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: 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: pcr_vol_270
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 270 days in the future.
DataField: option_breakeven_120
DataFieldDescription: Price at which a stock's options with expiration 120 days in the future break even based on its recent bid/ask mean.
DataField: put_breakeven_1080
DataFieldDescription: Price at which a stock's put options with expiration 1080 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_270
DataFieldDescription: Forward price at 270 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: 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: 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: 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: 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: call_breakeven_360
DataFieldDescription: Price at which a stock's call options with expiration 360 days in the future break even based on its recent bid/ask mean.
DataField: option_breakeven_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: 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: 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_10
DataFieldDescription: Price at which a stock's put options with expiration 10 days in the future break even based on its recent bid/ask mean.
DataField: option_breakeven_150
DataFieldDescription: Price at which a stock's options with expiration 150 days in the future break even based on its recent bid/ask mean.
DataField: option_breakeven_90
DataFieldDescription: Price at which a stock's options with expiration 90 days in the future break even based on its recent bid/ask mean.
DataField: pcr_oi_120
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 120 days in the future.
DataField: pcr_vol_30
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 30 days in the future.
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: put_breakeven_270
DataFieldDescription: Price at which a stock's put options with expiration 270 days in the future break even based on its recent bid/ask mean.
DataField: call_breakeven_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: 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: forward_price_360
DataFieldDescription: Forward price at 360 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: pcr_vol_150
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 150 days in the future.
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: put_breakeven_20
DataFieldDescription: Price at which a stock's put options with expiration 20 days in the future break even based on its recent bid/ask mean.
DataField: pcr_vol_20
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 20 days in the future.
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: 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: 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: fnd6_aodo
DataFieldDescription: Other Assets excluding Discontinued Operations
DataField: fnd6_aldo
DataFieldDescription: Long-term Assets of Discontinued Operations
DataField: fnd6_newqv1300_ciderglq
DataFieldDescription: Comp Inc - Derivative Gains/Losses
DataField: fnd6_txfed
DataFieldDescription: Income Taxes - Federal
DataField: fnd6_mibn
DataFieldDescription: Noncontrolling Interests - Nonredeemable - Balance Sheet
DataField: fnd6_cptmfmq_opepsq
DataFieldDescription: Earnings Per Share from Operations
DataField: fnd6_eventv110_txdbclq
DataFieldDescription: Current Deferred Tax Liability
DataField: fnd6_newqeventv110_aoq
DataFieldDescription: Assets - Other - Total
DataField: fnd6_newqeventv110_seteps12
DataFieldDescription: Settlement (Litigation/Insurance) Basic EPS Effect 12MM
DataField: fnd6_newqv1300_wcapq
DataFieldDescription: Working Capital (Balance Sheet)
DataField: fnd6_itcb
DataFieldDescription: Investment Tax Credit (Balance Sheet)
DataField: fnd6_intan
DataFieldDescription: Intangible Assets - Total
DataField: fnd6_lno
DataFieldDescription: Liabilities Netting & Other Adjustments
DataField: fnd6_cptnewqv1300_oeps12
DataFieldDescription: Earnings Per Share from Operations - 12 Months Moving
DataField: fnd6_eventv110_gdwlieps12
DataFieldDescription: Impairment of Goodwill Basic EPS Effect 12MM
DataField: fnd6_newqeventv110_xoptdqp
DataFieldDescription: Implied Option EPS Diluted Preliminary
DataField: fnd6_xacc
DataFieldDescription: Accrued Expenses
DataField: fnd6_newa1v1300_che
DataFieldDescription: Cash and Short-Term Investments
DataField: fnd6_cibegni
DataFieldDescription: Comp Inc - Beginning Net Income
DataField: fnd6_newqeventv110_glced12
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) Diluted EPS Effect 12MM
DataField: fnd6_newqv1300_lqpl1q
DataFieldDescription: Liabilities Level 1 (Quoted Prices)
DataField: fnd6_xints
DataFieldDescription: Interest Expense
DataField: bookvalue_ps
DataFieldDescription: Book Value Per Share
DataField: fnd6_newqeventv110_lol2q
DataFieldDescription: Liabilities Level 2 (Observable)
DataField: fnd6_newa1v1300_fincf
DataFieldDescription: Financing Activities - Net Cash Flow
DataField: fnd6_newqeventv110_optrfrq
DataFieldDescription: Risk Free Rate - Assumption (%)
DataField: fnd6_txdfo
DataFieldDescription: Deferred Taxes - Foreign
DataField: fnd6_newqv1300_chq
DataFieldDescription: Cash
DataField: fnd6_newqeventv110_txdiq
DataFieldDescription: Income Taxes - Deferred
DataField: fnd6_newqv1300_tfvlq
DataFieldDescription: Total Fair Value Liabilities
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: sales_guidance_value
DataFieldDescription: Sales - Guidance value for the annual period
DataField: anl4_fcf_number
DataFieldDescription: Free Cash Flow - number of estimations
DataField: anl4_ebitda_number
DataFieldDescription: Earnings before interest, taxes, depreciation and amortization - number of estimations
DataField: anl4_eaz2lrec_person
DataFieldDescription: Broker Id
DataField: anl4_basicconqfv110_low
DataFieldDescription: The lowest estimation
DataField: anl4_qf_az_eps_number
DataFieldDescription: Earnings per share - number of estimations
DataField: anl4_capex_value
DataFieldDescription: Capital Expenditures - announced financial value
DataField: sales_estimate_count_quarterly
DataFieldDescription: Sales - number of estimations
DataField: anl4_fsguidanceafv4_minguidance
DataFieldDescription: Min guidance value
DataField: max_reported_pretax_income_guidance
DataFieldDescription: Reported Pretax income- maximum guidance value
DataField: anl4_epsa_flag
DataFieldDescription: Earnings per share adjusted by excluding extraordinary items and stock option expenses - forecast type (revision/new/...)
