任务指令
一、核心设计理念
你是一名WorldQuant WebSim因子工程师，需要设计用于行业轮动策略的复合型Alpha因子。所有因子必须基于以下三个创新视角构建，每个视角提供独特的研究框架：
视角一：市场摩擦的横截面测绘 (Cross-sectional Imaging of Market Frictions)
核心思想：市场摩擦（流动性差异、交易冲击、价格发现延迟）不是需要消除的噪音，而是Alpha的直接来源。主动测绘不同股票对相同指令流冲击的差异化反应模式。
关键研究维度：
    指令流冲击的"消化速率"图谱：测量单位异常交易量引发的价格冲击及其衰减速度。构建"冲击-衰减"二维坐标系，识别高摩擦（冲击大、衰减慢）与低摩擦（冲击小、衰减快）的股票集群。
    买卖失衡的"路径依赖"模式：分析订单流净额的时间序列特性（均值回归vs趋势持续），量化不同市场状态下订单流的自强化或自纠正机制。
    价格发现的"领地性"划分：分解价格变动的驱动来源（自身交易驱动vs行业/指数驱动），计算"价格发现自主权"指标，研究内生性与外生性股票在不同市场环境中的轮动规律。
视角二：投资者注意力的生态学系统 (Ecology of Investor Attention)
核心思想：金融市场是注意力资源的分配系统而非信息聚合器。Alpha来源于对注意力"聚集-分散-转移"动态的精准捕捉。
关键研究维度：
    注意力分布的"聚焦度"谱系：量化交易量/活跃度在时间维度上的集中程度（基尼系数、赫芬达尔指数），识别注意力爆发期、持续关注期和注意力真空期。
    行业内注意力的"级联传导"网络：建立领导者-追随者注意力传导模型，测量强势股票出现后，同行业其他股票的响应速度、响应强度和响应延迟。
    注意力惯性的"衰减曲线"：度量催化事件结束后，异常关注度回归基线的速度，构建"注意力记忆时长"因子，捕捉定价偏差的持续性。
视角三：价格运动的"形态语法"解析 (Morphological Syntax of Price Movements)
核心思想：价格运动具有类似语言的"语法结构"和"叙事连贯性"。市场参与者潜意识地识别并交易这些形态模式，为系统性形态识别提供Alpha机会。
关键研究维度：
    价格序列的"可压缩性"度量：使用简化算法（分段线性近似、趋势线拟合残差）量化价格运动的规律性程度，识别从混沌转向有序（或相反）的临界状态。
    关键价位的"叙事逻辑"强度：分析价格在历史关键节点（前高、前低、缺口、密集区）的行为一致性，量化"支撑阻力叙事"的连贯性得分。
    多时间尺度的"相位同步"分析：研究不同周期滤波序列（如5日、20日、60日均线）之间的领先滞后关系和同步程度，识别多周期共振的形成与瓦解过程。
二、因子构建方法论
2.1 数据字段使用规范
可用字段：
    close: 收盘价（唯一价格字段）
    volume: 成交量（用于规模代理、活跃度度量）
    returns: 收益率序列，定义为 ts_delta(close, 1) 或 divide(close, ts_delay(close, 1)) - 1
禁止字段：
    ❌ market_cap, marketcap, mkt_cap（不存在）
    ✅ 使用volume作为规模代理，必要时进行横截面排序和分组
2.2 复合因子构建框架
维度融合模板（至少选择2个维度组合）：
A. 领导力动量 = 时序动量 × 横截面领导力调整
text
逻辑：大成交量股票的动量信号更强、更持续
结构示例：group_mean(ts_delta(close, 20), 1, bucket(rank(volume), range="0,3,0.4"))
经济解释：测量不同成交量分组内价格变化的均值，捕捉大成交量群体的主导方向
B. 状态自适应动量 = 市场状态 × 动量周期选择
text
逻辑：高波动环境使用短期动量，低波动环境使用长期动量
结构示例：if_else(ts_std_dev(returns, 20) > 0.02, ts_delta(close, 5), ts_delta(close, 20))
经济解释：根据波动率状态动态调整动量计算窗口，适应不同市场环境
C. 行业传导因子 = 行业间相关性 × 领先滞后关系
text
逻辑：与强势行业保持高相关性且略有滞后的行业可能迎来轮动机会
结构示例：multiply(ts_corr(group_mean(returns, 1, industry_A), group_mean(returns, 1, industry_B), 30), ts_delta(close, 10))
经济解释：测量行业间联动强度与自身动量的协同效应
D. 情绪反转因子 = 过度交易信号 × 趋势强度
text
逻辑：在过度交易区域，强势趋势可能面临反转；在交易清淡区域，趋势可能延续
结构示例：multiply(reverse(ts_rank(divide(volume, ts_mean(volume, 20)), 10)), ts_delta(close, 20))
经济解释：交易活跃度异常高时反转动量信号，异常低时增强动量信号
2.3 关键操作符使用规范
1. ts_regression使用规范：
    ✅ 正确：reg_slope = ts_regression(close, ts_step(1), 30, 0, 1)
    ❌ 错误：避免深度嵌套，如ts_delta(ts_regression(close, ts_step(1), 30, 0, 1), 5)
    ✅ 替代方案：先计算回归斜率，再对其应用ts_delta
2. if_else条件表达式规范：
    ✅ 正确：if_else(ts_rank(ts_std_dev(returns, 60), 120) > 0.7, 短期动量, 长期动量)
    ❌ 错误：避免复杂序列比较，如ts_std_dev(returns, 60) > ts_mean(ts_std_dev(returns, 60), 120)
3. bucket分组函数规范：
    ✅ 正确：bucket(rank(volume), range="0,3,0.4") == 0（第一组为大成交量）
    ✅ 正确：group_mean(x, 1, bucket(rank(volume), range="0,3,0.4"))
    注意字符串格式：range="起始值,组数,步长" 或 buckets="分割点列表"
4. 行业处理函数：
    group_mean(x, weight, group): 计算组内加权平均
    group_neutralize(x, group): 对组内进行中性化处理
