任务指令
一、经济逻辑描述优化
视角一：市场摩擦的横截面测绘
核心经济逻辑：
市场摩擦创造系统性的定价延迟和反应差异。不同股票因流动性、投资者结构和交易机制差异，对相同市场信息的反应速度和程度不同。这些差异形成可预测的Alpha机会：
流动性溢价动态：低流动性股票因交易成本较高，需要更高的预期收益补偿。但流动性条件会随时间变化，形成动态的流动性溢价套利窗口。
信息扩散速度差异：机构持仓集中度高的股票信息反应更快，散户主导的股票反应更慢且易出现过度反应，创造套利空间。
交易冲击的持续性：大宗交易对价格的冲击在低流动性环境中衰减更慢，形成短期价格动量；在高流动性环境中衰减更快，易出现反转。
视角二：投资者注意力生态学
核心经济逻辑：
注意力是金融市场中的稀缺资源，其分配不均导致定价效率差异：
有限注意力约束：投资者无法同时处理所有信息，只能关注有限数量的股票，导致被忽视股票出现定价延迟。
注意力传染效应：当某行业或主题受到关注时，注意力会按特定路径扩散（龙头→二线→边缘），形成可预测的轮动模式。
注意力衰减曲线：事件驱动型关注会随时间衰减，但衰减速度因股票特质而异。快速衰减可能导致定价错误快速修正，缓慢衰减则可能维持定价偏差。
视角三：价格运动的形态语法
核心经济逻辑：
价格形态反映市场参与者的集体行为模式和心理预期：
技术分析的自我实现：广泛使用的技术指标（如支撑阻力位、均线系统）影响交易决策，形成可预测的价格行为。
叙事驱动的价格记忆：价格在关键历史位置的行为会形成市场“记忆”，影响未来在这些位置附近的交易决策。
多时间尺度协调：不同时间框架投资者的行为协调（共振）或冲突（背离）决定趋势的可持续性。
二、复合因子构建的经济逻辑规范
A. 领导力动量因子
经济逻辑：
成交量是市场关注度和资金流向的直接体现。大成交量股票通常由机构投资者主导，其价格变动反映更充分的信息和更强的共识。这种“聪明钱”效应使大成交量股票的动量信号更具预测性。同时，成交量的横截面分布反映不同股票在投资者注意力竞争中的相对地位。
经济学基础：
成交量与信息含量正相关（Kyle模型）
机构交易者具有信息优势
注意力驱动的资本流动
B. 状态自适应动量
经济逻辑：
市场波动率状态反映信息流的速度和市场不确定性水平。高波动环境通常伴随高频信息流和快速变化的预期，短期动量更有效；低波动环境反映稳定预期，长期动量更可靠。通过波动率状态动态调整动量窗口，可以避免在不同市场机制下使用不匹配的策略。
经济学基础：
波动率聚集现象
市场状态的持久性
信息处理速度与波动率的关系
C. 行业传导因子
经济逻辑：
行业间存在基本面关联（产业链）和资金面关联（配置资金流动）。强势行业的出现通常反映某种宏观或产业逻辑，这种逻辑会按特定顺序向相关行业传导（如上游→下游，龙头→配套）。传导速度受行业基本面关联度和市场情绪影响，创造可预测的轮动机会。
经济学基础：
产业价值链传递
资金配置的渐进调整
相关性结构的时变性
D. 情绪反转因子
经济逻辑：
交易活跃度反映市场情绪强度。过度交易往往伴随非理性繁荣或恐慌，此时趋势可能接近拐点；交易清淡则反映市场分歧或缺乏关注，趋势可能延续。结合趋势强度可以区分情绪驱动的短期反转和基本面驱动的长期反转。
经济学基础：
过度反应与修正
有限套利与情绪持续性
交易量作为情绪代理变量
三、参数选择的经济逻辑
回顾期选择依据：
5-10日：捕捉事件驱动型Alpha，反映短期信息冲击
20-30日：捕捉月度调仓效应和基本面预期调整
60-120日：捕捉季度业绩周期和行业轮动周期
阈值参数的经济含义：
0.5：中位数效应，反映平均或典型情况
0.7-0.8：极端情况识别，捕捉显著的异常或结构性变化
四、行业轮动的经济学原理
周期性轮动：宏观经济周期不同阶段对各行业影响不同（早周期、中周期、晚周期）
相对估值轮动：行业间估值差异回归均值驱动资金流动
风险偏好轮动：市场风险偏好变化影响不同风险特征行业的相对表现
政策驱动轮动：产业政策、监管变化创造结构性机会
技术创新扩散：新技术沿产业链扩散的顺序性
五、风险调整的经济逻辑
流动性风险补偿：低流动性股票需提供更高预期收益
波动率风险定价：高波动股票的风险溢价要求
相关性结构风险：行业间相关性变化对分散化效果的影响
尾部风险暴露：极端事件对不同行业的非对称影响
六、交易可行性的经济学考虑
交易成本内生性：流动性差的股票交易成本高，需要更强的Alpha信号
容量约束：策略容量受市场深度限制
市场影响成本：大额交易对价格的冲击
竞争性衰减：被广泛采用的Alpha会因套利而衰减
七、因子表达式的经济解释规范
每个表达式应明确回答：
捕捉什么市场异象？（例如：注意力驱动定价延迟、流动性溢价变化等）
为什么这个异象会持续存在？（行为偏差、制度约束、风险补偿等）
在什么市场环境下更有效？（高波动、低流动性、趋势市等）
可能失效的条件是什么？（市场机制变化、投资者结构变化等）
这样的经济逻辑描述确保了每个因子都有清晰的理论基础和经济直觉，而非纯粹的数据挖掘结果。
*=====*
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, 以及我提供的数据集, 进行生成,组合 100 个alpha：

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: forward_price_120
DataFieldDescription: Forward price at 120 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: call_breakeven_720
DataFieldDescription: Price at which a stock's call options with expiration 720 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_30
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 30 days in the future.
DataField: put_breakeven_180
DataFieldDescription: Price at which a stock's put options with expiration 180 days in the future break even based on its recent bid/ask mean.
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: call_breakeven_270
DataFieldDescription: Price at which a stock's call options with expiration 270 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: pcr_oi_90
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 90 days in the future.
DataField: forward_price_60
DataFieldDescription: Forward price at 60 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_20
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 20 days in the future.
DataField: option_breakeven_90
DataFieldDescription: Price at which a stock's options with expiration 90 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: 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_vol_10
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 10 days in the future.
DataField: put_breakeven_30
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.
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: pcr_vol_20
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 20 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: 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_oi_180
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 180 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_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: call_breakeven_180
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.
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: 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_180
DataFieldDescription: Forward price at 180 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_150
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 150 days in the future.
DataField: pcr_vol_30
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 30 days in the future.
