任务指令
你是一个WorldQuant WebSim因子工程师。你的任务是生成 10 个用于行业轮动策略的复合型Alpha因子表达式。
核心规则
设计维度框架
维度1：时间序列动量（TM）
核心概念：捕捉行业价格的趋势、动量和形态变化
设计思路：
动量的变化率、加速度或平滑度构建
动量衰减或增强模式识别
价格与成交量关系的时序分析
维度2：横截面领导力（CL）
核心概念：识别行业内部的分化、龙头效应和相对强度
bucket（用于龙头股筛选）
设计思路：
行业内部龙头股与平均表现的差异
行业成分股的离散度分析
相对排名的变化和稳定性
维度3：市场状态适应性（MS）
核心概念：根据市场环境动态调整因子逻辑
设计思路：
波动率调整的动量指标
不同市场状态（高/低波动）使用不同的回顾期
条件逻辑下的参数动态调整
维度4：行业间联动（IS）
多序列相关性分析
设计思路：
领先-滞后行业的相关性分析
行业间动量传导效应
板块轮动的早期信号识别
维度5：交易行为情绪（TS）
核心概念：基于交易行为和情绪指标的反转信号
设计思路：
超买超卖状态识别
交易拥挤度指标
情绪极端值后的均值回归
复合因子设计原则
强制要求：
每个表达式必须融合至少两个设计维度
必须使用提供的操作符列表中的函数
因子应具有经济逻辑解释性
推荐组合模式：
TM + CL：时序动量 + 横截面领导力
示例：行业动量加速度 × 龙头股相对强度
TM + MS：时序动量 + 状态适应性
示例：波动率调整后的动量指标
CL + IS：横截面 + 行业间联动
示例：龙头股表现与相关行业的领先滞后关系
MS + TS：状态适应 + 交易情绪
示例：不同市场状态下的反转信号
IS + TS：行业联动 + 交易情绪
示例：行业间相关性变化与交易拥挤度
参数化建议：
使用不同的时间窗口组合（短/中/长周期）
尝试不同的权重分配方式
考虑非线性变换（log, power, sqrt）
使用条件逻辑增强鲁棒性
表达式构建指南
基本结构：
text
复合因子 = 维度A组件 [运算符] 维度B组件 [条件调整]
操作符限制：只能且必须使用以下列表中提供的操作符。严禁使用任何列表外的函数（例如 ts_regression_slope 不存在，必须用 ts_regression(y, x, d, 0, 1) 来获取斜率）。
操作符使用策略：
算术运算：abs(x), add(x, y, filter = false), densify(x), divide(x, y), inverse(x), max(x, y, ..), min(x, y ..), multiply(x ,y, ... , filter=false), power(x, y), reverse(x), sign(x), signed_power(x, y), sqrt(x), subtract(x, y, filter=false)
条件逻辑：and(input1, input2), if_else(input1, input2, input 3), input1 < input2, input1 <= input2, input1 == input2, input1 > input2, input1 >= input2, input1!= input2, is_nan(input), not(x), or(input1, input2)
时间序列操作：days_from_last_change(x), hump(x, hump = 0.01), kth_element(x, d, k), last_diff_value(x, d), ts_arg_max(x, d), ts_arg_min(x, d), ts_av_diff(x, d), ts_backfill(x,lookback = d, k=1, ignore="NAN"), ts_corr(x, y, d), ts_count_nans(x ,d), ts_covariance(y, x, d), ts_decay_linear(x, d, dense = false), ts_delay(x, d), ts_delta(x, d), ts_mean(x, d), ts_product(x, d), "ts_quantile(x,d, driver=""gaussian"" )", ts_rank(x, d, constant = 0), ts_regression(y, x, d, lag = 0, rettype = 0), ts_scale(x, d, constant = 0), ts_std_dev(x, d), ts_step(1), ts_sum(x, d), ts_zscore(x, d)
横截面操作: normalize(x, useStd = false, limit = 0.0), quantile(x, driver = gaussian, sigma = 1.0), rank(x, rate=2), scale(x, scale=1, longscale=1, shortscale=1), winsorize(x, std=4), zscore(x)
向量操作符：vec_avg(x), vec_sum(x)
转换操作符: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10"), trade_when(x, y, z)
聚合操作符: group_backfill(x, group, d, std = 4.0), group_mean(x, weight, group), group_neutralize(x, group), group_rank(x, group), group_scale(x, group), group_zscore(x, group), subtract(x, y, filter=false), multiply(x ,y, ... , filter=false), divide(x, y), add(x, y, filter = false)
*=====*
注意事项:
避免过度复杂的嵌套
使用经济直觉验证逻辑合理性
考虑实际交易可行性
包含风险控制元素（如波动率调整）
*=====*
参数逻辑：参数d（回顾期）应在[5, 10, 20, 30, 60, 120]等具有市场意义（周、月、季度、半年）的数值中合理选择并差异化。
