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: 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: forward_price_90
DataFieldDescription: Forward price at 90 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: option_breakeven_10
DataFieldDescription: Price at which a stock's options with expiration 10 days in the future break even based on its recent bid/ask mean.
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_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_20
DataFieldDescription: Price at which a stock's call options with expiration 20 days in the future break even based on its recent bid/ask mean.
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: pcr_vol_all
DataFieldDescription: Ratio of put volume to call volume for all maturities on stock's options.
DataField: forward_price_1080
DataFieldDescription: Forward price at 1080 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_150
DataFieldDescription: Forward price at 150 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_120
DataFieldDescription: Price at which a stock's put options with expiration 120 days in the future break even based on its recent bid/ask mean.
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: put_breakeven_60
DataFieldDescription: Price at which a stock's put options with expiration 60 days in the future break even based on its recent bid/ask mean.
DataField: pcr_oi_360
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 360 days in the future.
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: forward_price_30
DataFieldDescription: Forward price at 30 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: 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: 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: call_breakeven_90
DataFieldDescription: Price at which a stock's call options with expiration 90 days in the future break even based on its recent bid/ask mean.
DataField: call_breakeven_150
DataFieldDescription: Price at which a stock's call options with expiration 150 days in the future break even based on its recent bid/ask mean.
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: option_breakeven_270
DataFieldDescription: Price at which a stock's options with expiration 270 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: 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_180
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 180 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: 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_90
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 90 days in the future.
DataField: fnd6_cptnewqv1300_ceqq
DataFieldDescription: Common/Ordinary Equity - Total
DataField: fnd6_newqeventv110_stkcpaq
DataFieldDescription: After-tax stock compensation
DataField: fnd6_newa2v1300_oiadp
DataFieldDescription: Operating Income After Depreciation
DataField: fnd6_txndb
DataFieldDescription: Net Deferred Tax Asset (Liab) - Total
DataField: fnd6_newqv1300_mibnq
DataFieldDescription: Non-Redeemable Noncontrolling Interest (Balance Sheet) - Quarterly
DataField: fnd6_optlife
DataFieldDescription: Life of Options - Assumption (# yrs)
DataField: fnd6_newqeventv110_xsgaq
DataFieldDescription: Selling, General and Administrative Expenses
DataField: enterprise_value
DataFieldDescription: Enterprise Value
DataField: fnd6_cptnewqv1300_actq
DataFieldDescription: Current Assets - Total
DataField: fnd6_cptnewqeventv110_rectq
DataFieldDescription: Receivables - Total
DataField: fnd6_newqv1300_xoprq
DataFieldDescription: Operating Expense - Total
DataField: fnd6_dvrated
DataFieldDescription: Indicated Annual Dividend Rate - Daily
DataField: fnd6_newqeventv110_glcea12
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) After-tax 12MM
DataField: fnd6_newa1v1300_dvc
DataFieldDescription: Dividends Common/Ordinary
DataField: fnd6_mfmq_cheq
DataFieldDescription: Cash and Short-Term Investments
DataField: fnd6_newqv1300_cshoq
DataFieldDescription: Common Shares Outstanding
DataField: fnd6_cisecgl
DataFieldDescription: Comp Inc - Securities Gains/Losses
DataField: fnd6_newqeventv110_stkcoq
DataFieldDescription: Stock Compensation Expense
DataField: fnd6_sics
DataFieldDescription: SIC Code
DataField: fnd6_txts
DataFieldDescription: Income Taxes
DataField: fnd6_newqeventv110_txditcq
DataFieldDescription: Deferred Taxes and Investment Tax Credit
DataField: fnd6_ivch
DataFieldDescription: Increase in Investments
DataField: fnd6_newqeventv110_txtq
DataFieldDescription: Income Taxes - Total
DataField: fnd6_cibegni
DataFieldDescription: Comp Inc - Beginning Net Income
DataField: fnd6_txfed
DataFieldDescription: Income Taxes - Federal
DataField: fnd6_txtubposdec
DataFieldDescription: Decrease - Current Tax Positions
DataField: fnd6_cld2
DataFieldDescription: Capitalized Leases - Due in 2nd Year
DataField: fnd6_drlt
DataFieldDescription: Deferred Revenue - Long-term
DataField: fnd6_newqeventv110_spceeps12
DataFieldDescription: S&P Core Earnings EPS Basic 12MM
DataField: fnd6_cptnewqv1300_dpq
DataFieldDescription: Depreciation and Amortization - Total
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: max_shareholders_equity_guidance
DataFieldDescription: The maximum guidance value for Total Shareholders' Equity.