    group_rank(x, group): 计算组内排序
    group_scale(x, group): 组内标准化到[0,1]
    group_zscore(x, group): 计算组内z-score
2.4 参数选择逻辑
    回顾期d应从以下具有市场意义的数值中选择：[5, 10, 20, 30, 60, 120]
        5: 周度（5个交易日）
        10: 双周
        20: 月度（约20个交易日）
        30: 月半
        60: 季度
        120: 半年
    阈值参数从[0.5, 0.7, 0.8]中选择
    同一因子内不同组件的参数应差异化，体现多时间尺度融合
三、因子组件库（可自由组合）
3.1 动量类组件
    简单动量：ts_delta(close, {d})
    回归动量：ts_regression(close, ts_step(1), {d}, 0, 1)（返回斜率）
    加速动量：ts_delta(ts_delta(close, 5), 5)
    排名动量：ts_rank(ts_delta(close, 20), 60)
3.2 波动性与风险调整组件
    波动率：ts_std_dev(returns, {d})
    平均绝对收益：ts_mean(abs(returns), {d})
    波动率调整：divide(ts_delta(close, 20), ts_std_dev(returns, 20))
    波动率状态：ts_rank(ts_std_dev(returns, 20), 60)
3.3 成交量与活跃度组件
    成交量异常：divide(volume, ts_mean(volume, {d}))
    成交量z-score：ts_zscore(volume, {d})
    成交量排名：rank(volume)
    成交量分布：bucket(rank(volume), range="0,3,0.4")
3.4 横截面调整组件
    规模分组：if_else(rank(volume) > 0.7, 大市值组信号, 小市值组信号)
    相对强弱：divide(ts_delta(close, 10), group_mean(ts_delta(close, 10), 1, industry))
    行业中性化：group_neutralize(原始信号, industry)
3.5 相关性与时序关系组件
    时间序列相关性：ts_corr({x}, {y}, {d})
    协方差：ts_covariance({y}, {x}, {d})
    领先滞后关系：ts_corr(ts_delay(x, 1), y, d)
四、因子构建原则
4.1 复杂度控制原则
    嵌套层数建议不超过3层
    每个表达式应有清晰的经济逻辑解释
    避免过度优化和数据挖掘偏差
4.2 交易可行性原则
    严格避免未来函数（只能使用历史信息）
    考虑实际交易成本（避免高换手率因子）
    使用hump(x, hump=0.01)平滑信号变化，降低换手
4.3 风险控制原则
    包含波动率调整元素
    考虑极端值处理（使用winsorize(x, std=4)）
    进行适当的标准化（normalize()或zscore()）
4.4 行业轮动特异性
    必须包含行业维度处理（group_*函数）
    体现行业间传导、轮动、分化逻辑
    考虑行业相对强弱与绝对动量的结合
五、表达式构建示例框架
示例1：行业注意力传导因子
text
经济逻辑：捕捉强势行业对弱势行业的注意力传导效应，测量追随行业对领导行业信号的响应速度和强度。
组件分解：
1. 识别领导行业：过去5日行业动量排名前30%
2. 测量响应强度：自身收益率与领导行业收益率的滞后相关性
3. 调整响应延迟：根据成交量调整，大成交量股票响应更快
4. 行业相对位置：在自身行业内的动量排名
示例2：摩擦差异化的动量因子
text
经济逻辑：在高摩擦（低流动性）股票中寻找未被充分消化的动量，在低摩擦股票中寻找快速衰减的反转机会。
组件分解：
1. 摩擦测量：成交量冲击的价格影响半衰期
2. 动量计算：不同摩擦环境下的最优动量窗口
3. 横截面调整：同摩擦水平股票间的相对强弱
4. 行业中性化：控制行业风格暴露
示例3：多周期形态共振因子
text
经济逻辑：识别短期、中期、长期价格趋势进入同步状态（共振）的股票，这些股票往往有更强的趋势持续性。
组件分解：
1. 多周期滤波：5日、20日、60日价格序列
2. 相位同步测量：不同周期序列方向一致性的时间比例
3. 共振强度：同步期的动量加速度
4. 行业调整：与行业共振状态的相对差异
*=====*
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。
**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, 进行生成,组合因子：

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,
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
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: 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

DataField: pcr_vol_10
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 10 days in the future.
DataField: pcr_oi_120
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 120 days in the future.
DataField: pcr_vol_1080
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 1080 days in the future.
DataField: call_breakeven_1080
DataFieldDescription: Price at which a stock's call options with expiration 1080 days in the future break even based on its recent bid/ask mean.