行业隐含：通过group_mean、group_rank等函数或假设表达式在行业指数上运行来体现“行业”逻辑。
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。

示例思维（仅供理解，不输出）
一个融合“龙头股趋势加速度(M)”与“行业整体情绪背离(R)”的因子思路，可用你的操作符实现为(此为示例, 读取操作符的使用说明, 并结合上述的维度方案, 组合并创新因子)：
multiply( ts_delta(group_mean(ts_regression(close, ts_step(1), 20, 0, 1), bucket(rank(close), "0.7,1")), 5), reverse(ts_corr(ts_zscore(volume, 20), ts_zscore(close, 20), 10)) )
这里，ts_regression(..., rettype=1)获取斜率代替动量，bucket(rank(close), "0.7,1")近似选取市值前30%的龙头股，ts_corr(...)衡量价量情绪，reverse将其转化为背离信号。
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, 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
请提供具体的WQ表达式。
重申：请确保所有表达式都使用WorldQuant WebSim平台函数，不要使用pandas、numpy或其他Python库函数。输出必须是一行有效的WQ表达式。
以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子

以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子

========================= 操作符开始 =======================================注意: Operator: 后面的是操作符,
Description: 此字段后面的是操作符对应的描述或使用说明, Description字段后面的内容是使用说明, 不是操作符
特别注意!!!! 必须按照操作符字段Operator的使用说明生成 alphaOperator: abs(x)
Description: Absolute value of x
Operator: add(x, y, filter = false)
Description: Add all inputs (at least 2 inputs required). If filter = true, filter all input NaN to 0 before adding
Operator: densify(x)
Description: Converts a grouping field of many buckets into lesser number of only available buckets so as to make working with grouping fields computationally efficient
Operator: divide(x, y)
Description: x / y
Operator: inverse(x)
Description: 1 / x
Operator: log(x)
Description: Natural logarithm. For example: Log(high/low) uses natural logarithm of high/low ratio as stock weights.
Operator: max(x, y, ..)
Description: Maximum value of all inputs. At least 2 inputs are required
Operator: min(x, y ..)
Description: Minimum value of all inputs. At least 2 inputs are required
Operator: multiply(x ,y, ... , filter=false)
Description: Multiply all inputs. At least 2 inputs are required. Filter sets the NaN values to 1
Operator: power(x, y)
Description: x ^ y
Operator: reverse(x)
Description: - x
Operator: sign(x)
Description: if input > 0, return 1; if input < 0, return -1; if input = 0, return 0; if input = NaN, return NaN;
Operator: signed_power(x, y)
Description: x raised to the power of y such that final result preserves sign of x
Operator: sqrt(x)
Description: Square root of x
Operator: subtract(x, y, filter=false)
Description: x-y. If filter = true, filter all input NaN to 0 before subtracting
Operator: and(input1, input2)
Description: Logical AND operator, returns true if both operands are true and returns false otherwise
Operator: if_else(input1, input2, input 3)
Description: If input1 is true then return input2 else return input3.