DataField: anl4_rd_exp_low
DataFieldDescription: Research and Development Expense - the lowest estimation
DataField: anl4_adjusted_netincome_ft
DataFieldDescription: Adjusted net income - forecast type (revision/new/...)
DataField: anl4_cuo1actualqfv110_actual
DataFieldDescription: Announced financial data
DataField: stock_option_expense_max_guidance_qtr
DataFieldDescription: Stock option expense - maximum guidance value
DataField: anl4_median_epsreported
DataFieldDescription: GAAP Earnings per share - median of estimations
DataField: anl4_cfi_flag
DataFieldDescription: Cash Flow From Investing - forecast type (revision/new/...)
DataField: earnings_per_share_estimate_count
DataFieldDescription: Earnings per share - number of estimations
DataField: pretax_income_actual_reported_value
DataFieldDescription: Reported Pretax income- announced financial value
DataField: anl4_qfd1_az_hgih_vid
DataFieldDescription: Dividend per share - The highest estimation
DataField: min_customized_eps_guidance
DataFieldDescription: Customized Earnings per share - Minimum guidance value for the annual period
DataField: min_free_cash_flow_per_share_guidance
DataFieldDescription: Free cash flow per share - minimum guidance value for the annual period
DataField: anl4_netdebt_low
DataFieldDescription: Net debt - the lowest estimation
DataField: anl4_ebitda_flag
DataFieldDescription: Earnings before interest, taxes, depreciation and amortization - forecast type (revision/new/...)
DataField: anl4_qfv4_cfps_mean
DataFieldDescription: Cash Flow Per Share - average of estimations
DataField: anl4_netprofit_std
DataFieldDescription: Net profit - standard deviation of estimations
DataField: anl4_basicconqfv110_low
DataFieldDescription: The lowest estimation
DataField: dividend_previous_estimate_value
DataFieldDescription: The previous estimation of dividend
DataField: anl4_capex_std
DataFieldDescription: Capital Expenditures - standard deviation of estimations
DataField: anl4_basicdetailqfv110_estvalue
DataFieldDescription: Estimation value
DataField: dividend_estimate_maximum
DataFieldDescription: Dividend per share - The highest value among forecasts with a delay of 1 quarter
DataField: anl4_dts_rspe
DataFieldDescription: Reported Earnings per share - standard deviation of estimations
DataField: anl4_cfo_median
DataFieldDescription: Cash Flow From Operations - median of estimations
DataField: anl4_mark
DataFieldDescription: Recommendation consensus score
DataField: pretax_income_max_guidance_qtr
DataFieldDescription: The maximum guidance value for Pretax income.
DataField: sales_estimate_median_quarterly
DataFieldDescription: Sales - median of estimations
DataField: anl4_totgw_low
DataFieldDescription: Total Goodwill - The lowest estimation
DataField: anl4_ads1detailqfv110_person
DataFieldDescription: Broker Id
DataField: anl4_qf_az_eps_mean
DataFieldDescription: Earnings per share - mean of estimations
DataField: anl4_netdebt_flag
DataFieldDescription: Net debt - forecast type (revision/new/...)
