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_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_60
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 60 days in the future.
DataField: call_breakeven_10
DataFieldDescription: Price at which a stock's call options with expiration 10 days in the future break even based on its recent bid/ask mean.
DataField: option_breakeven_180
DataFieldDescription: Price at which a stock's options with expiration 180 days in the future break even based on its recent bid/ask mean.
DataField: 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_20
DataFieldDescription: Price at which a stock's options with expiration 20 days in the future break even based on its recent bid/ask mean.
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: call_breakeven_60
DataFieldDescription: Price at which a stock's call options with expiration 60 days in the future break even based on its recent bid/ask mean.
DataField: 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: 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: 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_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: 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: 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: 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: call_breakeven_1080
DataFieldDescription: Price at which a stock's call options with expiration 1080 days in the future break even based on its recent bid/ask mean.
DataField: pcr_vol_20
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 20 days in the future.
DataField: call_breakeven_360
DataFieldDescription: Price at which a stock's call options with expiration 360 days in the future break even based on its recent bid/ask mean.
DataField: pcr_oi_20
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 20 days in the future.
DataField: put_breakeven_90
DataFieldDescription: Price at which a stock's put options with expiration 90 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_30
DataFieldDescription: Forward price at 30 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: pcr_vol_180
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 180 days in the future.
DataField: pcr_vol_all
DataFieldDescription: Ratio of put volume to call volume for all maturities on stock's options.
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_720
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 720 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_150
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 150 days in the future.
DataField: forward_price_20
DataFieldDescription: Forward price at 20 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
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: 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: fnd6_esopct
DataFieldDescription: Common ESOP Obligation - Total
DataField: fnd6_newqeventv110_prcpd12
DataFieldDescription: Core Post-Retirement Adjustment 12MM Diluted EPS Effect Preliminary
DataField: fnd6_ciother
DataFieldDescription: Comp. Inc. - Other Adj.
DataField: fnd6_newa1v1300_aco
DataFieldDescription: Current Assets - Other - Total
DataField: fnd6_newa2v1300_spced
DataFieldDescription: S&P Core Earnings EPS Diluted
DataField: fnd6_newqeventv110_pnc12
DataFieldDescription: Pension Core Adjustment - 12mm
DataField: fnd6_xaccq
DataFieldDescription: Accrued Expenses
DataField: fnd6_recd
DataFieldDescription: Receivables - Estimated Doubtful
DataField: fnd6_newa1v1300_cshi
DataFieldDescription: Common Shares Issued
DataField: fnd6_newqv1300_cisecglq
DataFieldDescription: Comp Inc - Securities Gains/Losses
DataField: fnd6_newa1v1300_cogs
DataFieldDescription: Cost of Goods Sold
DataField: receivable
DataFieldDescription: Receivables - Total
DataField: fnd6_rea
DataFieldDescription: Retained Earnings - Restatement
DataField: fnd6_optvolq
DataFieldDescription: Volatility - Assumption (%)
DataField: fnd6_dm
DataFieldDescription: Debt - Mortgages & Other Secured
DataField: fnd6_newqeventv110_lcoq
DataFieldDescription: Current Liabilities - Other - Total
DataField: fnd6_txfo
DataFieldDescription: Income Taxes - Foreign
DataField: fnd6_newqv1300_acomincq
DataFieldDescription: Accumulated Other Comprehensive Income (Loss)
DataField: fnd6_txfed
DataFieldDescription: Income Taxes - Federal
DataField: fnd6_dltr
DataFieldDescription: Long-Term Debt - Reduction
DataField: fnd6_newqv1300_xoptq
DataFieldDescription: Implied Option Expense
DataField: fnd6_newqv1300_xsgaq
DataFieldDescription: Selling, General and Administrative Expenses
DataField: fnd6_newqeventv110_glcea12
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) After-tax 12MM
DataField: fnd6_newa2v1300_oiadp
DataFieldDescription: Operating Income After Depreciation
DataField: fnd6_divd
DataFieldDescription: Cash Dividends - Daily
DataField: fnd6_dd3
DataFieldDescription: Debt Due in 3rd Year
DataField: fnd6_newa1v1300_aocidergl
DataFieldDescription: Accum Other Comp Inc - Derivatives Unrealized Gain/Loss
DataField: fnd6_cisecgl
DataFieldDescription: Comp Inc - Securities Gains/Losses
DataField: fnd6_adesinda_curcd
DataFieldDescription: ISO Currency Code - Company Annual Market
DataField: fnd6_mfma1_dp
DataFieldDescription: Depreciation and Amortization
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_qfv4_eps_mean
DataFieldDescription: Earnings per share - mean of estimations
DataField: min_gross_income_guidance
DataFieldDescription: The minimum guidance value for Gross Income.
