment volume, fill nan with 1
|
|
DataField: snt_buzz_bfl_fast_d1
|
|
DataFieldDescription: negative relative sentiment volume, fill nan with 1
|
|
DataField: snt_buzz_fast_d1
|
|
DataFieldDescription: negative relative sentiment volume, fill nan with 0
|
|
DataField: snt_buzz_ret
|
|
DataFieldDescription: negative return of relative sentiment volume
|
|
DataField: snt_buzz_ret_fast_d1
|
|
DataFieldDescription: negative return of relative sentiment volume
|
|
DataField: snt_value
|
|
DataFieldDescription: negative sentiment, fill nan with 0
|
|
DataField: snt_value_fast_d1
|
|
DataFieldDescription: negative sentiment, fill nan with 0
|
|
DataField: analyst_revision_rank_derivative
|
|
DataFieldDescription: Change in ranking for analyst revisions and momentum compared to previous period.
|
|
DataField: cashflow_efficiency_rank_derivative
|
|
DataFieldDescription: Change in ranking for cash flow generation and profitability compared to previous period.
|
|
DataField: composite_factor_score_derivative
|
|
DataFieldDescription: Change in overall composite factor score from the prior period.
|
|
DataField: earnings_certainty_rank_derivative
|
|
DataFieldDescription: Change in ranking for earnings sustainability and certainty compared to previous period.
|
|
DataField: fscore_bfl_growth
|
|
DataFieldDescription: The purpose of this metric is to qualify the expected MT growth potential of the stock.
|
|
DataField: fscore_bfl_momentum
|
|
DataFieldDescription: The purpose of this metric is to identify stocks which are currently undergoing either up or downward analyst revisions.
|
|
DataField: fscore_bfl_profitability
|
|
DataFieldDescription: The purpose of this metric is to rank stock based on their ability to generate cash flows.
|
|
DataField: fscore_bfl_quality
|
|
DataFieldDescription: The purpose of this metric is to measure both the sustainability and certainty of earnings.
|
|
DataField: fscore_bfl_surface
|
|
DataFieldDescription: The static score. An index between 0 & 100 is applied for each stock and each composite factor - The first ranking is a pentagon surface-based score. The larger the surface, the higher the rank.
|
|
DataField: fscore_bfl_surface_accel
|
|
DataFieldDescription: The derivative score. In a second step, we calculate the derivative of this score (ie: Is the surface of the pentagon increasing or decreasing from the previous month?).
|
|
DataField: fscore_bfl_total
|
|
DataFieldDescription: The final score M-Score is a weighted average of both the Pentagon surface score and the Pentagon acceleration score.
|
|
DataField: fscore_bfl_value
|
|
DataFieldDescription: The purpose of this metric is to see if the stock is under or overpriced given several well known valuation standards.
|
|
DataField: fscore_growth
|
|
DataFieldDescription: The purpose of this metric is to qualify the expected MT growth potential of the stock.
|
|
DataField: fscore_momentum
|
|
DataFieldDescription: The purpose of this metric is to identify stocks which are currently undergoing either up or downward analyst revisions.
|
|
DataField: fscore_profitability
|
|
DataFieldDescription: The purpose of this metric is to rank stock based on their ability to generate cash flows.
|
|
DataField: fscore_quality
|
|
DataFieldDescription: The purpose of this metric is to measure both the sustainability and certainty of earnings.
|
|
DataField: fscore_surface
|
|
DataFieldDescription: The static score. An index between 0 & 100 is applied for each stock and each composite factor - The first ranking is a pentagon surface-based score. The larger the surface, the higher the rank.
|
|
DataField: fscore_surface_accel
|
|
DataFieldDescription: The derivative score. In a second step, we calculate the derivative of this score (ie: Is the surface of the pentagon increasing or decreasing from the previous month?).
|
|
DataField: fscore_total
|
|
DataFieldDescription: The final score M-Score is a weighted average of both the Pentagon surface score and the Pentagon acceleration score.