DataField: pv13_new_2l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy2_min2_1k_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min20_513_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_index_cap
DataFieldDescription: Company market capitalization
DataField: pv13_rha2_min2_513_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_liquid_min5_sector
DataFieldDescription: grouping fields
DataField: pv13_di_5l
DataFieldDescription: grouping fields
DataField: pv13_reportperiodlen
DataFieldDescription: The number of units which the report covers prior to the stated end date
DataField: pv13_com_rk_au
DataFieldDescription: the HITS authority score of competitors
DataField: pv13_r2_liquid_min10_sector
DataFieldDescription: grouping fields
DataField: rel_ret_cust
DataFieldDescription: averaged one-day-return of the instrument's customers
DataField: pv13_hierarchy_min2_focused_pureplay_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy2_513_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_liquid_min2_sector
DataFieldDescription: grouping fields
DataField: pv13_ompetitorgraphrank_hub_rank
DataFieldDescription: the HITS hub score of competitors
DataField: pv13_revere_term
DataFieldDescription: Indicates when a sector is the terminal sector (i.e., no sub-sectors)
DataField: pv13_hierarchy_min30_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min52_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy23_513_sector
DataFieldDescription: grouping fields
DataField: pv13_ustomergraphrank_hub_rank
DataFieldDescription: the HITS hub score of customers
DataField: rel_ret_all
DataFieldDescription: Averaged one-day return of the companies whose product overlapped with the instrument
DataField: pv13_hierarchy_min2_focused_pureplay_513_sector
DataFieldDescription: grouping fields
DataField: rel_num_all
DataFieldDescription: number of the companies whose product overlapped with the instrument
DataField: pv13_hierarchy_min20_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min52_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_2k_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min10_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_min10_1000_sector
DataFieldDescription: grouping fields
DataField: pv13_new_5l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min20_3k_sector
DataFieldDescription: grouping fields
DataField: historical_volatility_60
DataFieldDescription: Close-to-close Historical volatility over 60 days
DataField: implied_volatility_mean_270
DataFieldDescription: At-the-money option-implied volatility mean for 270 days
DataField: parkinson_volatility_120
DataFieldDescription: Parkinson model's historical volatility over 120 days
DataField: implied_volatility_mean_skew_60
DataFieldDescription: At-the-money option-implied volatility mean skew for 60 days
DataField: implied_volatility_put_30
DataFieldDescription: At-the-money option-implied volatility for Put Option for 30 days
DataField: implied_volatility_call_120
DataFieldDescription: At-the-money option-implied volatility for call Option for 120 days
DataField: implied_volatility_put_90
DataFieldDescription: At-the-money option-implied volatility for Put Option for 90 days
DataField: parkinson_volatility_180
DataFieldDescription: Parkinson model's historical volatility over 180 days
DataField: implied_volatility_mean_skew_90
DataFieldDescription: At-the-money option-implied volatility mean skew for 90 days
DataField: implied_volatility_mean_720
DataFieldDescription: At-the-money option-implied volatility mean for 720 days
DataField: implied_volatility_put_270
DataFieldDescription: At-the-money option-implied volatility for Put Option for 270 days
DataField: historical_volatility_20
DataFieldDescription: Close-to-close Historical volatility over 20 days
DataField: historical_volatility_10
DataFieldDescription: Close-to-close Historical volatility over 10 days
DataField: implied_volatility_mean_20
DataFieldDescription: At-the-money option-implied volatility mean for 20 days
DataField: implied_volatility_mean_skew_30
DataFieldDescription: At-the-money option-implied volatility mean skew for 30 days
DataField: implied_volatility_put_20
DataFieldDescription: At-the-money option-implied volatility for Put Option for 20 days
DataField: implied_volatility_mean_120
DataFieldDescription: At-the-money option-implied volatility mean for 120 days
DataField: parkinson_volatility_10
DataFieldDescription: Parkinson model's historical volatility over 2 weeks
DataField: implied_volatility_call_150