DataField: max_investing_cashflow_guidance
DataFieldDescription: The maximum guidance value for Cash Flow from Investing.
DataField: anl4_cuo1conqfv110_item
DataFieldDescription: Financial item
DataField: anl4_basicafv4_actual
DataFieldDescription: Announced financial data for the annual period.
DataField: cash_flow_operations_min_guidance
DataFieldDescription: Minimum guidance value for Cash Flow from Operations on an annual basis.
DataField: anl4_buy
DataFieldDescription: The number of recommendations to long the instrument
DataField: anl4_dei2laf_item
DataFieldDescription: Financial item
DataField: anl4_eaz2lltv110_person
DataFieldDescription: Broker Id
DataField: anl4_epsr_mean
DataFieldDescription: GAAP Earnings per share - mean of estimations
DataField: anl4_rd_exp_high
DataFieldDescription: Research and Development Expense - the highest estimation
DataField: max_adjusted_net_profit_guidance
DataFieldDescription: The maximum guidance value for adjusted net profit on an annual basis.
DataField: max_adjusted_eps_guidance
DataFieldDescription: The maximum guidance value for adjusted earnings per share.
DataField: min_adjusted_funds_from_operations_adj_guidance
DataFieldDescription: Minimum guidance value for Adjusted funds from operation
DataField: sales_min_guidance_quarterly
DataFieldDescription: Minimum guidance value for Sales
DataField: anl4_cfi_low
DataFieldDescription: Cash Flow From Investing - The lowest estimation
DataField: est_ffo
DataFieldDescription: Funds From Operation - Summary on Estimations, Mean
DataField: max_shareholders_equity_guidance
DataFieldDescription: The maximum guidance value for Total Shareholders' Equity.
DataField: lowest_sales_estimate
DataFieldDescription: Sales - The lowest estimation for the annual period
DataField: min_share_buyback_guidance
DataFieldDescription: Shares Basic - Minimum guidance value for the annual period
DataField: eps_min_guidance_quarterly
DataFieldDescription: Minimum guidance value for Earnings per Share
DataField: single_sector_pureplay_company_count
DataFieldDescription: Number of companies exclusively operating in a single sector.