DataField: option_breakeven_60
DataFieldDescription: Price at which a stock's options with expiration 60 days in the future break even based on its recent bid/ask mean.
DataField: call_breakeven_60
DataFieldDescription: Price at which a stock's call options with expiration 60 days in the future break even based on its recent bid/ask mean.
DataField: option_breakeven_30
DataFieldDescription: Price at which a stock's options with expiration 30 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_270
DataFieldDescription: Forward price at 270 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: forward_price_10
DataFieldDescription: Forward price at 10 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: put_breakeven_150
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.
DataField: pcr_oi_270
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 270 days in the future.
DataField: pcr_vol_360
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 360 days in the future.
DataField: put_breakeven_270
DataFieldDescription: Price at which a stock's put options with expiration 270 days in the future break even based on its recent bid/ask mean.
DataField: option_breakeven_180
DataFieldDescription: Price at which a stock's options with expiration 180 days in the future break even based on its recent bid/ask mean.
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: pcr_oi_20
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 20 days in the future.
DataField: put_breakeven_360
DataFieldDescription: Price at which a stock's put options with expiration 360 days in the future break even based on its recent bid/ask mean.
DataField: call_breakeven_360
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_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: forward_price_720
DataFieldDescription: Forward price at 720 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_720
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 720 days in the future.
DataField: forward_price_360
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.
DataField: pcr_vol_60
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 60 days in the future.
DataField: option_breakeven_360
DataFieldDescription: Price at which a stock's options with expiration 360 days in the future break even based on its recent bid/ask mean.
DataField: pcr_oi_10
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 10 days in the future.
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: pcr_vol_720
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 720 days in the future.
DataField: pcr_oi_150
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 150 days in the future.
DataField: call_breakeven_30
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.
DataField: pcr_vol_270
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 270 days in the future.