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: fnd6_newa2v1300_opeps
DataFieldDescription: Earnings Per Share from Operations
DataField: fnd6_cstkcv
DataFieldDescription: Common Stock-Carrying Value
DataField: fnd6_itci
DataFieldDescription: Investment Tax Credit (Income Account)
DataField: fnd6_txo
DataFieldDescription: Income Taxes - Other
DataField: cash
DataFieldDescription: Cash
DataField: fnd6_mibn
DataFieldDescription: Noncontrolling Interests - Nonredeemable - Balance Sheet
DataField: fnd6_newqeventv110_tfvaq
DataFieldDescription: Total Fair Value Assets
DataField: fnd6_newqv1300_glcea12
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) After-tax 12MM
DataField: fnd6_loxdr
DataFieldDescription: Liabilities - Other - Excluding Deferred Revenue
DataField: fnd6_newqv1300_spiq
DataFieldDescription: Special Items
DataField: fnd6_newqeventv110_cshfdq
DataFieldDescription: Common Shares for Diluted EPS
DataField: cashflow_op
DataFieldDescription: Operating Activities - Net Cash Flow
DataField: fnd6_cld3
DataFieldDescription: Capitalized Leases - Due in 3rd Year
DataField: debt
DataFieldDescription: Debt
DataField: fnd6_fato
DataFieldDescription: Plant, Property and Equipment at Cost - Other
DataField: fnd6_dcpstk
DataFieldDescription: Convertible Debt and Preferred Stock
DataField: fnd6_newqeventv110_cicurrq
DataFieldDescription: Comp Inc - Currency Trans Adj
DataField: fnd6_newqeventv110_rcaq
DataFieldDescription: Restructuring Cost After-tax
DataField: income_beforeextra
DataFieldDescription: Income Before Extraordinary Items
DataField: fnd6_newqeventv110_prcpd12
DataFieldDescription: Core Post-Retirement Adjustment 12MM Diluted EPS Effect Preliminary
DataField: fnd6_dilavx
DataFieldDescription: Dilution Available - Excluding Extraordinary Items
DataField: fnd6_esubs
DataFieldDescription: Equity in Earnings
DataField: inventory
DataFieldDescription: Inventories - Total
DataField: fnd6_fiao
DataFieldDescription: Financing Activities - Other
DataField: fnd6_newqeventv110_invrmq
DataFieldDescription: Inventory - Raw Materials
DataField: fnd6_newqeventv110_pncippq
DataFieldDescription: Core Pension Interest Adjustment Pretax Preliminary
DataField: fnd6_adesinda_curcd
DataFieldDescription: ISO Currency Code - Company Annual Market
DataField: fnd6_cshtrq
DataFieldDescription: Common Shares Traded - Quarter
DataField: fnd6_ceql
DataFieldDescription: Common Equity - Liquidation Value
DataField: fnd6_newqv1300_glceeps12
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) Basic EPS Effect 12MM
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_fcf_low
DataFieldDescription: Free Cash Flow - The lowest estimation
DataField: est_cashflow_op
DataFieldDescription: Cash Flow From Operations - mean of estimations
DataField: max_book_value_per_share_guidance
DataFieldDescription: Book value per share - Maximum value among forecasts
DataField: dividend_min_guidance_value
DataFieldDescription: Minimum guidance value for Dividend per share on an annual basis
DataField: max_net_income_guidance
DataFieldDescription: The maximum guidance value for net profit.
DataField: anl4_netdebt_flag
DataFieldDescription: Net debt - forecast type (revision/new/...)
DataField: sales_min_guidance_value
DataFieldDescription: Minimum sales guidance for the annual period.
DataField: anl4_cff_mean
DataFieldDescription: Cash Flow From Financing - mean of estimations
DataField: anl4_fcf_flag
DataFieldDescription: Free cash flow - forecast type (revision/new/...)
DataField: free_cash_flow_reported_value
DataFieldDescription: Free cash flow value for the quarter.