DataField: pv13_hierarchy_min20_513_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_liquid_min2_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_sector_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_di_6l
DataFieldDescription: grouping fields
DataField: pv13_4l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min52_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_top3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f2_sector
DataFieldDescription: grouping fields
DataField: rel_ret_part
DataFieldDescription: Averaged one-day return of the instrument's partners
DataField: pv13_5l_scibr
DataFieldDescription: grouping fields
DataField: pv13_ustomergraphrank_page_rank
DataFieldDescription: the PageRank of customers
DataField: pv13_hierarchy_min40_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_h2_sector
DataFieldDescription: grouping fields
DataField: pv13_percentregion
DataFieldDescription: Exposure percentage
DataField: pv13_r2_min2_1000_sector
DataFieldDescription: grouping fields
DataField: rel_num_all
DataFieldDescription: number of the companies whose product overlapped with the instrument
DataField: pv13_hierarchy_min2_focused_pureplay_sector
DataFieldDescription: grouping fields
DataField: pv13_reporttype
DataFieldDescription: Type of report
DataField: pv13_hierarchy_min22_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min52_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min5_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min5_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy23_sector
DataFieldDescription: grouping fields
DataField: pv13_region
DataFieldDescription: Unique code of the region
DataField: pv13_h_min2_focused_sector
DataFieldDescription: Grouping fields for top 200
DataField: pv13_hierarchy_min20_top3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_ompetitorgraphrank_hub_rank
DataFieldDescription: the HITS hub score of competitors
DataField: pv13_rha2_min30_3000_513_sector
DataFieldDescription: grouping fields
DataField: implied_volatility_mean_skew_120
DataFieldDescription: At-the-money option-implied volatility mean skew for 120 days
DataField: implied_volatility_call_180
DataFieldDescription: At-the-money option-implied volatility for call Option for 180 days
DataField: implied_volatility_call_10
DataFieldDescription: At-the-money option-implied volatility for call Option for 10 days
DataField: parkinson_volatility_30
DataFieldDescription: Parkinson model's historical volatility over 30 days
DataField: implied_volatility_mean_720
DataFieldDescription: At-the-money option-implied volatility mean for 720 days
DataField: implied_volatility_mean_90
DataFieldDescription: At-the-money option-implied volatility mean for 90 days
DataField: historical_volatility_180
DataFieldDescription: Close-to-close Historical volatility over 180 days
DataField: parkinson_volatility_180
DataFieldDescription: Parkinson model's historical volatility over 180 days
DataField: parkinson_volatility_10
DataFieldDescription: Parkinson model's historical volatility over 2 weeks
DataField: implied_volatility_mean_skew_270
DataFieldDescription: At-the-money option-implied volatility mean skew for 270 days
DataField: implied_volatility_mean_180
DataFieldDescription: At-the-money option-implied volatility mean for 180 days
DataField: implied_volatility_mean_10
DataFieldDescription: At-the-money option-implied volatility mean for 10 days
DataField: implied_volatility_mean_skew_20
DataFieldDescription: At-the-money option-implied volatility mean skew for 20 days
DataField: implied_volatility_mean_20
DataFieldDescription: At-the-money option-implied volatility mean for 20 days
DataField: implied_volatility_call_30
DataFieldDescription: At-the-money option-implied volatility for call Option for 30 days
DataField: implied_volatility_mean_skew_720
DataFieldDescription: At-the-money option-implied volatility mean skew for 720 days
DataField: implied_volatility_mean_skew_10
DataFieldDescription: At-the-money option-implied volatility mean skew for 10 days
DataField: implied_volatility_mean_skew_30
DataFieldDescription: At-the-money option-implied volatility mean skew for 30 days
DataField: implied_volatility_call_150
DataFieldDescription: At-the-money option-implied volatility for call Option for 150 days
DataField: implied_volatility_put_90
DataFieldDescription: At-the-money option-implied volatility for Put Option for 90 days
DataField: implied_volatility_mean_skew_1080
DataFieldDescription: At-the-money option-implied volatility mean skew for 3 years
DataField: implied_volatility_put_60
DataFieldDescription: At-the-money option-implied volatility for Put Option for 60 days
DataField: implied_volatility_put_30
DataFieldDescription: At-the-money option-implied volatility for Put Option for 30 days
DataField: implied_volatility_put_10
DataFieldDescription: At-the-money option-implied volatility for Put Option for 10 days
DataField: implied_volatility_mean_60
DataFieldDescription: At-the-money option-implied volatility mean for 60 days
DataField: implied_volatility_put_360
DataFieldDescription: At-the-money option-implied volatility for Put Option for 360 days
DataField: implied_volatility_call_1080
DataFieldDescription: At-the-money option-implied volatility for call option for 1080 days
DataField: implied_volatility_call_60
DataFieldDescription: At-the-money option-implied volatility for call Option for 60 days
DataField: implied_volatility_put_150
DataFieldDescription: At-the-money option-implied volatility for Put Option for 150 days
DataField: implied_volatility_put_120
DataFieldDescription: At-the-money option-implied volatility for Put Option for 120 days
DataField: nws12_allz_newssess
DataFieldDescription: Index of session in which the news was reported
DataField: nws12_mainz_1p
DataFieldDescription: The minimum of L or S above for 1-minute bucket
DataField: nws12_prez_spylast
DataFieldDescription: Last Price of the SPY at the time of the news
DataField: nws12_afterhsz_eodclose
DataFieldDescription: Close price of the session
DataField: nws12_prez_maxdnamt
DataFieldDescription: The price at the time of the news minus the after the news low
DataField: nws12_prez_90_min