|
|
DataField: fscore_value
|
|
DataFieldDescription: The purpose of this metric is to see if the stock is under or overpriced given several well known valuation standards.
|
|
DataField: growth_potential_rank_derivative
|
|
DataFieldDescription: Change in ranking for medium-term growth potential compared to previous period.
|
|
DataField: multi_factor_acceleration_score_derivative
|
|
DataFieldDescription: Change in the acceleration of multi-factor score compared to previous period.
|
|
DataField: multi_factor_static_score_derivative
|
|
DataFieldDescription: Change in static multi-factor score compared to previous period.
|
|
DataField: relative_valuation_rank_derivative
|
|
DataFieldDescription: Change in ranking for valuation metrics compared to previous period.
|
|
DataField: snt_social_value
|
|
DataFieldDescription: Z score of sentiment
|
|
DataField: snt_social_volume
|
|
DataFieldDescription: Normalized tweet volume
|
|
DataField: beta_last_30_days_spy
|
|
DataFieldDescription: Beta to SPY in 30 Days
|
|
DataField: beta_last_360_days_spy
|
|
DataFieldDescription: Beta to SPY in 360 Days
|
|
DataField: beta_last_60_days_spy
|
|
DataFieldDescription: Beta to SPY in 60 Days
|
|
DataField: beta_last_90_days_spy
|
|
DataFieldDescription: Beta to SPY in 90 Days
|
|
DataField: correlation_last_30_days_spy
|
|
DataFieldDescription: Correlation to SPY in 30 Days
|
|
DataField: correlation_last_360_days_spy
|
|
DataFieldDescription: Correlation to SPY in 360 Days
|
|
DataField: correlation_last_60_days_spy
|
|
DataFieldDescription: Correlation to SPY in 60 Days
|
|
DataField: correlation_last_90_days_spy
|
|
DataFieldDescription: Correlation to SPY in 90 Days
|
|
DataField: systematic_risk_last_30_days
|
|
DataFieldDescription: Systematic Risk Last 30 Days
|
|
DataField: systematic_risk_last_360_days
|
|
DataFieldDescription: Systematic Risk Last 360 Days
|
|
DataField: systematic_risk_last_60_days
|
|
DataFieldDescription: Systematic Risk Last 60 Days
|
|
DataField: systematic_risk_last_90_days
|
|
DataFieldDescription: Systematic Risk Last 90 Days
|
|
DataField: unsystematic_risk_last_30_days
|
|
DataFieldDescription: Unsystematic Risk Last 30 Days - Relative to SPY
|
|
DataField: unsystematic_risk_last_360_days
|
|
DataFieldDescription: Unsystematic Risk Last 360 Days - Relative to SPY
|
|
DataField: unsystematic_risk_last_60_days
|
|
DataFieldDescription: Unsystematic Risk Last 60 Days - Relative to SPY
|
|
DataField: unsystematic_risk_last_90_days
|
|
DataFieldDescription: Unsystematic Risk Last 90 Days - Relative to SPY
|
|
DataField: anl4_tot_gw_ft
|
|
DataFieldDescription: Total Goodwill - forecast type (revision/new/...)