DataFieldDescription: At-the-money option-implied volatility for call Option for 150 days
DataField: implied_volatility_put_720
DataFieldDescription: At-the-money option-implied volatility for Put Option for 720 days
DataField: parkinson_volatility_60
DataFieldDescription: Parkinson model's historical volatility over 60 days
DataField: implied_volatility_call_270
DataFieldDescription: At-the-money option-implied volatility for call Option for 270 days
DataField: implied_volatility_mean_150
DataFieldDescription: At-the-money option-implied volatility mean for 150 days
DataField: implied_volatility_mean_skew_270
DataFieldDescription: At-the-money option-implied volatility mean skew for 270 days
DataField: implied_volatility_mean_skew_20
DataFieldDescription: At-the-money option-implied volatility mean skew for 20 days
DataField: historical_volatility_120
DataFieldDescription: Close-to-close Historical volatility over 120 days
DataField: implied_volatility_mean_360
DataFieldDescription: At-the-money option-implied volatility mean for 360 days
DataField: implied_volatility_mean_90
DataFieldDescription: At-the-money option-implied volatility mean for 90 days
DataField: historical_volatility_150
DataFieldDescription: Close-to-close Historical volatility over 150 days
DataField: implied_volatility_call_360
DataFieldDescription: At-the-money option-implied volatility for call Option for 360 days
DataField: nws12_mainz_4s
DataFieldDescription: Number of minutes that elapsed before price went down 4 percentage points
DataField: nws12_mainz_3l
DataFieldDescription: Number of minutes that elapsed before price went up 3 percentage points
DataField: nws12_prez_volstddev
DataFieldDescription: (CurrentVolume - AvgVol)/VolStDev, where AvgVol is the average of the daily volume, and VolStdDev is one standard deviation for the daily volume, both for 30 calendar days
DataField: nws12_afterhsz_short_interest
DataFieldDescription: Total number of shares sold short divided by total number of shares outstanding
DataField: nws12_prez_tonlast
DataFieldDescription: Price at the time of news
DataField: nws12_prez_spylast
DataFieldDescription: Last Price of the SPY at the time of the news
DataField: news_eod_vwap
DataFieldDescription: Volume weighted average price between the time of news and the end of the session
DataField: nws12_mainz_allvwap
DataFieldDescription: Volume weighted average price of all sessions
DataField: nws12_mainz_newssess
DataFieldDescription: Index of session in which the news was reported
DataField: nws12_afterhsz_dayopen
DataFieldDescription: Price at the session open
DataField: news_mins_5_pct_up
DataFieldDescription: Number of minutes that elapsed before price went up 5 percentage points
DataField: nws12_afterhsz_result_vs_index
DataFieldDescription: ((EODClose - TONLast) / TONLast) - ((SPYClose - SPYLast) / SPYLast)
DataField: nws12_mainz_tonhigh
DataFieldDescription: Highest price reached during the session before the time of news
DataField: nws12_prez_prev_vol
DataFieldDescription: Previous day's session volume
DataField: nws12_prez_57p
DataFieldDescription: The minimum of L or S above for 7.5-minute bucket
DataField: news_tot_ticks
DataFieldDescription: Total number of ticks for the trading day
DataField: nws12_afterhsz_curr_vol
DataFieldDescription: Current day's session volume
DataField: news_mins_10_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: nws12_afterhsz_01s
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: nws12_prez_57l
DataFieldDescription: Number of minutes that elapsed before price went up 7.5 percentage points
DataField: nws12_prez_4p
DataFieldDescription: The minimum of L or S above for 4-minute bucket
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_rangeamt
DataFieldDescription: Session High Price - Session Low Price
DataField: news_high_exc_stddev
DataFieldDescription: (EODHigh - TONLast)/StdDev, where StdDev is one standard deviation for the close price for 30 calendar days
DataField: nws12_prez_newrecord
DataFieldDescription: Tracks whether the news is the first instance or a duplicate
DataField: nws12_mainz_prevwap
DataFieldDescription: Pre session volume weighted average price
DataField: nws12_afterhsz_atrratio
DataFieldDescription: Ratio of Today Range to 20-day average true range
DataField: news_ton_high
DataFieldDescription: Highest price reached during the session before the time of news
DataField: nws12_prez_2s
DataFieldDescription: Number of minutes that elapsed before price went down 2 percentage points
DataField: nws12_prez_short_interest