DataField: actuals_value_currency_code
DataFieldDescription: Pricing Currency where the security trades
DataField: anl4_ebitda_high
DataFieldDescription: Earnings before interest, taxes, depreciation, and amortization - the highest estimation
DataField: anl4_ptp_median
DataFieldDescription: Pretax income - median of estimations
DataField: book_value_per_share_min_guidance_qtr
DataFieldDescription: Book value per share - minimum guidance value
DataField: min_research_development_expense_guidance_2
DataFieldDescription: Minimum guidance value for Research & Development Expense on an annual basis
DataField: research_development_expense_reported_value
DataFieldDescription: Research & Development (Income Statement) Value in Millions
DataField: min_total_assets_guidance
DataFieldDescription: Minimum guidance value for Total Assets
DataField: anl4_basicconafv110_low
DataFieldDescription: The lowest estimation
DataField: anl4_rd_exp_mean
DataFieldDescription: Research and Development Expense - mean of estimations
DataField: capital_expenditure_reported_value
DataFieldDescription: Capital Expenditures - Total (Cash Flow/Investing) (Millions)
DataField: anl4_cuo1conafv110_item
DataFieldDescription: Financial item
DataField: anl4_fsgdncbscv4_maxguidance
DataFieldDescription: Max guidance value
DataField: anl4_netdebt_mean
DataFieldDescription: Net debt - mean of estimations
DataField: anl4_netprofit_median
DataFieldDescription: Net profit - Median of estimations
DataField: est_sga
DataFieldDescription: SGA - mean of estimations
DataField: actuals_reporting_currency
DataFieldDescription: Home currency of instrument
DataField: anl4_epsr_high
DataFieldDescription: GAAP Earnings per share - The highest estimation
DataField: dividend_estimate_minimum
DataFieldDescription: Dividend per share - The lowest value among forecasts - D1
DataField: min_ebitda_guidance
DataFieldDescription: Minimum guidance value for Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA) - Annual
DataField: min_total_goodwill_guidance
DataFieldDescription: Total Goodwill - The lowest guidance value
DataField: pv13_hierarchy_min10_top3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min2_focused_sector
DataFieldDescription: Grouping fields for top 200
DataField: pv13_hierarchy_min40_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f2_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_only_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min20_f3_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min100_corr21_sector
DataFieldDescription: grouping fields
DataField: pv13_ompetitorgraphrank_hub_rank
DataFieldDescription: the HITS hub score of competitors
DataField: pv13_hierarchy_min30_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min50_f3_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min20_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min100_corr21_513_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_term
DataFieldDescription: Indicates when a sector is the terminal sector (i.e., no sub-sectors)
DataField: pv13_r2_min2_1000_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_pureplay_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_comproduct_company
DataFieldDescription: Company product
DataField: pv13_revere_city
DataFieldDescription: City code
DataField: pv13_hierarchy_min52_2k_sector
DataFieldDescription: grouping fields
DataField: pv13_ustomergraphrank_hub_rank
DataFieldDescription: the HITS hub score of customers
DataField: pv13_2l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f2_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f4_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min10_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_pureplay_only_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_industry_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_1l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_1000_513_sector
DataFieldDescription: grouping fields
DataField: implied_volatility_put_720
DataFieldDescription: At-the-money option-implied volatility for Put Option for 720 days
DataField: implied_volatility_call_180
DataFieldDescription: At-the-money option-implied volatility for call Option for 180 days
DataField: implied_volatility_call_360
DataFieldDescription: At-the-money option-implied volatility for call Option for 360 days
DataField: implied_volatility_mean_150
DataFieldDescription: At-the-money option-implied volatility mean for 150 days
DataField: implied_volatility_mean_skew_20
DataFieldDescription: At-the-money option-implied volatility mean skew for 20 days
DataField: implied_volatility_mean_skew_10
DataFieldDescription: At-the-money option-implied volatility mean skew for 10 days
DataField: parkinson_volatility_30
DataFieldDescription: Parkinson model's historical volatility over 30 days
DataField: implied_volatility_call_30
DataFieldDescription: At-the-money option-implied volatility for call Option for 30 days