Operator: input1 < input2
Description: If input1 < input2 return true, else return false
Operator: input1 <= input2
Description: Returns true if input1 <= input2, return false otherwise
Operator: input1 == input2
Description: Returns true if both inputs are same and returns false otherwise
Operator: input1 > input2
Description: Logic comparison operators to compares two inputs
Operator: input1 >= input2
Description: Returns true if input1 >= input2, return false otherwise
Operator: input1!= input2
Description: Returns true if both inputs are NOT the same and returns false otherwise
Operator: is_nan(input)
Description: If (input == NaN) return 1 else return 0
Operator: not(x)
Description: Returns the logical negation of x. If x is true (1), it returns false (0), and if input is false (0), it returns true (1).
Operator: or(input1, input2)
Description: Logical OR operator returns true if either or both inputs are true and returns false otherwise
Operator: days_from_last_change(x)
Description: Amount of days since last change of x
Operator: hump(x, hump = 0.01)
Description: Limits amount and magnitude of changes in input (thus reducing turnover)
Operator: kth_element(x, d, k)
Description: Returns K-th value of input by looking through lookback days. This operator can be used to backfill missing data if k=1
Operator: last_diff_value(x, d)
Description: Returns last x value not equal to current x value from last d days
Operator: ts_arg_max(x, d)
Description: Returns the relative index of the max value in the time series for the past d days. If the current day has the max value for the past d days, it returns 0. If previous day has the max value for the past d days, it returns 1
Operator: ts_arg_min(x, d)
Description: Returns the relative index of the min value in the time series for the past d days; If the current day has the min value for the past d days, it returns 0; If previous day has the min value for the past d days, it returns 1.
Operator: ts_av_diff(x, d)
Description: Returns x - tsmean(x, d), but deals with NaNs carefully. That is NaNs are ignored during mean computation
Operator: ts_backfill(x,lookback = d, k=1, ignore="NAN")
Description: Backfill is the process of replacing the NAN or 0 values by a meaningful value (i.e., a first non-NaN value)
Operator: ts_corr(x, y, d)
Description: Returns correlation of x and y for the past d days
Operator: ts_count_nans(x ,d)
Description: Returns the number of NaN values in x for the past d days
Operator: ts_covariance(y, x, d)
Description: Returns covariance of y and x for the past d days
Operator: ts_decay_linear(x, d, dense = false)
Description: Returns the linear decay on x for the past d days. Dense parameter=false means operator works in sparse mode and we treat NaN as 0. In dense mode we do not.
Operator: ts_delay(x, d)
Description: Returns x value d days ago
Operator: ts_delta(x, d)
Description: Returns x - ts_delay(x, d)
Operator: ts_mean(x, d)
Description: Returns average value of x for the past d days.
Operator: ts_product(x, d)
Description: Returns product of x for the past d days
Operator: ts_quantile(x,d, driver="gaussian" )
Description: It calculates ts_rank and apply to its value an inverse cumulative density function from driver distribution. Possible values of driver (optional ) are "gaussian", "uniform", "cauchy" distribution where "gaussian" is the default.
Operator: ts_rank(x, d, constant = 0)
Description: Rank the values of x for each instrument over the past d days, then return the rank of the current value + constant. If not specified, by default, constant = 0.
Operator: ts_regression(y, x, d, lag = 0, rettype = 0)
Description: Returns various parameters related to regression function
Operator: ts_scale(x, d, constant = 0)
Description: Returns (x - ts_min(x, d)) / (ts_max(x, d) - ts_min(x, d)) + constant. This operator is similar to scale down operator but acts in time series space
Operator: ts_std_dev(x, d)
Description: Returns standard deviation of x for the past d days
Operator: ts_step(1)
Description: Returns days' counter
Operator: ts_sum(x, d)
Description: Sum values of x for the past d days.
Operator: ts_zscore(x, d)
Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean: (x - tsmean(x,d)) / tsstddev(x,d). This operator may help reduce outliers and drawdown.
Operator: normalize(x, useStd = false, limit = 0.0)
Description: Calculates the mean value of all valid alpha values for a certain date, then subtracts that mean from each element
Operator: quantile(x, driver = gaussian, sigma = 1.0)
Description: Rank the raw vector, shift the ranked Alpha vector, apply distribution (gaussian, cauchy, uniform). If driver is uniform, it simply subtract each Alpha value with the mean of all Alpha values in the Alpha vector
Operator: rank(x, rate=2)
Description: Ranks the input among all the instruments and returns an equally distributed number between 0.0 and 1.0. For precise sort, use the rate as 0
Operator: scale(x, scale=1, longscale=1, shortscale=1)
Description: Scales input to booksize. We can also scale the long positions and short positions to separate scales by mentioning additional parameters to the operator
Operator: winsorize(x, std=4)
Description: Winsorizes x to make sure that all values in x are between the lower and upper limits, which are specified as multiple of std.