|
|
DataField: anl4_bvps_value
|
|
DataFieldDescription: Book value per share - announced financial value
|
|
DataField: max_reported_pretax_income_guidance_2
|
|
DataFieldDescription: Reported Pretax income- maximum guidance value
|
|
DataField: anl4_dei3lqfv110_item
|
|
DataFieldDescription: Financial item
|
|
DataField: anl4_netprofita_low
|
|
DataFieldDescription: Adjusted net income - the lowest estimation
|
|
DataField: anl4_eaz1laf_person
|
|
DataFieldDescription: Broker Id
|
|
DataField: total_assets_reported_value
|
|
DataFieldDescription: Total Assets - actual value
|
|
DataField: anl4_fsactualafv4_actual
|
|
DataFieldDescription: Announced financial data
|
|
DataField: anl4_bac1detailafv110_item
|
|
DataFieldDescription: Financial item
|
|
DataField: financing_cashflow_reported_value
|
|
DataFieldDescription: Cash Flow From Financing - Value
|
|
DataField: anl4_fsguidanceafv4_item
|
|
DataFieldDescription: Financial item
|
|
DataField: dividend_estimate_standard_deviation
|
|
DataFieldDescription: Dividend per share - standard deviation of estimations
|
|
DataField: anl4_cff_value
|
|
DataFieldDescription: Cash Flow From Financing - announced financial value
|
|
DataField: max_operating_cashflow_guidance_2
|
|
DataFieldDescription: The maximum guidance value for Cash Flow from Operations on an annual basis.
|
|
DataField: sales_estimate_average
|
|
DataFieldDescription: Sales - mean of estimations with a delay of 1 quarter
|
|
DataField: anl4_eaz2lltv110_estvalue
|
|
DataFieldDescription: Estimation value
|
|
DataField: shareholders_equity_reported_value
|
|
DataFieldDescription: Shareholders' Equity - Total Value
|
|
DataField: anl4_bac1detaillt_item
|
|
DataFieldDescription: Financial item
|
|
DataField: anl4_basicdetaillt_estvalue
|
|
DataFieldDescription: Estimation value
|
|
DataField: previous_recommendation_value
|
|
DataFieldDescription: The previous estimation of financial item for recommendation
|
|
DataField: anl4_ebitda_flag
|
|
DataFieldDescription: Earnings before interest, taxes, depreciation and amortization - forecast type (revision/new/...)
|
|
DataField: highest_sales_estimate
|
|
DataFieldDescription: Sales - The highest estimation for the annual period
|
|
DataField: anl4_median_epsreported
|
|
DataFieldDescription: GAAP Earnings per share - median of estimations
|
|
DataField: anl4_ads1detailafv110_person
|
|
DataFieldDescription: Broker Id
|
|
DataField: cashflow_per_share_max_guidance
|
|
DataFieldDescription: The maximum guidance value for Cash Flow Per Share on an annual basis.
|
|
DataField: anl4_fsdtlestmtafv4_item
|
|
DataFieldDescription: Financial item
|
|
DataField: anl4_basicconafv110_high
|
|
DataFieldDescription: The highest estimation
|
|
DataField: anl4_guiafv4_est
|
|
DataFieldDescription: Estimation value
|
|
DataField: anl4_fcfps_low
|
|
DataFieldDescription: Free Cash Flow Per Share - the lowest estimation
|
|
DataField: min_financing_cashflow_guidance
|
|
DataFieldDescription: Minimum guidance value for Cash Flow From Financing
|
|
DataField: pv13_hierarchy_min50_f3_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_h_min2_focused_pureplay_3000_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_rha2_min2_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_ompetitorgraphrank_hub_rank
|
|
DataFieldDescription: the HITS hub score of competitors
|
|
DataField: rel_num_all
|
|
DataFieldDescription: number of the companies whose product overlapped with the instrument
|
|
DataField: pv13_6l_scibr
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_h_min30_3000_mapped_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_h_min51_f3_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_reportperiodend
|
|
DataFieldDescription: Stated end date for the report
|
|
DataField: pv13_hierarchy_min22_1000_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min10_2k_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_r2_min5_1000_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_rha2_min5_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min52_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy23_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_f4_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_rha2_min20_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min51_f2_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy2_min2_1k_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_rha2_min2_1000_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: primary_sector_focused_company_count
|
|
DataFieldDescription: Number of companies primarily focused in a given sector.