DataFieldDescription: Total number of shares sold short divided by total number of shares outstanding
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: rp_nip_inverstor
DataFieldDescription: News impact projection of investor relations news
DataField: nws18_event_relevance
DataFieldDescription: Relevance of the event to the story
DataField: rp_css_credit_ratings
DataFieldDescription: Composite sentiment score of credit ratings news
DataField: rp_css_credit
DataFieldDescription: Composite sentiment score of credit news
DataField: rp_ess_credit_ratings
DataFieldDescription: Event sentiment score of credit ratings news
DataField: nws18_ghc_lna
DataFieldDescription: Change in analyst recommendation
DataField: rp_css_product
DataFieldDescription: Composite sentiment score of product and service-related news
DataField: rp_ess_price
DataFieldDescription: Event sentiment score of stock price news
DataField: rp_nip_marketing
DataFieldDescription: News impact projection of marketing news
DataField: rp_ess_assets
DataFieldDescription: Event sentiment score of assets news
DataField: rp_ess_ratings
DataFieldDescription: Event sentiment score of analyst ratings-related news
DataField: rp_css_price
DataFieldDescription: Composite sentiment score of stock price news
DataField: rp_nip_product
DataFieldDescription: News impact projection of product and service-related news
DataField: rp_ess_mna
DataFieldDescription: Event sentiment score of mergers and acquisitions-related news
DataField: rp_ess_revenue
DataFieldDescription: Event sentiment score of revenue news
DataField: rp_css_society
DataFieldDescription: Composite sentiment score of society-related news
DataField: nws18_sse
DataFieldDescription: Sentiment of phrases impacting the company
DataField: rp_css_inverstor
DataFieldDescription: Composite sentiment score of investor relations news
DataField: rp_nip_ptg
DataFieldDescription: News impact projection of price target news
DataField: rp_css_legal
DataFieldDescription: Composite sentiment score of legal news
DataField: rp_nip_credit_ratings
DataFieldDescription: News impact projection of credit ratings news
DataField: rp_css_ratings
DataFieldDescription: Composite sentiment score of analyst ratings-related news
DataField: rp_ess_equity
DataFieldDescription: Event sentiment score of equity action news
DataField: nws18_bee
DataFieldDescription: News sentiment specializing in growth of earnings
DataField: rp_css_revenue
DataFieldDescription: Composite sentiment score of revenue news
DataField: rp_ess_technical
DataFieldDescription: Event sentiment score based on technical analysis
DataField: rp_ess_legal
DataFieldDescription: Event sentiment score of legal news
DataField: rp_css_earnings
DataFieldDescription: Composite sentiment score of earnings news
DataField: nws18_ber
DataFieldDescription: News sentiment specializing in earnings result
DataField: rp_ess_business
DataFieldDescription: Event sentiment score of business-related news
DataField: fn_comp_options_grants_weighted_avg_q
DataFieldDescription: Weighted average price at which grantees could have acquired the underlying shares with respect to stock options that were terminated.
DataField: fnd2_oprlsfmpdcurr
DataFieldDescription: Amount of required minimum rental payments for operating leases having an initial or remaining non-cancelable lease term in excess of 1 year due in the 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_inventoryfinishedgoods
DataFieldDescription: Amount before valuation and LIFO reserves of completed merchandise or goods expected to be sold within 1 year or operating cycle, if longer.
DataField: fn_comp_number_of_shares_authorized_q
DataFieldDescription: The maximum number of shares (or other type of equity) originally approved (usually by shareholders and board of directors), net of any subsequent amendments and adjustments, for awards under the equity-based compensation plan. As stock or unit options and equity instruments other than options are awarded to participants, the shares or units remain authorized and become reserved for issuance under outstanding awards (not necessarily vested).
DataField: fn_incremental_shares_attributable_to_share_based_payment_q
DataFieldDescription: Additional shares included in the calculation of diluted EPS as a result of the potentially dilutive effect of share-based payment arrangements using the treasury stock method.
DataField: fn_payments_to_acquire_businesses_net_of_cash_acquired_a
DataFieldDescription: The cash outflow associated with the acquisition of a business, net of the cash acquired from the purchase.