Operator: zscore(x)
Description: Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean
Operator: vec_avg(x)
Description: Taking mean of the vector field x
Operator: vec_sum(x)
Description: Sum of vector field x
Operator: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10")
Description: Convert float values into indexes for user-specified buckets. Bucket is useful for creating group values, which can be passed to GROUP as input
Operator: trade_when(x, y, z)
Description: Used in order to change Alpha values only under a specified condition and to hold Alpha values in other cases. It also allows to close Alpha positions (assign NaN values) under a specified condition
Operator: group_backfill(x, group, d, std = 4.0)
Description: If a certain value for a certain date and instrument is NaN, from the set of same group instruments, calculate winsorized mean of all non-NaN values over last d days
Operator: group_mean(x, weight, group)
Description: All elements in group equals to the mean
Operator: group_neutralize(x, group)
Description: Neutralizes Alpha against groups. These groups can be subindustry, industry, sector, country or a constant
Operator: group_rank(x, group)
Description: Each elements in a group is assigned the corresponding rank in this group
Operator: group_scale(x, group)
Description: Normalizes the values in a group to be between 0 and 1. (x - groupmin) / (groupmax - groupmin)
Operator: group_zscore(x, group)
Description: Calculates group Z-score - numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. zscore = (data - mean) / stddev of x for each instrument within its group.========================= 操作符结束 =======================================

========================= 数据字段开始 =======================================注意: DataField: 后面的是数据字段, DataFieldDescription: 此字段后面的是数据字段对应的描述或使用说明, DataFieldDescription字段后面的内容是使用说明, 不是数据字段

DataField: pcr_oi_90
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 90 days in the future.
DataField: option_breakeven_720
DataFieldDescription: Price at which a stock's options with expiration 720 days in the future break even based on its recent bid/ask mean.
DataField: 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_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: pcr_vol_all
DataFieldDescription: Ratio of put volume to call volume for all maturities on stock's options.
DataField: pcr_oi_270
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 270 days in the future.
DataField: put_breakeven_150
DataFieldDescription: Price at which a stock's put options with expiration 150 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_60
DataFieldDescription: Forward price at 60 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: pcr_vol_270
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 270 days in the future.
DataField: pcr_vol_10
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 10 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: 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: call_breakeven_30
DataFieldDescription: Price at which a stock's call options with expiration 30 days in the future break even based on its recent bid/ask mean.
DataField: 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_360
DataFieldDescription: Price at which a stock's options with expiration 360 days in the future break even based on its recent bid/ask mean.
DataField: pcr_vol_30
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 30 days in the future.
DataField: option_breakeven_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_1080
DataFieldDescription: Forward price at 1080 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: pcr_oi_10
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 10 days in the future.
DataField: pcr_oi_all
DataFieldDescription: Ratio of put open interest to call open interest for all maturities on stock's options.
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: 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: pcr_oi_30
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 30 days in the future.
DataField: pcr_oi_720
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 720 days in the future.
DataField: pcr_vol_1080
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 1080 days in the future.
DataField: 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: 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: 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: 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: pcr_oi_150
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 150 days in the future.