DataField: fnd6_cld4
DataFieldDescription: Capitalized Leases - Due in 4th Year
DataField: fnd6_sstk
DataFieldDescription: Sale of Common and Preferred Stock
DataField: goodwill
DataFieldDescription: Goodwill (net)
DataField: fnd6_txdc
DataFieldDescription: Deferred Taxes (Cash Flow)
DataField: fnd6_newqeventv110_miiq
DataFieldDescription: Noncontrolling Interest - Income Account
DataField: fnd6_newqeventv110_dtepq
DataFieldDescription: Extinguishment of Debt Pretax
DataField: fnd6_newqv1300_loq
DataFieldDescription: Liabilities - Other
DataField: fnd6_newqeventv110_prcpdq
DataFieldDescription: Core Post Retirement Adjustment Diluted EPS Effect Preliminary
DataField: fnd6_dd5
DataFieldDescription: Debt Due in 5th Year
DataField: fnd6_txs
DataFieldDescription: Income Taxes - State
DataField: fnd6_newqeventv110_acoq
DataFieldDescription: Current Assets - Other - Total
DataField: fnd6_newqeventv110_xoptdqp
DataFieldDescription: Implied Option EPS Diluted Preliminary
DataField: fnd6_txndbl
DataFieldDescription: Net Deferred Tax Liability
DataField: fnd6_newa2v1300_tstk
DataFieldDescription: Treasury Stock - Total (All Capital)
DataField: fnd6_newqeventv110_rrpq
DataFieldDescription: Reversal - Restructuring/Acquisition Pretax
DataField: fnd6_newa2v1300_txditc
DataFieldDescription: Deferred Taxes and Investment Tax Credit
DataField: fnd6_newqeventv110_chq
DataFieldDescription: Cash
DataField: ppent
DataFieldDescription: Property Plant and Equipment - Total (Net)
DataField: fnd6_recd
DataFieldDescription: Receivables - Estimated Doubtful
DataField: fnd6_mkvaltq
DataFieldDescription: Market Value - Total
DataField: fnd6_newa1v1300_acominc
DataFieldDescription: Accumulated Other Comprehensive Income (Loss)
DataField: fnd6_newqeventv110_prcraq
DataFieldDescription: Repurchase Price - Average per share
DataField: fnd6_newqeventv110_ibcomq
DataFieldDescription: Income Before Extraordinary Items - Available for Common
DataField: ebitda
DataFieldDescription: Earnings Before Interest
DataField: fnd6_ibs
DataFieldDescription: Income before Extraordinary Items
DataField: fnd6_txtubadjust
DataFieldDescription: Other Unrecognized Tax Benefit Adjustment
DataField: fnd6_newqv1300_rectaq
DataFieldDescription: Accum Other Comp Inc - Cumulative Translation Adjustments
DataField: fnd6_newqeventv110_aociderglq
DataFieldDescription: Accumulated Other Comprehensive Income - Derivatives Unrealized Gain/Loss
DataField: fnd6_newa1v1300_ivncf
DataFieldDescription: Investing Activities - Net Cash Flow
DataField: fnd6_esubs
DataFieldDescription: Equity in Earnings
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_basicconqfv110_mean
DataFieldDescription: Mean of estimations
DataField: anl4_capex_std
DataFieldDescription: Capital Expenditures - standard deviation of estimations
DataField: anl4_netprofit_flag
DataFieldDescription: Net profit - forecast type (revision/new/...)
DataField: min_shares_outstanding_guidance
DataFieldDescription: Minimum guidance value for Shares
DataField: estimate_value_currency_code
DataFieldDescription: Home currency of instrument
DataField: anl4_eaz2lrec_ratingvalue
DataFieldDescription: Score on the given instrument
DataField: max_ebitda_guidance
DataFieldDescription: The maximum guidance value for Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA) on an annual basis.
DataField: anl4_netprofit_median
DataFieldDescription: Net profit - Median of estimations
DataField: max_customized_eps_guidance
DataFieldDescription: The maximum guidance value for custom earnings per share on an annual basis.
DataField: anl4_eaz2lltv110_person
DataFieldDescription: Broker Id
DataField: anl4_afv4_maxguidance
DataFieldDescription: Max guidance value
DataField: sales_estimate_value
DataFieldDescription: Sales - Estimated value
DataField: est_ffo
DataFieldDescription: Funds From Operation - Summary on Estimations, Mean
DataField: max_reported_eps_guidance
DataFieldDescription: Reported Earnings Per Share - Maximum guidance value
DataField: shareholders_equity_actual_value
DataFieldDescription: Shareholders' Equity - Total Value
DataField: free_cash_flow_total
DataFieldDescription: Free Cash Flow value - Annual
DataField: anl4_bac1detailrec_item
DataFieldDescription: Financial item
DataField: min_free_cashflow_per_share_guidance
DataFieldDescription: Free cash flow per share - minimum guidance value
DataField: anl4_fcfps_flag
DataFieldDescription: Free cash flow per share - forecast type (revision/new/...)