DataField: cashflow_per_share_median_value
DataFieldDescription: Cash Flow Per Share - Median value among forecasts
DataField: anl4_qf_az_div_mean
DataFieldDescription: Dividend per share - average of estimations
DataField: free_cash_flow_per_share_reported_value
DataFieldDescription: Free cash flow per share- announced financial value
DataField: ebitda_reported_value
DataFieldDescription: EBITDA value for the quarter.
DataField: anl4_af_eps_value
DataFieldDescription: Earnings Per Share - Actual Value
DataField: anl4_ptpr_flag
DataFieldDescription: Reported Pretax income - forecast type (revision/new/...)
DataField: anl4_af_cfps_value
DataFieldDescription: Cash Flow Per Share - Actual Value
DataField: anl4_qf_az_wol_spe
DataFieldDescription: Earnings per share - The lowest estimation
DataField: anl4_capex_number
DataFieldDescription: Capital Expenditures - number of estimations
DataField: min_capital_expenditure_guidance
DataFieldDescription: Minimum guidance value for Capital Expenditures
DataField: anl4_fcf_high
DataFieldDescription: Free cash flow - aggregation on estimations, max
DataField: anl4_bvps_low
DataFieldDescription: Book value - the lowest estimation, per share
DataField: min_tangible_book_value_per_share_guidance
DataFieldDescription: Tangible Book Value per Share - minimum guidance value
DataField: anl4_basicdetaillt_person
DataFieldDescription: Broker Id
DataField: anl4_eaz2lrec_person
DataFieldDescription: Broker Id
DataField: min_pretax_profit_guidance_2
DataFieldDescription: The minimum guidance value for Pretax income on an annual basis.
DataField: anl4_bvps_flag
DataFieldDescription: Book value per share - forecast type (revision/new/...)
DataField: anl4_cfi_number
DataFieldDescription: Cash Flow From Investing - number of estimations
DataField: sales_max_guidance_value
DataFieldDescription: Maximum guidance value for annual sales
DataField: est_fcf_ps
DataFieldDescription: Free Cash Flow Per Share - Mean of Estimations
DataField: anl4_cuo1guidaf_item
DataFieldDescription: Financial item
DataField: dividend_min_guidance_value
DataFieldDescription: Minimum guidance value for Dividend per share on an annual basis
DataField: anl4_netdebt_mean
DataFieldDescription: Net debt - mean of estimations
DataField: anl4_qfd1_az_div_number
DataFieldDescription: Dividend per share - number of estimations
DataField: min_ebit_guidance
DataFieldDescription: Minimum guidance value for Earnings Before Interest and Taxes (EBIT)
DataField: min_free_cash_flow_guidance
DataFieldDescription: The minimum guidance value for Free Cash Flow on an annual basis.
DataField: anl4_afv4_div_high
DataFieldDescription: Dividend per share - The highest estimation for the annual forecast.