|
|
DataField: pv13_r2_liquid_min10_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min20_3k_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min10_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_revere_country
|
|
DataFieldDescription: Country code
|
|
DataField: pv13_r2_min20_3000_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_revere_term
|
|
DataFieldDescription: Indicates when a sector is the terminal sector (i.e., no sub-sectors)
|
|
DataField: pv13_hierarchy_min51_f4_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min2_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min5_3000_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: historical_volatility_20
|
|
DataFieldDescription: Close-to-close Historical volatility over 20 days
|
|
DataField: implied_volatility_call_150
|
|
DataFieldDescription: At-the-money option-implied volatility for call Option for 150 days
|
|
DataField: implied_volatility_call_1080
|
|
DataFieldDescription: At-the-money option-implied volatility for call option for 1080 days
|
|
DataField: historical_volatility_150
|
|
DataFieldDescription: Close-to-close Historical volatility over 150 days
|
|
DataField: parkinson_volatility_30
|
|
DataFieldDescription: Parkinson model's historical volatility over 30 days
|
|
DataField: implied_volatility_mean_skew_20
|
|
DataFieldDescription: At-the-money option-implied volatility mean skew for 20 days
|
|
DataField: implied_volatility_mean_1080
|
|
DataFieldDescription: At-the-money option-implied volatility mean for 3 years
|
|
DataField: implied_volatility_put_720
|
|
DataFieldDescription: At-the-money option-implied volatility for Put Option for 720 days
|
|
DataField: implied_volatility_put_30
|
|
DataFieldDescription: At-the-money option-implied volatility for Put Option for 30 days
|
|
DataField: implied_volatility_call_60
|
|
DataFieldDescription: At-the-money option-implied volatility for call Option for 60 days
|
|
DataField: implied_volatility_mean_skew_30
|
|
DataFieldDescription: At-the-money option-implied volatility mean skew for 30 days
|
|
DataField: implied_volatility_call_720
|
|
DataFieldDescription: At-the-money option-implied volatility for call Option for 720 days
|
|
DataField: historical_volatility_90
|
|
DataFieldDescription: Close-to-close Historical volatility over 90 days
|
|
DataField: historical_volatility_10
|
|
DataFieldDescription: Close-to-close Historical volatility over 10 days
|
|
DataField: implied_volatility_mean_skew_90
|
|
DataFieldDescription: At-the-money option-implied volatility mean skew for 90 days
|
|
DataField: implied_volatility_mean_skew_60
|
|
DataFieldDescription: At-the-money option-implied volatility mean skew for 60 days
|
|
DataField: implied_volatility_mean_720
|
|
DataFieldDescription: At-the-money option-implied volatility mean for 720 days
|
|
DataField: parkinson_volatility_90
|
|
DataFieldDescription: Parkinson model's historical volatility over 90 days
|
|
DataField: implied_volatility_put_150
|
|
DataFieldDescription: At-the-money option-implied volatility for Put Option for 150 days
|
|
DataField: implied_volatility_mean_skew_120
|
|
DataFieldDescription: At-the-money option-implied volatility mean skew for 120 days
|
|
DataField: implied_volatility_mean_skew_360
|
|
DataFieldDescription: At-the-money option-implied volatility mean skew for 360 days
|
|
DataField: implied_volatility_call_180
|
|
DataFieldDescription: At-the-money option-implied volatility for call Option for 180 days
|
|
DataField: implied_volatility_put_60
|
|
DataFieldDescription: At-the-money option-implied volatility for Put Option for 60 days
|
|
DataField: parkinson_volatility_150
|
|
DataFieldDescription: Parkinson model's historical volatility over 150 days
|
|
DataField: implied_volatility_mean_10
|
|
DataFieldDescription: At-the-money option-implied volatility mean for 10 days
|
|
DataField: implied_volatility_mean_skew_10
|
|
DataFieldDescription: At-the-money option-implied volatility mean skew for 10 days
|
|
DataField: implied_volatility_mean_skew_180
|
|
DataFieldDescription: At-the-money option-implied volatility mean skew for 180 days
|
|
DataField: implied_volatility_put_180
|
|
DataFieldDescription: At-the-money option-implied volatility for put option for 180 days
|
|
DataField: implied_volatility_mean_360
|
|
DataFieldDescription: At-the-money option-implied volatility mean for 360 days
|
|
DataField: parkinson_volatility_180
|
|
DataFieldDescription: Parkinson model's historical volatility over 180 days
|
|
DataField: news_session_range
|
|
DataFieldDescription: Session High Price - Session Low Price
|
|
DataField: news_mins_20_chg
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|
DataFieldDescription: The minimum of L or S above for 20-minute bucket
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DataField: nws12_mainz_prevclose
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DataFieldDescription: Previous trading day's close price
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DataField: nws12_prez_opengap
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DataFieldDescription: (DayOpen - PrevClose) / PrevClose.