DataField: historical_volatility_150
DataFieldDescription: Close-to-close Historical volatility over 150 days
DataField: implied_volatility_put_30
DataFieldDescription: At-the-money option-implied volatility for Put Option for 30 days
DataField: implied_volatility_put_90
DataFieldDescription: At-the-money option-implied volatility for Put Option for 90 days
DataField: implied_volatility_call_270
DataFieldDescription: At-the-money option-implied volatility for call Option for 270 days
DataField: historical_volatility_60
DataFieldDescription: Close-to-close Historical volatility over 60 days
DataField: implied_volatility_put_360
DataFieldDescription: At-the-money option-implied volatility for Put Option for 360 days
DataField: implied_volatility_call_60
DataFieldDescription: At-the-money option-implied volatility for call Option for 60 days
DataField: implied_volatility_mean_180
DataFieldDescription: At-the-money option-implied volatility mean for 180 days
DataField: implied_volatility_mean_720
DataFieldDescription: At-the-money option-implied volatility mean for 720 days
DataField: implied_volatility_call_10
DataFieldDescription: At-the-money option-implied volatility for call Option for 10 days
DataField: implied_volatility_mean_10
DataFieldDescription: At-the-money option-implied volatility mean for 10 days
DataField: implied_volatility_mean_360
DataFieldDescription: At-the-money option-implied volatility mean for 360 days
DataField: parkinson_volatility_90
DataFieldDescription: Parkinson model's historical volatility over 90 days
DataField: parkinson_volatility_10
DataFieldDescription: Parkinson model's historical volatility over 2 weeks
DataField: implied_volatility_mean_skew_30
DataFieldDescription: At-the-money option-implied volatility mean skew for 30 days
DataField: implied_volatility_call_1080
DataFieldDescription: At-the-money option-implied volatility for call option for 1080 days
DataField: implied_volatility_put_270
DataFieldDescription: At-the-money option-implied volatility for Put Option for 270 days
DataField: implied_volatility_call_90
DataFieldDescription: At-the-money option-implied volatility for call Option for 90 days
DataField: implied_volatility_mean_20
DataFieldDescription: At-the-money option-implied volatility mean for 20 days
DataField: implied_volatility_mean_skew_120
DataFieldDescription: At-the-money option-implied volatility mean skew for 120 days
DataField: parkinson_volatility_60
DataFieldDescription: Parkinson model's historical volatility over 60 days
DataField: implied_volatility_put_120
DataFieldDescription: At-the-money option-implied volatility for Put Option for 120 days
DataField: nws12_mainz_eodhigh
DataFieldDescription: Highest price reached between the time of news and the end of the session
DataField: news_mins_5_chg
DataFieldDescription: The minimum of L or S above for 5-minute bucket
DataField: nws12_afterhsz_eodhigh
DataFieldDescription: Highest price reached between the time of news and the end of the session
DataField: nws12_afterhsz_4p
DataFieldDescription: The minimum of L or S above for 4-minute bucket
DataField: news_pct_60min
DataFieldDescription: The percent change in price in the first 60 minutes following the news release
DataField: nws12_prez_prevday
DataFieldDescription: Percent change between the previous day's open and close
DataField: nws12_prez_57l
DataFieldDescription: Number of minutes that elapsed before price went up 7.5 percentage points
DataField: news_mins_10_chg
DataFieldDescription: The minimum of L or S above for 10-minute bucket
DataField: nws12_afterhsz_57l
DataFieldDescription: Number of minutes that elapsed before price went up 7.5 percentage points
DataField: nws12_prez_div_y
DataFieldDescription: Annual yield
DataField: nws12_mainz_5s
DataFieldDescription: Number of minutes that elapsed before price went down 5 percentage points
DataField: news_mins_20_chg
DataFieldDescription: The minimum of L or S above for 20-minute bucket
DataField: nws12_afterhsz_2p
DataFieldDescription: The minimum of L or S above for 2-minute bucket
DataField: nws12_prez_result_vs_index
DataFieldDescription: ((EODClose - TONLast) / TONLast) - ((SPYClose - SPYLast) / SPYLast)
DataField: nws12_prez_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: news_close_vol
DataFieldDescription: Main close volume
DataField: nws12_prez_2l
DataFieldDescription: Number of minutes that elapsed before price went up 2 percentage points
DataField: nws12_afterhsz_mov_vol
DataFieldDescription: 30-day moving average session volume
DataField: nws12_mainz_57p
DataFieldDescription: The minimum of L or S above for 7.5-minute bucket
DataField: nws12_afterhsz_3s
DataFieldDescription: Number of minutes that elapsed before price went down 3 percentage points
DataField: nws12_afterhsz_01s
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: nws12_mainz_eodlow
DataFieldDescription: Lowest price reached between the time of news and the end of the session.