DataField: shareholders_equity_actual_value
DataFieldDescription: Shareholders' Equity - Total Value
DataField: pv13_hierarchys32_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f1_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min5_513_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min30_3000_mapped_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy2_min2_1k_513_sector
DataFieldDescription: grouping fields
DataField: pv13_new_1l_scibr
DataFieldDescription: grouping fields
DataField: pv13_3l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min20_3k_sector
DataFieldDescription: grouping fields
DataField: pv13_new_6l_scibr
DataFieldDescription: grouping fields
DataField: pv13_r2_min2_1000_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f1_513_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_comproduct_company
DataFieldDescription: Company product
DataField: pv13_custretsig_retsig
DataFieldDescription: Sign of customer return
DataField: pv13_r2_min5_1000_sector
DataFieldDescription: grouping fields
DataField: pv13_reveremap
DataFieldDescription: Mapping data
DataField: pv13_hierarchy_min10_sector_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_level
DataFieldDescription: Level of the sector within the hierarchy
DataField: pv13_hierarchy_min2_pureplay_only_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min100_corr21_513_sector
DataFieldDescription: grouping fields
DataField: pv13_ustomergraphrank_page_rank
DataFieldDescription: the PageRank of customers
DataField: pv13_hierarchy_min2_focused_pureplay_513_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min2_focused_pureplay_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_only_513_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_country
DataFieldDescription: Country code
DataField: pv13_reportperiodlen
DataFieldDescription: The number of units which the report covers prior to the stated end date
DataField: pv13_rha2_min10_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_key_sector_total
DataFieldDescription: Number of key focus sectors for the company
DataField: rel_ret_comp
DataFieldDescription: Averaged one-day return of the competing companies
DataField: pv13_5l_scibr
DataFieldDescription: grouping fields
DataField: implied_volatility_mean_skew_90
DataFieldDescription: At-the-money option-implied volatility mean skew for 90 days
DataField: implied_volatility_put_1080
DataFieldDescription: At-the-money option-implied volatility for Put Option for 3 years
DataField: implied_volatility_put_120
DataFieldDescription: At-the-money option-implied volatility for Put Option for 120 days
DataField: implied_volatility_call_360
DataFieldDescription: At-the-money option-implied volatility for call Option for 360 days
DataField: implied_volatility_mean_120
DataFieldDescription: At-the-money option-implied volatility mean for 120 days
DataField: implied_volatility_mean_1080
DataFieldDescription: At-the-money option-implied volatility mean for 3 years
DataField: parkinson_volatility_180
DataFieldDescription: Parkinson model's historical volatility over 180 days
DataField: implied_volatility_call_60
DataFieldDescription: At-the-money option-implied volatility for call Option for 60 days
DataField: parkinson_volatility_150
DataFieldDescription: Parkinson model's historical volatility over 150 days
DataField: implied_volatility_put_90
DataFieldDescription: At-the-money option-implied volatility for Put Option for 90 days
DataField: implied_volatility_mean_270
DataFieldDescription: At-the-money option-implied volatility mean for 270 days
DataField: implied_volatility_call_270
DataFieldDescription: At-the-money option-implied volatility for call Option for 270 days
DataField: historical_volatility_150
DataFieldDescription: Close-to-close Historical volatility over 150 days
DataField: implied_volatility_call_20
DataFieldDescription: At-the-money option-implied volatility for call Option for 20 days
DataField: implied_volatility_put_30
DataFieldDescription: At-the-money option-implied volatility for Put Option for 30 days
DataField: implied_volatility_call_10
DataFieldDescription: At-the-money option-implied volatility for call Option for 10 days
DataField: implied_volatility_mean_skew_180
DataFieldDescription: At-the-money option-implied volatility mean skew for 180 days
DataField: implied_volatility_put_10