DataField: anl4_ebitda_high
DataFieldDescription: Earnings before interest, taxes, depreciation, and amortization - the highest estimation
DataField: anl4_netprofita_median
DataFieldDescription: Adjusted net income - median of estimations
DataField: anl4_dez1basicafv4v104_est
DataFieldDescription: Estimation value
DataField: sales_estimate_average_annual
DataFieldDescription: Sales - mean of estimations
DataField: max_operating_cashflow_guidance
DataFieldDescription: The maximum guidance value for Cash Flow from Operations.
DataField: anl4_qfv4_eps_high
DataFieldDescription: Earnings per share - The highest estimation
DataField: anl4_cuo1detailqfv110_item
DataFieldDescription: Financial item
DataField: selling_general_admin_expense_max_guidance_qtr
DataFieldDescription: Selling, General & Admin Expenses - Maximum guidance value
DataField: anl4_afv4_actual
DataFieldDescription: Announced financial data
DataField: eps_adjusted_min_guidance_value
DataFieldDescription: The minimum guidance value for adjusted earnings per share excluding extraordinary items and stock option expenses on an annual basis.
DataField: guidance_value_currency_code_qtr
DataFieldDescription: Home currency of instrument
DataField: rel_num_cust
DataFieldDescription: number of the instrument's customers
DataField: pv13_reportperiodend
DataFieldDescription: Stated end date for the report
DataField: pv13_h_min2_focused_pureplay_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min52_2k_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_2k_513_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_min2_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min20_513_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min10_top3000_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_key_sector_total
DataFieldDescription: Number of key focus sectors for the company
DataField: pv13_hierarchy_f1_513_sector
DataFieldDescription: grouping fields
DataField: pv13_reveremap
DataFieldDescription: Mapping data
DataField: pv13_hierarchy_min50_f3_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_pureplay_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_com_rk_au
DataFieldDescription: the HITS authority score of competitors
DataField: pv13_hierarchy_min10_2k_sector
DataFieldDescription: grouping fields
DataField: pv13_new_1l_scibr
DataFieldDescription: grouping fields
DataField: pv13_r2_min10_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_min10_1000_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_term_sector_total
DataFieldDescription: Number of terminal sectors for the company
DataField: pv13_hierarchy_min5_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min5_corr21_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_country
DataFieldDescription: Country code
DataField: pv13_hierarchy_min25_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min54_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_liquid_min10_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_pureplay_sector
DataFieldDescription: grouping fields
DataField: pv13_h2_min2_1k_sector
DataFieldDescription: Grouping fields for top 1000
DataField: pv13_hierarchy_min52_2k_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min20_top3000_sector
DataFieldDescription: grouping fields
DataField: implied_volatility_mean_skew_180
DataFieldDescription: At-the-money option-implied volatility mean skew for 180 days
DataField: implied_volatility_call_20
DataFieldDescription: At-the-money option-implied volatility for call Option for 20 days
DataField: implied_volatility_mean_180
DataFieldDescription: At-the-money option-implied volatility mean for 180 days
DataField: implied_volatility_put_1080
DataFieldDescription: At-the-money option-implied volatility for Put Option for 3 years
DataField: implied_volatility_mean_skew_1080
DataFieldDescription: At-the-money option-implied volatility mean skew for 3 years
DataField: historical_volatility_150
DataFieldDescription: Close-to-close Historical volatility over 150 days
DataField: implied_volatility_put_60
DataFieldDescription: At-the-money option-implied volatility for Put Option for 60 days
DataField: implied_volatility_call_90
DataFieldDescription: At-the-money option-implied volatility for call Option for 90 days
DataField: implied_volatility_put_360
DataFieldDescription: At-the-money option-implied volatility for Put Option for 360 days
DataField: implied_volatility_mean_skew_150
DataFieldDescription: At-the-money option-implied volatility mean skew for 150 days
DataField: implied_volatility_call_10
DataFieldDescription: At-the-money option-implied volatility for call Option for 10 days
DataField: implied_volatility_put_90
DataFieldDescription: At-the-money option-implied volatility for Put Option for 90 days
DataField: implied_volatility_call_180
DataFieldDescription: At-the-money option-implied volatility for call Option for 180 days