DataFieldDescription: The percent change in price in the first 90 minutes following the news release
DataField: nws12_prez_peratio
DataFieldDescription: Reported price to earnings ratio for the calendar day of the session
DataField: nws12_afterhsz_newrecord
DataFieldDescription: Tracks whether the news is first instance or a duplicate
DataField: news_mins_10_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: nws12_prez_maxupamt
DataFieldDescription: The after-the-news high minus the price at the time of the news
DataField: nws12_afterhsz_postvwap
DataFieldDescription: Post-session volume weighted average price
DataField: news_mins_4_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 4 percentage points
DataField: nws12_afterhsz_reportsess
DataFieldDescription: Index of Session on which the spreadsheet is reporting
DataField: nws12_mainz_provider
DataFieldDescription: index of name of the news provider
DataField: news_spy_last
DataFieldDescription: Last Price of the SPY at the time of the news
DataField: nws12_afterhsz_newssess
DataFieldDescription: Index of the session in which the news was reported
DataField: nws12_prez_10_min
DataFieldDescription: The percent change in price in the first 10 minutes following the news release
DataField: nws12_afterhsz_spyclose
DataFieldDescription: Price of SPY at close of session
DataField: nws12_mainz_02p
DataFieldDescription: The minimum of L or S above for 20-minute bucket
DataField: news_ton_high
DataFieldDescription: Highest price reached during the session before the time of news
DataField: news_pct_30min
DataFieldDescription: The percent change in price in the first 30 minutes following the news release
DataField: nws12_mainz_1l
DataFieldDescription: Number of minutes that elapsed before price went up 1 percentage point
DataField: nws12_prez_mktcap
DataFieldDescription: Reported market capitalization for the calendar day of the session
DataField: nws12_mainz_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_prez_curr_vol
DataFieldDescription: Current day's session volume
DataField: nws12_prez_1p
DataFieldDescription: The minimum of L or S above for 1-minute bucket
DataField: nws12_mainz_5l
DataFieldDescription: Number of minutes that elapsed before price went up 5 percentage points
DataField: news_mins_20_chg
DataFieldDescription: The minimum of L or S above for 20-minute bucket
DataField: nws12_mainz_newssess
DataFieldDescription: Index of session in which the news was reported
DataField: nws12_prez_2p
DataFieldDescription: The minimum of L or S above for 2-minute bucket
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: rp_ess_dividends
DataFieldDescription: Event sentiment score of dividends news
DataField: rp_nip_price
DataFieldDescription: News impact projection of stock price news
DataField: rp_nip_ratings
DataFieldDescription: News impact projection of analyst ratings-related news
DataField: rp_css_assets
DataFieldDescription: Composite sentiment score of assets news
DataField: rp_css_inverstor
DataFieldDescription: Composite sentiment score of investor relations news
DataField: rp_css_insider
DataFieldDescription: Composite sentiment score of insider trading news
DataField: rp_nip_technical
DataFieldDescription: News impact projection based on technical analysis
DataField: rp_ess_price
DataFieldDescription: Event sentiment score of stock price news
DataField: rp_nip_credit
DataFieldDescription: News impact projection of credit news
DataField: nws18_qmb
DataFieldDescription: News sentiment specializing in editorials on global markets
DataField: rp_css_ptg
DataFieldDescription: Composite sentiment score of price target news
DataField: rp_css_society
DataFieldDescription: Composite sentiment score of society-related news
DataField: rp_nip_business
DataFieldDescription: News impact projection of business-related news
DataField: rp_nip_revenue
DataFieldDescription: News impact projection of revenue news
DataField: rp_nip_dividends
DataFieldDescription: News impact projection of dividends news
DataField: rp_css_equity
DataFieldDescription: Composite sentiment score of equity action news
DataField: rp_ess_revenue
DataFieldDescription: Event sentiment score of revenue news
DataField: rp_css_dividends
DataFieldDescription: Composite sentiment score of dividends news
DataField: nws18_event_relevance
DataFieldDescription: Relevance of the event to the story
DataField: rp_ess_labor
DataFieldDescription: Event sentiment score of labor issues news
DataField: rp_ess_credit_ratings
DataFieldDescription: Event sentiment score of credit ratings news
DataField: rp_ess_ratings
DataFieldDescription: Event sentiment score of analyst ratings-related news
DataField: rp_nip_equity
DataFieldDescription: News impact projection of equity action news
DataField: nws18_relevance
DataFieldDescription: Relevance of news to the company
DataField: rp_nip_ptg
DataFieldDescription: News impact projection of price target news
DataField: rp_ess_assets
DataFieldDescription: Event sentiment score of assets news
DataField: rp_ess_society
DataFieldDescription: Event sentiment score of society-related news
DataField: rp_ess_partner
DataFieldDescription: Event sentiment score of partnership news
DataField: rp_css_ratings
DataFieldDescription: Composite sentiment score of analyst ratings-related news
DataField: rp_nip_mna
DataFieldDescription: News impact projection of mergers and acquisitions-related news
DataField: fn_oth_comp_fair_value_a
DataFieldDescription: Annual share-based compensation equity instruments other than options grants in period weighted average grant date fair value
DataField: fn_finite_lived_intangible_assets_net_a
DataFieldDescription: Finite Lived Intangible Assets, Net
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_accrued_liab_a
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_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: 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_propplteqmuflmamfrt
DataFieldDescription: PPE, Furniture, Useful Life, Maximum
DataField: fnd2_a_stkdrgprdvalnewissues
DataFieldDescription: Equity impact of the value of new stock issued during the period. Includes shares issued in an initial public offering or a secondary public offering.