DataFieldDescription: At-the-money option-implied volatility for Put Option for 10 days
DataField: implied_volatility_put_360
DataFieldDescription: At-the-money option-implied volatility for Put Option for 360 days
DataField: historical_volatility_120
DataFieldDescription: Close-to-close Historical volatility over 120 days
DataField: implied_volatility_mean_skew_10
DataFieldDescription: At-the-money option-implied volatility mean skew for 10 days
DataField: historical_volatility_20
DataFieldDescription: Close-to-close Historical volatility over 20 days
DataField: implied_volatility_mean_20
DataFieldDescription: At-the-money option-implied volatility mean for 20 days
DataField: historical_volatility_30
DataFieldDescription: Close-to-close Historical volatility over 30 days
DataField: implied_volatility_mean_skew_720
DataFieldDescription: At-the-money option-implied volatility mean skew for 720 days
DataField: historical_volatility_10
DataFieldDescription: Close-to-close Historical volatility over 10 days
DataField: implied_volatility_mean_skew_60
DataFieldDescription: At-the-money option-implied volatility mean skew for 60 days
DataField: implied_volatility_call_150
DataFieldDescription: At-the-money option-implied volatility for call Option for 150 days
DataField: implied_volatility_mean_skew_120
DataFieldDescription: At-the-money option-implied volatility mean skew for 120 days
DataField: parkinson_volatility_30
DataFieldDescription: Parkinson model's historical volatility over 30 days
DataField: nws12_prez_02l
DataFieldDescription: Number of minutes that elapsed before price went up 20 percentage points
DataField: news_mins_20_chg
DataFieldDescription: The minimum of L or S above for 20-minute bucket
DataField: nws12_mainz_mainvwap
DataFieldDescription: Main session volume weighted average price
DataField: nws12_prez_57s
DataFieldDescription: Number of minutes that elapsed before price went down 7.5 percentage points
DataField: nws12_prez_eodclose
DataFieldDescription: Close price of the session
DataField: nws12_afterhsz_1_minute
DataFieldDescription: The percent change in price in the first minute following the news release
DataField: news_ls
DataFieldDescription: Whether a long or short position would have been more advantageous: If (EODHigh - Last) > (Last - EODLow) Then LS = 1; If (EODHigh - Last) = (Last - EODLow) Then LS= 0; If (EODHigh - Last) < (Last - EODLow) Then LS = -1.
DataField: nws12_prez_prevwap
DataFieldDescription: Pre-session volume weighted average price
DataField: nws12_afterhsz_41rta
DataFieldDescription: 14-day Average True Range
DataField: nws12_allz_result1
DataFieldDescription: Percent change between the price at the time of the news release and the price at the close of the session
DataField: news_mins_3_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 3 percentage points
DataField: nws12_afterhsz_tonlast
DataFieldDescription: Price at the time of news
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_mainz_newrecord
DataFieldDescription: Tracks whether the news is first instance or a duplicate
DataField: news_indx_perf
DataFieldDescription: ((EODClose - TONLast) / TONLast) - ((SPYClose - SPYLast) / SPYLast)
DataField: nws12_prez_1s
DataFieldDescription: Number of minutes that elapsed before price went down 1 percentage point
DataField: nws12_prez_open_vol
DataFieldDescription: Main open volume
DataField: nws12_mainz_close_vol
DataFieldDescription: Main close volume
DataField: news_mins_7_5_pct_up
DataFieldDescription: Number of minutes that elapsed before price went up 7.5 percentage points
DataField: nws12_afterhsz_5_min
DataFieldDescription: The percent change in price in the first 5 minutes following the news release
DataField: nws12_afterhsz_4p
DataFieldDescription: The minimum of L or S above for 4-minute bucket
DataField: nws12_afterhsz_30_min
DataFieldDescription: The percent change in price in the first 30 minutes following the news release
DataField: news_pct_30min
DataFieldDescription: The percent change in price in the first 30 minutes following the news release
DataField: nws12_prez_5s
DataFieldDescription: Number of minutes that elapsed before price went down 5 percentage points
DataField: nws12_mainz_02l
DataFieldDescription: Number of minutes that elapsed before price went up 20 percentage points
DataField: nws12_afterhsz_02l