DataField: fnd6_newqeventv110_invrmq
DataFieldDescription: Inventory - Raw Materials
DataField: fnd6_tfvl
DataFieldDescription: Total Fair Value Liabilities
DataField: fnd6_xpp
DataFieldDescription: Prepaid Expenses
DataField: fnd6_newqv1300_txpq
DataFieldDescription: Income Taxes Payable
DataField: fnd6_newqeventv110_chq
DataFieldDescription: Cash
DataField: fnd6_newa2v1300_txp
DataFieldDescription: Income Taxes Payable
DataField: fnd6_newa1v1300_aol2
DataFieldDescription: Assets Level 2 (Observable)
DataField: fnd6_cptnewqv1300_lctq
DataFieldDescription: Current Liabilities - Total
DataField: fnd6_invwip
DataFieldDescription: Inventories - Work In Process
DataField: fnd6_pidom
DataFieldDescription: Pretax Income - Domestic
DataField: fnd6_newa1v1300_caps
DataFieldDescription: Capital Surplus/Share Premium Reserve
DataField: fnd6_mfma1_apalch
DataFieldDescription: Accounts Payable and Accrued Liabilities - Increase/(Decrease)
DataField: fnd6_idesindq_curcd
DataFieldDescription: ISO Currency Code - Company Annual Market
DataField: fnd6_newqeventv110_xiq
DataFieldDescription: Extraordinary Items
DataField: fnd6_dvrated
DataFieldDescription: Indicated Annual Dividend Rate - Daily
DataField: fnd6_newqv1300_cshoq
DataFieldDescription: Common Shares Outstanding
DataField: fnd6_newqv1300_pncq
DataFieldDescription: Core Pension Adjustment
DataField: fnd6_txtubposinc
DataFieldDescription: Increase - Current Tax Positions
DataField: fnd6_fic
DataFieldDescription: identifies the country in which the company is incorporated or legally registered
DataField: fnd6_newa2v1300_rdipeps
DataFieldDescription: In Process R&D Expense Basic EPS Effect
DataField: fnd6_newqv1300_cshprq
DataFieldDescription: Common Shares Used to Calculate Earnings Per Share - Basic
DataField: fnd6_prch
DataFieldDescription: Price High - Annual
DataField: fnd6_prcl
DataFieldDescription: Price Low - Annual
DataField: fnd6_newqeventv110_dpactq
DataFieldDescription: Depreciation, Depletion and Amortization (Accumulated)
DataField: fnd6_newa2v1300_spceeps
DataFieldDescription: S&P Core Earnings EPS Basic
DataField: fnd6_newqv1300_ibmiiq
DataFieldDescription: Income before Extraordinary Items and Noncontrolling Interests
DataField: fnd6_dxd4
DataFieldDescription: Debt (excl Capitalized Leases) - Due in 4th Year
DataField: fnd6_dn
DataFieldDescription: Debt - Notes
DataField: fnd6_newqeventv110_rrpq
DataFieldDescription: Reversal - Restructuring/Acquisition Pretax
DataField: pretax_income
DataFieldDescription: Pretax Income
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: est_epsr
DataFieldDescription: GAAP Earnings per share - mean of estimations
DataField: actuals_value_currency_code
DataFieldDescription: Pricing Currency where the security trades
DataField: anl4_eaz2lltv110_estvalue
DataFieldDescription: Estimation value
DataField: anl4_bac1conqfv110_item
DataFieldDescription: Financial item
DataField: anl4_fsdtlestmtafv4_item
DataFieldDescription: Financial item
DataField: net_income_adjusted
DataFieldDescription: Adjusted net income- announced financial value for annual frequency
DataField: shares_outstanding_max_guidance
DataFieldDescription: Maximum guidance value for Shares
DataField: earnings_per_share_reported
DataFieldDescription: Reported Earnings Per Share - Actual Value
DataField: anl4_cuo1guidaf_minguidance
DataFieldDescription: Minimum guidance value
DataField: anl4_dez1basicqfv4v104_est
DataFieldDescription: Estimation value
DataField: anl4_netdebt_mean
DataFieldDescription: Net debt - mean of estimations
DataField: gross_income_reported_value
DataFieldDescription: Gross Income value for the quarter
DataField: sales_estimate_average_annual
DataFieldDescription: Sales - mean of estimations
DataField: anl4_totassets_low
DataFieldDescription: Total Assets - The lowest estimation
DataField: anl4_afv4_eps_mean
DataFieldDescription: Earnings per share - mean of estimations for annual frequency
DataField: anl4_basicdetailqfv110_estvalue
DataFieldDescription: Estimation value
DataField: anl4_fsguidanceqfv4_item
DataFieldDescription: Financial item
DataField: anl4_ads1detailqfv110_bk
DataFieldDescription: Broker name (int)
DataField: anl4_basicdetaillt_person
DataFieldDescription: Broker Id
DataField: anl4_dez1qfv4_est
DataFieldDescription: Estimation value
DataField: anl4_bac1detailafv110_item
DataFieldDescription: Financial item
DataField: guidance_estimate_value
DataFieldDescription: Estimated value for basic annual financial guidance
DataField: anl4_cff_low
DataFieldDescription: Cash Flow From Financing - The lowest estimation
DataField: anl4_qfv4_maxguidance
DataFieldDescription: Max guidance value
DataField: anl4_eaz2lqfv110_bk
DataFieldDescription: Broker name (int)
DataField: anl4_rd_exp_high
DataFieldDescription: Research and Development Expense - the highest estimation
DataField: max_free_cashflow_per_share_guidance
DataFieldDescription: The maximum guidance value for free cash flow per share.