DataField: fn_comp_number_of_shares_authorized_a
DataFieldDescription: Count of unique IDs of industry participants. Industry stands for an aggregate view of all  equity clearance activity for the date, symbol, and transaction type in question.
DataField: fn_income_from_equity_investments_q
DataFieldDescription: Income From Equity Method Investments
DataField: fnd2_a_unrgtxbnfitxpenlintacd
DataFieldDescription: Amount accrued for interest on an underpayment of income taxes and penalties related to a tax position claimed or expected to be claimed in the tax return.
DataField: fnd2_q_flintasamt1expy5
DataFieldDescription: Amount of amortization expense for assets, excluding financial assets and goodwill, lacking physical substance with a finite life expected to be recognized during the 5th fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: fnd2_a_lhdiprtsg
DataFieldDescription: Amount before accumulated depreciation of additions or improvements to assets held under a lease arrangement.
DataField: fn_new_shares_options_q
DataFieldDescription: Number of share options (or share units) exercised during the current period.
DataField: fn_assets_fair_val_l3_q
DataFieldDescription: Asset Fair Value, Recurring, Level 3
DataField: fn_op_lease_min_pay_due_in_3y_a
DataFieldDescription: Amount of required minimum rental payments for operating leases having an initial or remaining non-cancelable lease term in excess of one year due in the 3rd 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_q_seniornotes
DataFieldDescription: Including the current and noncurrent portions, carrying value as of the balance sheet date of Notes with the highest claim on the assets of the issuer in case of bankruptcy or liquidation (with maturities initially due after 1 year or beyond the operating cycle if longer). Senior note holders are paid off in full before any payments are made to junior note holders.
DataField: fn_comp_options_exercises_weighted_avg_a
DataFieldDescription: Share-Based Compensation, Options Assumed, Weighted Average Exercise Price
DataField: fn_finite_lived_intangible_assets_net_q
DataFieldDescription: Finite Lived Intangible Assets, Net
DataField: fnd2_a_blgandiprtsg
DataFieldDescription: Amount before accumulated depreciation of building structures held for productive use including addition, improvement, or renovation to the structure, including, but not limited to, interior masonry, interior flooring, electrical, and plumbing.
DataField: 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_debt_issuance_costs_q
DataFieldDescription: Amount of debt issuance costs (for example, but not limited to, legal, accounting, broker, and regulatory fees).
DataField: fn_taxes_payable_q
DataFieldDescription: Carrying value as of the balance sheet date of obligations incurred and payable for statutory income, sales, use, payroll, excise, real, property and other taxes. 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_sbcpnargtbysbpmtwpwrr
DataFieldDescription: Weighted average price at which grantees could have acquired the underlying shares with respect to stock options of the plan that expired.
DataField: fnd2_a_eplsrbcpntxbnffcmpex
DataFieldDescription: The total recognized tax benefit related to compensation cost for equity-based payment arrangements recognized in income during the period.
DataField: fn_def_tax_liab_a
DataFieldDescription: Amount, after deferred tax asset, of deferred tax liability attributable to taxable differences without jurisdictional netting.
DataField: fn_proceeds_from_issuance_of_common_stock_q
DataFieldDescription: The cash inflow from the additional capital contribution to the entity.
DataField: fn_derivative_notional_amount_q
DataFieldDescription: Nominal or face amount used to calculate payments on the derivative liability.
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: fnd2_a_flintasamt1expytwo
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 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: 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 =======================================