DataField: implied_volatility_mean_90
DataFieldDescription: At-the-money option-implied volatility mean for 90 days
DataField: implied_volatility_mean_skew_120
DataFieldDescription: At-the-money option-implied volatility mean skew for 120 days
DataField: parkinson_volatility_120
DataFieldDescription: Parkinson model's historical volatility over 120 days
DataField: implied_volatility_put_10
DataFieldDescription: At-the-money option-implied volatility for Put Option for 10 days
DataField: historical_volatility_60
DataFieldDescription: Close-to-close Historical volatility over 60 days
DataField: parkinson_volatility_10
DataFieldDescription: Parkinson model's historical volatility over 2 weeks
DataField: implied_volatility_mean_20
DataFieldDescription: At-the-money option-implied volatility mean for 20 days
DataField: parkinson_volatility_150
DataFieldDescription: Parkinson model's historical volatility over 150 days
DataField: implied_volatility_mean_skew_20
DataFieldDescription: At-the-money option-implied volatility mean skew for 20 days
DataField: parkinson_volatility_180
DataFieldDescription: Parkinson model's historical volatility over 180 days
DataField: historical_volatility_20
DataFieldDescription: Close-to-close Historical volatility over 20 days
DataField: implied_volatility_mean_150
DataFieldDescription: At-the-money option-implied volatility mean for 150 days
DataField: parkinson_volatility_20
DataFieldDescription: Parkinson model's historical volatility over 20 days
DataField: implied_volatility_mean_10
DataFieldDescription: At-the-money option-implied volatility mean for 10 days
DataField: implied_volatility_mean_1080
DataFieldDescription: At-the-money option-implied volatility mean for 3 years
DataField: implied_volatility_mean_skew_60
DataFieldDescription: At-the-money option-implied volatility mean skew for 60 days
DataField: implied_volatility_mean_skew_360
DataFieldDescription: At-the-money option-implied volatility mean skew for 360 days
DataField: nws12_afterhsz_1p
DataFieldDescription: The minimum of L or S above for 1-minute bucket
DataField: news_close_vol
DataFieldDescription: Main close volume
DataField: nws12_afterhsz_prev_vol
DataFieldDescription: Previous day's session volume
DataField: nws12_prez_2s
DataFieldDescription: Number of minutes that elapsed before price went down 2 percentage points
DataField: nws12_afterhsz_allticks
DataFieldDescription: Total number of ticks for the trading day
DataField: news_post_vwap
DataFieldDescription: Post-session volume-weighted average price
DataField: nws12_prez_vol_ratio
DataFieldDescription: Curr_Vol / Mov_Vol
DataField: nws12_mainz_2l
DataFieldDescription: Number of minutes that elapsed before price went up 2 percentage points
DataField: nws12_prez_1s
DataFieldDescription: Number of minutes that elapsed before price went down 1 percentage point
DataField: nws12_afterhsz_spylast
DataFieldDescription: Last Price of the SPY at the time of the news
DataField: news_mins_3_pct_up
DataFieldDescription: Number of minutes that elapsed before price went up 3 percentage points
DataField: nws12_mainz_5p
DataFieldDescription: The minimum of L or S above for 5-minute bucket
DataField: nws12_mainz_eodclose
DataFieldDescription: Close price of the session
DataField: nws12_mainz_1l
DataFieldDescription: Number of minutes that elapsed before price went up 1 percentage point
DataField: nws12_prez_10_min
DataFieldDescription: The percent change in price in the first 10 minutes following the news release
DataField: nws12_afterhsz_reportsess
DataFieldDescription: Index of Session on which the spreadsheet is reporting
DataField: nws12_prez_4p
DataFieldDescription: The minimum of L or S above for 4-minute bucket
DataField: nws12_mainz_spylast
DataFieldDescription: Last Price of the SPY at the time of the news
DataField: nws12_afterhsz_maxdnamt
DataFieldDescription: The price at the time of the news minus the after the news low
DataField: nws12_prez_5l
DataFieldDescription: Number of minutes that elapsed before price went up 5 percentage points
DataField: nws12_afterhsz_1_minute
DataFieldDescription: The percent change in price in the first minute following the news release
DataField: news_mins_5_chg
DataFieldDescription: The minimum of L or S above for 5-minute bucket
DataField: nws12_mainz_short_interest
DataFieldDescription: Total number of shares sold short divided by total number of shares outstanding
DataField: nws12_prez_prev_vol
DataFieldDescription: Previous day's session volume
DataField: nws12_mainz_01s
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: nws12_afterhsz_sl
DataFieldDescription: Whether a long or short position would have been more advantageous: If (EODHigh - Last) > (Last - EODLow) Then LS = 1; If (EODHigh - Last) = (Last - EODLow) Then LS = 0; If (EODHigh - Last) < (Last - EODLow) Then LS = -1.