DataField: max_customized_eps_guidance
DataFieldDescription: The maximum guidance value for custom earnings per share on an annual basis.
DataField: anl4_epsr_value
DataFieldDescription: GAAP Earnings per share - announced financial value
DataField: estimate_value_currency_code
DataFieldDescription: Home currency of instrument
DataField: pv13_rha2_min20_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min52_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f2_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_pureplay_513_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min24_500_sector
DataFieldDescription: Grouping fields for top 500
DataField: pv13_revere_parent
DataFieldDescription: Code of parent sector
DataField: pv13_revere_index_cap
DataFieldDescription: Company market capitalization
DataField: pv13_hierarchy_sector
DataFieldDescription: grouping fields
DataField: pv13_custretsig_retsig
DataFieldDescription: Sign of customer return
DataField: pv13_hierarchy_min5_f3g2_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_513_sector
DataFieldDescription: grouping fields
DataField: pv13_new_4l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min22_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_reporttype
DataFieldDescription: Type of report
DataField: pv13_revere_country
DataFieldDescription: Country code
DataField: pv13_hierarchy_f4_513_sector
DataFieldDescription: grouping fields
DataField: pv13_reportperiodend
DataFieldDescription: Stated end date for the report
DataField: pv13_hierarchy_min51_f1_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_2k_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_sector_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_5l_scibr
DataFieldDescription: grouping fields
DataField: rel_ret_comp
DataFieldDescription: Averaged one-day return of the competing companies
DataField: pv13_r2_min2_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min20_top3000_sector
DataFieldDescription: grouping fields
DataField: pv13_h_f3_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_pureplay_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_term_sector_total
DataFieldDescription: Number of terminal sectors for the company
DataField: rel_ret_part
DataFieldDescription: Averaged one-day return of the instrument's partners
DataField: pv13_hierarchy_f4_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min52_513_sector
DataFieldDescription: grouping fields
DataField: implied_volatility_mean_720
DataFieldDescription: At-the-money option-implied volatility mean for 720 days
DataField: implied_volatility_call_180
DataFieldDescription: At-the-money option-implied volatility for call Option for 180 days
DataField: implied_volatility_mean_skew_90
DataFieldDescription: At-the-money option-implied volatility mean skew for 90 days
DataField: implied_volatility_put_180
DataFieldDescription: At-the-money option-implied volatility for put option for 180 days
DataField: implied_volatility_put_20
DataFieldDescription: At-the-money option-implied volatility for Put Option for 20 days
DataField: implied_volatility_call_1080
DataFieldDescription: At-the-money option-implied volatility for call option for 1080 days
DataField: implied_volatility_mean_skew_360
DataFieldDescription: At-the-money option-implied volatility mean skew for 360 days
DataField: historical_volatility_60
DataFieldDescription: Close-to-close Historical volatility over 60 days
DataField: implied_volatility_mean_20