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DataField: nws12_prez_maxdown
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|
DataFieldDescription: Percent change from the price at the time of the news to the after the news low
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DataField: nws12_afterhsz_dayopen
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DataFieldDescription: Price at the session open
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DataField: nws12_mainz_57s
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DataFieldDescription: Number of minutes that elapsed before price went down 7.5 percentage points
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DataField: news_mins_10_pct_dn
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DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
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DataField: news_indx_perf
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|
DataFieldDescription: ((EODClose - TONLast) / TONLast) - ((SPYClose - SPYLast) / SPYLast)
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DataField: nws12_afterhsz_lowexcstddev
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DataFieldDescription: (TONLast - EODLow) / StdDev, where StdDev is one standard deviation for the close price for 30 calendar days
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DataField: nws12_afterhsz_1_minute
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DataFieldDescription: The percent change in price in the first minute following the news release
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DataField: nws12_afterhsz_epsactual
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DataFieldDescription: The actual Earnings Per Share value that was conveyed by the news release
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DataField: nws12_prez_60_min
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|
DataFieldDescription: The percent change in price in the first 60 minutes following the news release
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|
DataField: nws12_afterhsz_41rta
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DataFieldDescription: 14-day Average True Range
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DataField: nws12_allz_reportsess
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|
DataFieldDescription: Index of Session on which the spreadsheet is reporting
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DataField: nws12_mainz_rangestddev
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DataFieldDescription: (RangeAmt-AvgRange)/RangeStdDev, where AvgRange is the average of the daily range, and RangeStdDev is one standard deviation for the daily range, both for 30 calendar days
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|
DataField: nws12_afterhsz_1p
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|
DataFieldDescription: The minimum of L or S above for 1-minute bucket
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|
DataField: nws12_prez_tonhigh
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|
DataFieldDescription: Highest price reached during the session before the time of the news
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|
DataField: nws12_allz_provider
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|
DataFieldDescription: index of name of the news provider
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|
DataField: nws12_prez_tonlow
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|
DataFieldDescription: Lowest price reached during the session before the time of the news
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|
DataField: nws12_afterhsz_3s
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|
DataFieldDescription: Number of minutes that elapsed before price went down 3 percentage points
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|
DataField: nws12_prez_10_min
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|
DataFieldDescription: The percent change in price in the first 10 minutes following the news release
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|
DataField: nws12_mainz_short_interest
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|
DataFieldDescription: Total number of shares sold short divided by total number of shares outstanding
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|
DataField: nws12_prez_5_min
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|
DataFieldDescription: The percent change in price in the first 5 minutes following the news release