DataField: nws12_afterhsz_01s
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: nws12_prez_4s
DataFieldDescription: Number of minutes that elapsed before price went down 4 percentage points
DataField: news_mins_1_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 1 percentage point
DataField: news_pct_60min
DataFieldDescription: The percent change in price in the first 60 minutes following the news release
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: nws18_relevance
DataFieldDescription: Relevance of news to the company
DataField: rp_css_ratings
DataFieldDescription: Composite sentiment score of analyst ratings-related news
DataField: nws18_acb
DataFieldDescription: News sentiment specializing in corporate action announcements
DataField: rp_ess_society
DataFieldDescription: Event sentiment score of society-related news
DataField: rp_nip_price
DataFieldDescription: News impact projection of stock price news
DataField: rp_nip_credit_ratings
DataFieldDescription: News impact projection of credit ratings news
DataField: rp_ess_mna
DataFieldDescription: Event sentiment score of mergers and acquisitions-related news
DataField: rp_css_technical
DataFieldDescription: Composite sentiment score based on technical analysis
DataField: rp_css_price
DataFieldDescription: Composite sentiment score of stock price news
DataField: rp_nip_partner
DataFieldDescription: News impact projection of partnership news
DataField: rp_ess_credit_ratings
DataFieldDescription: Event sentiment score of credit ratings news
DataField: rp_nip_equity
DataFieldDescription: News impact projection of equity action news
DataField: rp_nip_mna
DataFieldDescription: News impact projection of mergers and acquisitions-related news
DataField: rp_ess_assets
DataFieldDescription: Event sentiment score of assets news
DataField: rp_css_mna
DataFieldDescription: Composite sentiment score of mergers and acquisitions-related news
DataField: rp_css_dividends
DataFieldDescription: Composite sentiment score of dividends news
DataField: rp_css_society
DataFieldDescription: Composite sentiment score of society-related news
DataField: rp_ess_labor
DataFieldDescription: Event sentiment score of labor issues news
DataField: rp_css_business
DataFieldDescription: Composite sentiment score of business-related news
DataField: nws18_ssc
DataFieldDescription: Sentiment of the news calculated using multiple techniques
DataField: rp_ess_dividends
DataFieldDescription: Event sentiment score of dividends news
DataField: rp_nip_society
DataFieldDescription: News impact projection of society-related news
DataField: rp_nip_technical
DataFieldDescription: News impact projection based on technical analysis
DataField: rp_nip_dividends
DataFieldDescription: News impact projection of dividends news
DataField: rp_ess_ratings
DataFieldDescription: Event sentiment score of analyst ratings-related news
DataField: nws18_qmb
DataFieldDescription: News sentiment specializing in editorials on global markets
DataField: rp_css_earnings
DataFieldDescription: Composite sentiment score of earnings news
DataField: rp_css_labor
DataFieldDescription: Composite sentiment score of labor issues news
DataField: rp_css_credit
DataFieldDescription: Composite sentiment score of credit news
DataField: nws18_sse
DataFieldDescription: Sentiment of phrases impacting the company
DataField: fnd2_a_fedstyitxrt
DataFieldDescription: Effective Income Tax Rate Reconciliation - Federal Statutory Income Tax Rate %
DataField: fnd2_a_dbplanepdrtnplas
DataFieldDescription: An amount calculated as a basis for determining the extent of delayed recognition of the effects of changes in the fair value of assets. The expected return on plan assets is determined based on the expected long-term rate of return on plan assets and the market-related value of plan assets.
DataField: fnd2_itxreexftfedstyitxrt
DataFieldDescription: Income tax amount computed at the federal tax rate, before any adjustments
DataField: fn_income_taxes_paid_q
DataFieldDescription: The amount of cash paid during the current period to foreign, federal, state, and local authorities as taxes on income.
DataField: fn_repurchased_shares_a
DataFieldDescription: Number of shares that have been repurchased during the period.
DataField: fn_liab_fair_val_l2_q
DataFieldDescription: Liabilities Fair Value, Recurring, Level 2
DataField: fnd2_unrgtxbnfdcfpprdtxpss
DataFieldDescription: Amount of decrease in unrecognized tax benefits resulting from tax positions that have been or will be taken in current period tax return.