DataFieldDescription: At-the-money option-implied volatility mean for 20 days
DataField: historical_volatility_10
DataFieldDescription: Close-to-close Historical volatility over 10 days
DataField: parkinson_volatility_30
DataFieldDescription: Parkinson model's historical volatility over 30 days
DataField: implied_volatility_call_270
DataFieldDescription: At-the-money option-implied volatility for call Option for 270 days
DataField: implied_volatility_call_10
DataFieldDescription: At-the-money option-implied volatility for call Option for 10 days
DataField: implied_volatility_mean_skew_10
DataFieldDescription: At-the-money option-implied volatility mean skew 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_30
DataFieldDescription: At-the-money option-implied volatility mean for 30 days
DataField: implied_volatility_call_20
DataFieldDescription: At-the-money option-implied volatility for call Option for 20 days
DataField: implied_volatility_mean_270
DataFieldDescription: At-the-money option-implied volatility mean for 270 days
DataField: parkinson_volatility_60
DataFieldDescription: Parkinson model's historical volatility over 60 days
DataField: implied_volatility_mean_60
DataFieldDescription: At-the-money option-implied volatility mean for 60 days
DataField: implied_volatility_call_120
DataFieldDescription: At-the-money option-implied volatility for call Option for 120 days
DataField: implied_volatility_call_60
DataFieldDescription: At-the-money option-implied volatility for call Option for 60 days
DataField: implied_volatility_put_1080
DataFieldDescription: At-the-money option-implied volatility for Put Option for 3 years
DataField: implied_volatility_mean_90
DataFieldDescription: At-the-money option-implied volatility mean for 90 days
DataField: historical_volatility_90
DataFieldDescription: Close-to-close Historical volatility over 90 days
DataField: implied_volatility_mean_1080
DataFieldDescription: At-the-money option-implied volatility mean for 3 years
DataField: implied_volatility_call_30
DataFieldDescription: At-the-money option-implied volatility for call Option for 30 days
DataField: parkinson_volatility_10
DataFieldDescription: Parkinson model's historical volatility over 2 weeks
DataField: parkinson_volatility_150
DataFieldDescription: Parkinson model's historical volatility over 150 days
DataField: implied_volatility_put_60
DataFieldDescription: At-the-money option-implied volatility for Put Option for 60 days
DataField: nws12_afterhsz_prevclose
DataFieldDescription: Previous trading day's close price
DataField: nws12_afterhsz_epsactual
DataFieldDescription: The actual Earnings Per Share value that was conveyed by the news release
DataField: nws12_mainz_1p
DataFieldDescription: The minimum of L or S above for 1-minute bucket
DataField: nws12_prez_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: nws12_afterhsz_allticks
DataFieldDescription: Total number of ticks for the trading day
DataField: nws12_mainz_mainvwap
DataFieldDescription: Main session volume weighted average price
DataField: nws12_mainz_30_seconds
DataFieldDescription: The percent change in price in the 30 seconds following the news release
DataField: nws12_afterhsz_sl
DataFieldDescription: Whether a long or short position would have been more advantageous: If (EODHigh - Last) > (Last - EODLow) Then LS = 1; If (EODHigh - Last) = (Last - EODLow) Then LS = 0; If (EODHigh - Last) < (Last - EODLow) Then LS = -1.