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|
DataField: news_pct_1min
|
|
DataFieldDescription: The percent change in price in the first minute following the news release
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|
DataField: nws12_prez_mov_vol
|
|
DataFieldDescription: 30-day moving average session volume
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|
DataField: nws12_mainz_2p
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|
DataFieldDescription: The minimum of L or S above for 2 minute bucket
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|
DataField: nws12_afterhsz_2l
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|
DataFieldDescription: Number of minutes that elapsed before price went up 2 percentage points
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|
DataField: news_close_vol
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|
DataFieldDescription: Main close volume
|
|
DataField: nws12_afterhsz_3l
|
|
DataFieldDescription: Number of minutes that elapsed before price went up 3 percentage points
|
|
DataField: top1000
|
|
DataFieldDescription: 20140630
|
|
DataField: top200
|
|
DataFieldDescription: 20140630
|
|
DataField: top3000
|
|
DataFieldDescription: 20140630
|
|
DataField: top500
|
|
DataFieldDescription: 20140630
|
|
DataField: topsp500
|
|
DataFieldDescription: 20140630
|
|
DataField: rp_nip_price
|
|
DataFieldDescription: News impact projection of stock price news
|
|
DataField: rp_nip_marketing
|
|
DataFieldDescription: News impact projection of marketing news
|
|
DataField: rp_ess_dividends
|
|
DataFieldDescription: Event sentiment score of dividends news
|
|
DataField: rp_ess_labor
|
|
DataFieldDescription: Event sentiment score of labor issues news
|
|
DataField: rp_css_marketing
|
|
DataFieldDescription: Composite sentiment score of marketing news
|
|
DataField: nws18_ghc_lna
|
|
DataFieldDescription: Change in analyst recommendation
|
|
DataField: rp_ess_credit_ratings
|
|
DataFieldDescription: Event sentiment score of credit ratings news
|
|
DataField: rp_css_legal
|
|
DataFieldDescription: Composite sentiment score of legal news
|
|
DataField: nws18_relevance
|
|
DataFieldDescription: Relevance of news to the company
|
|
DataField: rp_css_mna
|
|
DataFieldDescription: Composite sentiment score of mergers and acquisitions-related news
|
|
DataField: rp_css_society
|
|
DataFieldDescription: Composite sentiment score of society-related news
|
|
DataField: rp_css_business
|
|
DataFieldDescription: Composite sentiment score of business-related news
|
|
DataField: nws18_ber
|
|
DataFieldDescription: News sentiment specializing in earnings result
|
|
DataField: rp_ess_technical
|
|
DataFieldDescription: Event sentiment score based on technical analysis
|
|
DataField: rp_css_inverstor
|
|
DataFieldDescription: Composite sentiment score of investor relations news
|
|
DataField: rp_css_labor
|
|
DataFieldDescription: Composite sentiment score of labor issues news
|
|
DataField: nws18_qep
|
|
DataFieldDescription: News sentiment based on positive and negative words on global equity
|
|
DataField: rp_ess_business
|
|
DataFieldDescription: Event sentiment score of business-related news
|
|
DataField: nws18_nip
|
|
DataFieldDescription: Degree of impact of the news
|
|
DataField: nws18_sse
|
|
DataFieldDescription: Sentiment of phrases impacting the company
|
|
DataField: nws18_ssc
|
|
DataFieldDescription: Sentiment of the news calculated using multiple techniques
|
|
DataField: nws18_event_similarity_days
|
|
DataFieldDescription: Days since a similar event was detected
|
|
DataField: rp_css_credit
|
|
DataFieldDescription: Composite sentiment score of credit news
|
|
DataField: rp_css_technical
|
|
DataFieldDescription: Composite sentiment score based on technical analysis
|
|
DataField: rp_ess_society
|
|
DataFieldDescription: Event sentiment score of society-related news
|
|
DataField: rp_nip_technical
|
|
DataFieldDescription: News impact projection based on technical analysis
|
|
DataField: rp_css_ptg
|
|
DataFieldDescription: Composite sentiment score of price target news
|
|
DataField: rp_nip_assets
|
|
DataFieldDescription: News impact projection of assets news
|
|
DataField: rp_nip_ratings
|
|
DataFieldDescription: News impact projection of analyst ratings-related news
|
|
DataField: rp_ess_earnings
|
|
DataFieldDescription: Event sentiment score of earnings news
|
|
DataField: fnd2_a_inventoryrawmaterials
|
|
DataFieldDescription: Amount before valuation and LIFO reserves of raw materials expected to be sold, or consumed within 1 year or operating cycle, if longer.