DataFieldDescription: Number of minutes that elapsed before price went up 20 percentage points
DataField: news_mins_3_pct_up
DataFieldDescription: Number of minutes that elapsed before price went up 3 percentage points
DataField: nws12_afterhsz_rangeamt
DataFieldDescription: Session High Price - Session Low Price
DataField: news_max_dn_ret
DataFieldDescription: Percent change from the price at the time of the news to the after the news low
DataField: nws12_afterhsz_eodclose
DataFieldDescription: Close price of the session
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: rp_css_price
DataFieldDescription: Composite sentiment score of stock price news
DataField: rp_css_partner
DataFieldDescription: Composite sentiment score of partnership news
DataField: rp_ess_technical
DataFieldDescription: Event sentiment score based on technical analysis
DataField: rp_css_ptg
DataFieldDescription: Composite sentiment score of price target news
DataField: rp_ess_earnings
DataFieldDescription: Event sentiment score of earnings news
DataField: rp_css_dividends
DataFieldDescription: Composite sentiment score of dividends news
DataField: rp_css_assets
DataFieldDescription: Composite sentiment score of assets news
DataField: nws18_qcm
DataFieldDescription: News sentiment of relevant news with high confidence
DataField: rp_ess_assets
DataFieldDescription: Event sentiment score of assets news
DataField: nws18_ghc_lna
DataFieldDescription: Change in analyst recommendation
DataField: rp_css_credit_ratings
DataFieldDescription: Composite sentiment score of credit ratings news
DataField: rp_nip_product
DataFieldDescription: News impact projection of product and service-related news
DataField: rp_css_credit
DataFieldDescription: Composite sentiment score of credit news
DataField: rp_ess_price
DataFieldDescription: Event sentiment score of stock price news
DataField: rp_nip_inverstor
DataFieldDescription: News impact projection of investor relations news
DataField: rp_nip_technical
DataFieldDescription: News impact projection based on technical analysis
DataField: rp_css_mna
DataFieldDescription: Composite sentiment score of mergers and acquisitions-related news
DataField: rp_nip_price
DataFieldDescription: News impact projection of stock price news
DataField: rp_ess_equity
DataFieldDescription: Event sentiment score of equity action news
DataField: rp_css_marketing
DataFieldDescription: Composite sentiment score of marketing news
DataField: rp_ess_insider
DataFieldDescription: Event sentiment score of insider trading news
DataField: rp_css_insider
DataFieldDescription: Composite sentiment score of insider trading news
DataField: rp_nip_marketing
DataFieldDescription: News impact projection of marketing news
DataField: nws18_sse
DataFieldDescription: Sentiment of phrases impacting the company
DataField: rp_css_technical
DataFieldDescription: Composite sentiment score based on technical analysis
DataField: rp_ess_mna
DataFieldDescription: Event sentiment score of mergers and acquisitions-related news
DataField: rp_ess_ratings
DataFieldDescription: Event sentiment score of analyst ratings-related news
DataField: rp_nip_credit
DataFieldDescription: News impact projection of credit news
DataField: rp_nip_dividends
DataFieldDescription: News impact projection of dividends news
DataField: rp_nip_business
DataFieldDescription: News impact projection of business-related news
DataField: fn_allocated_share_based_compensation_expense_q
DataFieldDescription: Represents the expense recognized during the period arising from equity-based compensation arrangements (for example, shares of stock, units, stock options, or other equity instruments) with employees, directors, and certain consultants qualifying for treatment as employees.
DataField: fn_income_from_equity_investments_q
DataFieldDescription: Income From Equity Method Investments
DataField: fn_assets_fair_val_l1_q
DataFieldDescription: Asset Fair Value, Recurring, Level 1
DataField: fnd2_a_flintasamt1expy5
DataFieldDescription: Amount of amortization expense for assets, excluding financial assets and goodwill, lacking physical substance with a finite life expected to be recognized during the 5th fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: fn_comp_non_opt_vested_q
DataFieldDescription: The number of equity-based payment instruments, excluding stock (or unit) options, that vested during the reporting period.