DataField: fn_derivative_fair_value_of_derivative_asset_q
DataFieldDescription: Fair value, before effects of master netting arrangements, of a financial asset or other contract with one or more underlyings, notional amount or payment provision or both, and the contract can be net settled by means outside the contract or delivery of an asset. Includes assets elected not to be offset. Excludes assets not subject to a master netting arrangement.
DataField: fnd2_a_dbplanservicecst
DataFieldDescription: The actuarial present value of benefits attributed by the pension benefit formula to services rendered by employees during the period. The portion of the expected postretirement benefit obligation attributed to employee service during the period. The service cost component is a portion of the benefit obligation and is unaffected by the funded status of the plan.
DataField: fn_comp_fair_value_assumptions_weighted_avg_vol_rate_a
DataFieldDescription: Weighted average expected volatility rate of share-based compensation awards.
DataField: fnd2_sbcpnshardpreops
DataFieldDescription: Share-based compensation shares authorized under stock option plans exercise price range number of exercisable options
DataField: fn_def_income_tax_expense_a
DataFieldDescription: Income Tax Expense, Deferred
DataField: fn_repayments_of_debt_q
DataFieldDescription: The cash outflow during the period from the repayment of aggregate short-term and long-term debt. Excludes payment of capital lease obligations.
DataField: fn_employee_related_liab_a
DataFieldDescription: Total of the carrying values as of the balance sheet date of obligations incurred through that date and payable for obligations related to services received from employees, such as accrued salaries and bonuses, payroll taxes and fringe benefits. 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).
DataField: fnd2_a_gsles1xtinguishmentofd
DataFieldDescription: Difference between the fair value of payments made and the carrying amount of debt which is extinguished prior to maturity.
DataField: fn_finite_lived_intangible_assets_net_q
DataFieldDescription: Finite Lived Intangible Assets, Net
DataField: fn_line_of_credit_facility_max_borrowing_capacity_q
DataFieldDescription: Maximum borrowing capacity under the credit facility without consideration of any current restrictions on the amount that could be borrowed or the amounts currently outstanding under the facility.
DataField: fn_debt_instrument_carrying_amount_a
DataFieldDescription: Debt carrying amount
DataField: fn_debt_instrument_interest_rate_stated_percentage_q
DataFieldDescription: Stated percentage of interest rate on debt
DataField: fn_proceeds_from_stock_options_exercised_a
DataFieldDescription: The cash inflow associated with the amount received from holders exercising their stock options. This item inherently excludes any excess tax benefit, which the entity may have realized and reported separately.
DataField: fn_profit_loss_q
DataFieldDescription: The consolidated profit or loss for the period, net of income taxes, including the portion attributable to the noncontrolling interest.
DataField: fnd2_a_dbplanintcst
DataFieldDescription: The increase in a defined benefit pension plan's projected benefit obligation or a defined benefit postretirement plan's accumulated postretirement benefit obligation due to the passage of time.
DataField: fn_excess_tax_benefit_from_share_based_comp_fin_activities_a
DataFieldDescription: Amount of cash inflow from realized tax benefit related to deductible compensation cost reported on the entity's tax return for equity instruments in excess of the compensation cost for those instruments recognized for financial reporting purposes.
DataField: fnd2_a_sbcpnargtbysbpmtwpwrr
DataFieldDescription: Weighted average price at which grantees could have acquired the underlying shares with respect to stock options of the plan that expired.
DataField: fnd2_a_stkdrgprdvalnewissues
DataFieldDescription: Equity impact of the value of new stock issued during the period. Includes shares issued in an initial public offering or a secondary public offering.
DataField: fnd2_a_allfdbflaccrwriteoffs
DataFieldDescription: Amount of recoveries of receivables doubtful of collection that were previously charged off.
DataField: fn_oth_comp_grants_weighted_avg_grant_date_fair_value_q
DataFieldDescription: Quarterly Share-Based Compensation Equity Instruments Other Than Options Nonvested Weighted Average Grant Date Fair Value
DataField: fn_comp_options_exercisable_number_q
DataFieldDescription: The number of shares into which fully or partially vested stock options outstanding as of the balance sheet date can be currently converted under the option plan.
DataField: fn_accrued_liab_curr_q
DataFieldDescription: Carrying value as of the balance sheet date of obligations incurred and payable, pertaining to costs that are statutory in nature, are incurred on contractual obligations, or accumulate over time and for which invoices have not yet been received or will not be rendered.
DataField: fnd2_a_curritxexp
DataFieldDescription: Income Tax Expense, Current
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 =======================================