DataField: fnd2_a_lhdiprtsg
DataFieldDescription: Amount before accumulated depreciation of additions or improvements to assets held under a lease arrangement.
DataField: fn_repayments_of_lines_of_credit_q
DataFieldDescription: Amount of cash outflow for payment of an obligation from a lender, including but not limited to, letter of credit, standby letter of credit and revolving credit arrangements.
DataField: fnd2_a_frtandfixturesg
DataFieldDescription: Amount before accumulated depreciation of equipment commonly used in offices and stores that have no permanent connection to the structure of a building or utilities. Examples include, but are not limited to, desks, chairs, tables, and bookcases.
DataField: fn_assets_fair_val_l1_q
DataFieldDescription: Asset Fair Value, Recurring, Level 1
DataField: fn_comprehensive_income_net_of_tax_q
DataFieldDescription: Amount after tax of increase (decrease) in equity from transactions and other events and circumstances from net income and other comprehensive income, attributable to parent entity. Excludes changes in equity resulting from investments by owners and distributions to owners.
DataField: fn_op_lease_rent_exp_a
DataFieldDescription: Rental expense for the reporting period incurred under operating leases, including minimum and any contingent rent expense, net of related sublease income.
DataField: fnd2_a_restructuringcharges
DataFieldDescription: Amount of expenses associated with exit or disposal activities pursuant to an authorized plan. Excludes expenses related to a discontinued operation or an asset retirement obligation.
DataField: fn_derivative_notional_amount_q
DataFieldDescription: Nominal or face amount used to calculate payments on the derivative liability.
DataField: fnd2_a_sbcpnatqsttotnsvdptfv
DataFieldDescription: Fair value of share-based awards for which the grantee gained the right by satisfying service and performance requirements, to receive or retain shares or units, other instruments, or cash.
DataField: fn_accum_depr_depletion_and_amortization_ppne_q
DataFieldDescription: Amount of accumulated depreciation, depletion and amortization for physical assets used in the normal conduct of business to produce goods and services.
DataField: fn_derivative_fair_value_of_derivative_liability_a
DataFieldDescription: Fair value, before effects of master netting arrangements, of a financial liability or 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 liabilities elected not to be offset. Excludes liabilities not subject to a master netting arrangement.
DataField: fnd2_currfedtxexp
DataFieldDescription: Income Tax Expense, Current - Federal
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: fn_comp_options_exercises_weighted_avg_q
DataFieldDescription: Share-Based Compensation, Options Assumed, Weighted Average Exercise Price
DataField: fnd2_a_flintasacmamtzcsrld
DataFieldDescription: Finite Lived Intangible Assets Accumulated Amortization, Customer Related
DataField: fn_effect_of_exchange_rate_on_cash_and_equiv_q
DataFieldDescription: Amount of increase (decrease) from the effect of exchange rate changes on cash and cash equivalent balances held in foreign currencies.
DataField: fn_effect_of_exchange_rate_on_cash_and_equiv_a
DataFieldDescription: Amount of increase (decrease) from the effect of exchange rate changes on cash and cash equivalent balances held in foreign currencies.
DataField: fn_def_income_tax_expense_a
DataFieldDescription: Income Tax Expense, Deferred
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: 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: fn_comp_not_rec_stock_options_a
DataFieldDescription: Unrecognized cost of unvested stock option awards.
DataField: fnd2_a_flintasgcsrld
DataFieldDescription: Finite Lived Intangible Assets Gross, Customer Related
DataField: fnd2_a_stkrpeprogramardamt
DataFieldDescription: Amount of a stock repurchase plan authorized by an entity's Board of Directors.
DataField: fn_prepaid_expense_q
DataFieldDescription: Carrying amount for an unclassified balance sheet date of expenditures made in advance of when the economic benefit of the cost will be realized, and which will be expensed in future periods with the passage of time or when a triggering event occurs. For a classified balance sheet, represents the noncurrent portion of prepaid expenses (the current portion has a separate concept).
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 =======================================