DataField: fn_finite_lived_intangible_assets_acq_q
DataFieldDescription: Amount of assets, excluding financial assets and goodwill, lacking physical substance with a finite life acquired.
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: fnd2_propplteqmuflmameqmt
DataFieldDescription: PPE, Equipment, Useful Life, Maximum
DataField: fnd2_eixrtreclstatelocalitxes
DataFieldDescription: Percentage of the difference between reported income tax expense (benefit) and expected income tax expense (benefit) computed by applying the domestic federal statutory income tax rates to pretax income (loss) from continuing operations applicable to state and local income tax expense (benefit), net of federal tax expense (benefit).
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: fn_def_income_tax_expense_q
DataFieldDescription: Income Tax Expense, Deferred
DataField: fnd2_dfdtxastxdfdexprssaccrs
DataFieldDescription: Amount before allocation of valuation allowances of deferred tax asset attributable to deductible temporary differences from reserves and accruals.
DataField: fn_comp_options_grants_fair_value_q
DataFieldDescription: Annual Share-Based Compensation Arrangement by Share-Based Payment Award Options Grants in Period Weighted Average Grant Date Fair Value
DataField: fn_repurchased_shares_a
DataFieldDescription: Number of shares that have been repurchased during the period.
DataField: fnd2_a_gsles1xtinguishmentofd
DataFieldDescription: Difference between the fair value of payments made and the carrying amount of debt which is extinguished prior to maturity.
DataField: fn_liab_fair_val_l2_q
DataFieldDescription: Liabilities Fair Value, Recurring, Level 2
DataField: fn_comp_options_exercisable_number_q
DataFieldDescription: The number of shares into which fully or partially vested stock options outstanding as of the balance sheet date can be currently converted under the option plan.
DataField: fn_proceeds_from_stock_options_exercised_q
DataFieldDescription: The cash inflow associated with the amount received from holders exercising their stock options. This item inherently excludes any excess tax benefit, which the entity may have realized and reported separately.
DataField: fn_op_lease_min_pay_due_in_2y_a
DataFieldDescription: Amount of required minimum rental payments for operating leases having an initial or remaining non-cancelable lease term in excess of 1 year due in the 2nd fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: fn_comp_options_out_weighted_avg_a
DataFieldDescription: Weighted average price at which grantees can acquire the shares reserved for issuance under the stock option plan.
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_sbcpnargmsptawervl
DataFieldDescription: Amount of accumulated difference between fair value of underlying shares on dates of exercise and exercise price on options exercised (or share units converted) into shares.
DataField: 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: fnd2_a_bnscbmacqrcsts
DataFieldDescription: This element represents acquisition-related costs incurred to effect a business combination which costs have been expensed during the period. Such costs include finder's fees; advisory, legal, accounting, valuation, and other professional or consulting fees; general administrative costs, including the costs of maintaining an internal acquisitions department; and may include costs of registering and issuing debt and equity securities.
DataField: fn_comp_options_grants_a
DataFieldDescription: Net number of share options (or share units) granted during the period.
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_accrued_liab_curr_q
DataFieldDescription: Carrying value as of the balance sheet date of obligations incurred and payable, pertaining to costs that are statutory in nature, are incurred on contractual obligations, or accumulate over time and for which invoices have not yet been received or will not be rendered.
DataField: fnd2_a_sbcpnargmpmwggil
DataFieldDescription: Amount by which the current fair value of the underlying stock exceeds the exercise price of fully vested and expected to vest options outstanding.
DataField: fn_proceeds_from_issuance_of_debt_a
DataFieldDescription: The cash inflow during the period from additional borrowings in aggregate debt. Includes proceeds from short-term and long-term debt.
DataField: fn_def_tax_assets_net_q
DataFieldDescription: Deferred Tax Assets Net Of Valuation Allowance
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 =======================================