|
|
DataField: fnd2_ebitfr
|
|
DataFieldDescription: EBIT, Foreign
|
|
DataField: fnd2_itxreclstatelocalitxes
|
|
DataFieldDescription: Amount of the difference between reported income tax expense (benefit) and expected income tax expense (benefit) computed by applying the domestic federal statutory income tax rates to pretax income (loss) from continuing operations attributable to state and local income tax expense (benefit).
|
|
DataField: fn_assets_fair_val_l1_a
|
|
DataFieldDescription: Asset Fair Value, Recurring, Level 1
|
|
DataField: fn_intangible_assets_accum_amort_q
|
|
DataFieldDescription: Accumulated amount of amortization of assets, excluding financial assets and goodwill, lacking physical substance with a finite life.
|
|
DataField: fn_new_shares_options_q
|
|
DataFieldDescription: Number of share options (or share units) exercised during the current period.
|
|
DataField: fn_comp_fair_value_assumptions_weighted_avg_vol_rate_a
|
|
DataFieldDescription: Weighted average expected volatility rate of share-based compensation awards.
|
|
DataField: fn_repayments_of_lines_of_credit_a
|
|
DataFieldDescription: Amount of cash outflow for payment of an obligation from a lender, including but not limited to, letter of credit, standby letter of credit and revolving credit arrangements.
|
|
DataField: fnd2_dbplanfvalpnas
|
|
DataFieldDescription: Fair value of assets that have been segregated and restricted to provide pension or postretirement benefits. Assets include, but are not limited to, stocks, bonds, other investments, earnings from investments, and contributions by the employer and employees.
|
|
DataField: fnd2_a_eplsbvdcpcstnrgsbaoo
|
|
DataFieldDescription: Unrecognized cost of unvested other share-based compensation awards.
|
|
DataField: fn_op_lease_min_pay_due_in_5y_a
|
|
DataFieldDescription: Amount of required minimum rental payments for operating leases having an initial or remaining non-cancelable lease term in excess of 1 year due in the 5th fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
|
|
DataField: fn_liab_fair_val_l1_q
|
|
DataFieldDescription: Liabilities Fair Value, Recurring, Level 1
|
|
DataField: fn_def_tax_liab_q
|
|
DataFieldDescription: Amount, after deferred tax asset, of deferred tax liability attributable to taxable differences without jurisdictional netting.
|
|
DataField: fnd2_q_flintasamt1expy5
|
|
DataFieldDescription: Amount of amortization expense for assets, excluding financial assets and goodwill, lacking physical substance with a finite life expected to be recognized during the 5th fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
|
|
DataField: fn_income_from_equity_investments_a
|
|
DataFieldDescription: Income From Equity Method Investments
|
|
DataField: fn_op_lease_min_pay_due_in_4y_a
|
|
DataFieldDescription: Amount of required minimum rental payments for operating leases having an initial or remaining non-cancelable lease term in excess of 1 year due in the 4th fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
|
|
DataField: fnd2_a_ltrmdmrepoplinytwo
|
|
DataFieldDescription: Amount of long-term debt payable, sinking fund requirements, and other securities issued that are redeemable by holder at fixed or determinable prices and dates maturing in the 2nd fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
|
|
DataField: fnd2_a_sbcpnargmsptawervl
|
|
DataFieldDescription: Amount of accumulated difference between fair value of underlying shares on dates of exercise and exercise price on options exercised (or share units converted) into shares.
|
|
DataField: fnd2_dbplanchgbnfolintcst
|
|
DataFieldDescription: Defined Benefit Plan Change In Benefit Obligation Interest Cost
|
|
DataField: fnd2_q_inventoryrawmaterials
|
|
DataFieldDescription: Amount before valuation and LIFO reserves of raw materials expected to be sold, or consumed within 1 year or operating cycle, if longer.