DataField: nws12_afterhsz_result1
DataFieldDescription: Percent change between the price at the time of the news release to the price at the close of the session
DataField: news_low_exc_stddev
DataFieldDescription: (TONLast - EODLow) / StdDev, where StdDev is one standard deviation for the close price for 30 calendar days
DataField: nws12_prez_close_vol
DataFieldDescription: Main close volume
DataField: news_ratio_vol
DataFieldDescription: Curr_Vol / Mov_Vol
DataField: nws12_afterhsz_2s
DataFieldDescription: Number of minutes that elapsed before price went down 2 percentage points
DataField: nws12_mainz_57l
DataFieldDescription: Number of minutes that elapsed before price went up 7.5 percentage points
DataField: news_session_range_pct
DataFieldDescription: (Session High Price - Session Low Price) / Session Low Price.
DataField: news_ton_low
DataFieldDescription: Lowest price reached during the session before the time of the news
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: nws18_ber
DataFieldDescription: News sentiment specializing in earnings result
DataField: rp_nip_mna
DataFieldDescription: News impact projection of mergers and acquisitions-related news
DataField: nws18_bee
DataFieldDescription: News sentiment specializing in growth of earnings
DataField: rp_css_assets
DataFieldDescription: Composite sentiment score of assets news
DataField: rp_nip_business
DataFieldDescription: News impact projection of business-related news
DataField: rp_nip_assets
DataFieldDescription: News impact projection of assets news
DataField: rp_css_technical
DataFieldDescription: Composite sentiment score based on technical analysis
DataField: rp_css_credit_ratings
DataFieldDescription: Composite sentiment score of credit ratings news
DataField: rp_ess_price
DataFieldDescription: Event sentiment score of stock price news
DataField: rp_nip_technical
DataFieldDescription: News impact projection based on technical analysis
DataField: rp_ess_revenue
DataFieldDescription: Event sentiment score of revenue news
DataField: rp_css_ptg
DataFieldDescription: Composite sentiment score of price target news
DataField: rp_nip_labor
DataFieldDescription: News impact projection of labor issues news
DataField: rp_ess_ratings
DataFieldDescription: Event sentiment score of analyst ratings-related news
DataField: rp_nip_price
DataFieldDescription: News impact projection of stock price news
DataField: rp_css_earnings
DataFieldDescription: Composite sentiment score of earnings news
DataField: rp_ess_assets
DataFieldDescription: Event sentiment score of assets news
DataField: nws18_acb
DataFieldDescription: News sentiment specializing in corporate action announcements
DataField: rp_ess_legal
DataFieldDescription: Event sentiment score of legal news
DataField: rp_nip_inverstor
DataFieldDescription: News impact projection of investor relations news
DataField: rp_ess_insider
DataFieldDescription: Event sentiment score of insider trading news
DataField: rp_nip_credit_ratings
DataFieldDescription: News impact projection of credit ratings news
DataField: rp_nip_legal
DataFieldDescription: News impact projection of legal news
DataField: rp_nip_credit
DataFieldDescription: News impact projection of credit news
DataField: nws18_nip
DataFieldDescription: Degree of impact of the news
DataField: rp_css_partner
DataFieldDescription: Composite sentiment score of partnership news
DataField: rp_css_dividends
DataFieldDescription: Composite sentiment score of dividends news
DataField: rp_ess_product
DataFieldDescription: Event sentiment score of product and service-related news
DataField: nws18_qcm
DataFieldDescription: News sentiment of relevant news with high confidence
DataField: rp_nip_earnings
DataFieldDescription: News impact projection of earnings news
DataField: fn_derivative_fair_value_of_derivative_asset_a
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: 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: fnd2_a_blgandiprtsg
DataFieldDescription: Amount before accumulated depreciation of building structures held for productive use including addition, improvement, or renovation to the structure, including, but not limited to, interior masonry, interior flooring, electrical, and plumbing.
DataField: fn_oth_income_loss_fx_transaction_and_tax_translation_adj_q
DataFieldDescription: Amount after tax and reclassification adjustments of gain (loss) on foreign currency translation adjustments, foreign currency transactions designated and effective as economic hedges of a net investment in a foreign entity and intra-entity foreign currency transactions that are of a long-term-investment nature.