|
|
DataField: fn_repayments_of_lines_of_credit_q
|
|
DataFieldDescription: Amount of cash outflow for payment of an obligation from a lender, including but not limited to, letter of credit, standby letter of credit and revolving credit arrangements.
|
|
DataField: fn_business_combination_assets_aquired_goodwill_q
|
|
DataFieldDescription: Business Combination, Portion of Purchase Price Allocated to Goodwill
|
|
DataField: fn_comp_options_exercises_weighted_avg_a
|
|
DataFieldDescription: Share-Based Compensation, Options Assumed, Weighted Average Exercise Price
|
|
DataField: fn_op_lease_rent_exp_a
|
|
DataFieldDescription: Rental expense for the reporting period incurred under operating leases, including minimum and any contingent rent expense, net of related sublease income.
|
|
DataField: fnd2_a_lhdiprtsg
|
|
DataFieldDescription: Amount before accumulated depreciation of additions or improvements to assets held under a lease arrangement.
|
|
DataField: fnd2_a_ltrmdmrepoplinyfour
|
|
DataFieldDescription: Amount of long-term debt payable, sinking fund requirements, and other securities issued that are redeemable by holder at fixed or determinable prices and dates maturing in the 4th fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
|
|
DataField: fnd2_propplteqmuflmeqmt
|
|
DataFieldDescription: PPE, Equipment, Useful Life, Minimum
|
|
DataField: fn_comp_not_rec_stock_options_a
|
|
DataFieldDescription: Unrecognized cost of unvested stock option awards.
|
|
DataField: fn_business_acq_ppne_a
|
|
DataFieldDescription: Business Combination, Assumed Property, Plant and Equipment
|
|
DataField: fnd2_a_sbcpnargmpmwggil
|
|
DataFieldDescription: Amount by which the current fair value of the underlying stock exceeds the exercise price of fully vested and expected to vest options outstanding.
|
|
DataField: adv20
|
|
DataFieldDescription: Average daily volume in past 20 days
|
|
DataField: cap
|
|
DataFieldDescription: Daily market capitalization (in millions)
|
|
DataField: close
|
|
DataFieldDescription: Daily close price
|
|
DataField: country
|
|
DataFieldDescription: Country grouping
|
|
DataField: currency
|
|
DataFieldDescription: Currency
|
|
DataField: cusip
|
|
DataFieldDescription: CUSIP Value
|
|
DataField: dividend
|
|
DataFieldDescription: Dividend
|
|
DataField: exchange
|
|
DataFieldDescription: Exchange grouping
|
|
DataField: high
|
|
DataFieldDescription: Daily high price
|
|
DataField: industry
|
|
DataFieldDescription: Industry grouping
|
|
DataField: isin
|
|
DataFieldDescription: ISIN Value
|
|
DataField: low
|
|
DataFieldDescription: Daily low price
|
|
DataField: market
|
|
DataFieldDescription: Market grouping
|
|
DataField: open
|
|
DataFieldDescription: Daily open price
|
|
DataField: returns
|
|
DataFieldDescription: Daily returns
|
|
DataField: sector
|
|
DataFieldDescription: Sector grouping
|
|
DataField: sedol
|
|
DataFieldDescription: Sedol
|
|
DataField: sharesout
|
|
DataFieldDescription: Daily outstanding shares (in millions)
|
|
DataField: split
|
|
DataFieldDescription: Stock split ratio
|
|
DataField: subindustry
|
|
DataFieldDescription: Subindustry grouping
|
|
DataField: ticker
|
|
DataFieldDescription: Ticker
|
|
DataField: volume
|
|
DataFieldDescription: Daily volume
|
|
DataField: vwap
|
|
DataFieldDescription: Daily volume weighted average price
|
|
========================= 数据字段结束 =======================================
|
|
|
|
|