DataField: fn_employee_related_liab_q
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: fn_comp_options_exercisable_weighted_avg_q
DataFieldDescription: The weighted-average price as of the balance sheet date at which grantees can acquire the shares reserved for issuance on vested portions of options outstanding and currently exercisable under the stock option plan.
DataField: fnd2_propplteqmuflmameqmt
DataFieldDescription: PPE, Equipment, Useful Life, Maximum
DataField: fn_assets_fair_val_l1_q
DataFieldDescription: Asset Fair Value, Recurring, Level 1
DataField: fn_comp_not_rec_a
DataFieldDescription: Unrecognized cost of unvested share-based compensation awards.
DataField: fn_def_tax_liab_a
DataFieldDescription: Amount, after deferred tax asset, of deferred tax liability attributable to taxable differences without jurisdictional netting.
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_oth_comp_forfeitures_fair_value_a
DataFieldDescription: Annual Share Based Compensation Equity Instruments Other Than Options Forfeitures Weighted Average Grant Date Fair Value
DataField: fn_op_lease_min_pay_due_after_5y_a
DataFieldDescription: Amount of required minimum rental payments for operating leases having an initial or remaining non-cancelable lease term in excess of one year due after 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_avg_diluted_sharesout_adj_a
DataFieldDescription: The sum of dilutive potential common shares or units used in the calculation of the diluted per-share or per-unit computation.
DataField: fnd2_a_opclpsnprtmbnfplansajnt
DataFieldDescription: Amount after tax and reclassification adjustments, of (increase) decrease in accumulated other comprehensive (income) loss related to pension and other postretirement defined benefit plans.
DataField: fn_def_income_tax_expense_q
DataFieldDescription: Income Tax Expense, Deferred
DataField: fn_comp_options_out_number_q
DataFieldDescription: Number of options outstanding, including both vested and non-vested options.
DataField: fn_accum_oth_income_loss_fx_adj_net_of_tax_a
DataFieldDescription: Accumulated adjustment, net of tax, that results from the process of translating subsidiary financial statements and foreign equity investments into the reporting currency from the functional currency of the reporting entity, net of reclassification of realized foreign currency translation gains or losses.
DataField: fnd2_dbplanepdfbnfpnext12m
DataFieldDescription: Amount of benefits from a defined benefit plan expected to be paid in the next 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_lhdiprtsg
DataFieldDescription: Amount before accumulated depreciation of additions or improvements to assets held under a lease arrangement.
DataField: fnd2_currfrtxexp
DataFieldDescription: Income Tax Expense, Current - Foreign
DataField: fn_business_combination_assets_aquired_goodwill_q
DataFieldDescription: Business Combination, Portion of Purchase Price Allocated to Goodwill
DataField: fnd2_a_sbcpnargmsawpfipwerpr
DataFieldDescription: Weighted average price of options that were either forfeited or expired.
DataField: fn_goodwill_acquired_during_period_q
DataFieldDescription: Amount of increase in asset representing future economic benefits arising from other assets acquired in a business combination that are not individually identified and separately recognized resulting from a business combination.
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_comp_fair_value_assumptions_weighted_avg_vol_rate_a
DataFieldDescription: Weighted average expected volatility rate of share-based compensation awards.
DataField: fnd2_unrgtxbnfinregfcrps
DataFieldDescription: Amount of increase in unrecognized tax benefits resulting from tax positions that have been or will be taken in current period tax return.
DataField: fnd2_a_lineofcrfcyrmbrgcap
DataFieldDescription: Amount of borrowing capacity currently available under the credit facility (current borrowing capacity less the amount of borrowings outstanding).
DataField: fn_payments_for_repurchase_of_common_stock_q
DataFieldDescription: Value reported on Cash Flow Statement. May include shares repurchased as part of a buyback plan, as well as shares purchased for employee compensation, etc.
DataField: fnd2_itxreexftfedstyitxrt
DataFieldDescription: Income tax amount computed at the federal tax rate, before any adjustments
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 =======================================