DataField: nws12_mainz_1s
DataFieldDescription: Number of minutes that elapsed before price went down 1 percentage point
DataField: nws12_mainz_2l
DataFieldDescription: Number of minutes that elapsed before price went up 2 percentage points
DataField: nws12_afterhsz_4p
DataFieldDescription: The minimum of L or S above for 4-minute bucket
DataField: news_ton_high
DataFieldDescription: Highest price reached during the session before the time of news
DataField: nws12_afterhsz_tonlow
DataFieldDescription: Lowest price reached during the session before the time of the news
DataField: news_mins_4_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 4 percentage points
DataField: nws12_prez_eodhigh
DataFieldDescription: Highest price reached between the time of news and the end of the session
DataField: nws12_prez_vol_ratio
DataFieldDescription: Curr_Vol / Mov_Vol
DataField: nws12_prez_dayopen
DataFieldDescription: Price at the session open
DataField: nws12_prez_result1
DataFieldDescription: Percent change between the price at the time of the news release to the price at the close of the session
DataField: nws12_mainz_reportsess
DataFieldDescription: Index of Session on which the spreadsheet is reporting
DataField: nws12_prez_4l
DataFieldDescription: Number of minutes that elapsed before price went up 4 percentage points
DataField: nws12_afterhsz_2l
DataFieldDescription: Number of minutes that elapsed before price went up 2 percentage points
DataField: nws12_mainz_5s
DataFieldDescription: Number of minutes that elapsed before price went down 5 percentage points
DataField: news_tot_ticks
DataFieldDescription: Total number of ticks for the trading day
DataField: nws12_afterhsz_maxdown
DataFieldDescription: Percent change from the price at the time of the news to the after the news low
DataField: nws12_prez_rangeamt
DataFieldDescription: Session High Price - Session Low Price
DataField: nws12_afterhsz_result2
DataFieldDescription: Percent change between the price at the time of the news release to the price at the close of the session
DataField: news_open_gap
DataFieldDescription: (DayOpen - PrevClose) / PrevClose
DataField: nws12_mainz_tonlow
DataFieldDescription: Lowest price reached during the session before the time of the news
DataField: news_mins_10_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: nws18_ber
DataFieldDescription: News sentiment specializing in earnings result
DataField: rp_nip_price
DataFieldDescription: News impact projection of stock price news
DataField: rp_nip_assets
DataFieldDescription: News impact projection of assets news
DataField: nws18_acb
DataFieldDescription: News sentiment specializing in corporate action announcements
DataField: rp_nip_credit
DataFieldDescription: News impact projection of credit news
DataField: rp_ess_insider
DataFieldDescription: Event sentiment score of insider trading news
DataField: nws18_nip
DataFieldDescription: Degree of impact of the news
DataField: rp_ess_labor
DataFieldDescription: Event sentiment score of labor issues news
DataField: rp_nip_product
DataFieldDescription: News impact projection of product and service-related news
DataField: rp_ess_legal
DataFieldDescription: Event sentiment score of legal news
DataField: rp_ess_price
DataFieldDescription: Event sentiment score of stock price news
DataField: rp_css_ptg
DataFieldDescription: Composite sentiment score of price target news
DataField: rp_ess_credit
DataFieldDescription: Event sentiment score of credit news
DataField: nws18_ghc_lna
DataFieldDescription: Change in analyst recommendation
DataField: rp_css_earnings
DataFieldDescription: Composite sentiment score of earnings news
DataField: rp_nip_credit_ratings
DataFieldDescription: News impact projection of credit ratings news
DataField: nws18_qep
DataFieldDescription: News sentiment based on positive and negative words on global equity
DataField: rp_ess_assets
DataFieldDescription: Event sentiment score of assets news
DataField: nws18_bam
DataFieldDescription: News sentiment specializing in mergers and acquisitions
DataField: rp_nip_technical
DataFieldDescription: News impact projection based on technical analysis
DataField: rp_ess_society
DataFieldDescription: Event sentiment score of society-related news
DataField: nws18_ssc
DataFieldDescription: Sentiment of the news calculated using multiple techniques
DataField: nws18_relevance
DataFieldDescription: Relevance of news to the company
DataField: rp_css_society
DataFieldDescription: Composite sentiment score of society-related news
DataField: rp_ess_partner
DataFieldDescription: Event sentiment score of partnership news
DataField: rp_css_product
DataFieldDescription: Composite sentiment score of product and service-related news
DataField: rp_ess_equity
DataFieldDescription: Event sentiment score of equity action news
DataField: nws18_sse
DataFieldDescription: Sentiment of phrases impacting the company
DataField: rp_css_legal
DataFieldDescription: Composite sentiment score of legal news
DataField: rp_css_assets
DataFieldDescription: Composite sentiment score of assets news
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_incremental_shares_attributable_to_share_based_payment_a
DataFieldDescription: Additional shares included in the calculation of diluted EPS as a result of the potentially dilutive effect of share-based payment arrangements using the treasury stock method.
DataField: fnd2_ebitdm
DataFieldDescription: EBIT, Domestic
DataField: fnd2_a_sbcpnargmtwfsptepddvdrt
DataFieldDescription: The estimated dividend rate (a percentage of the share price) to be paid (expected dividends) to holders of the underlying shares over the option's term.
DataField: fn_intangible_assets_accum_amort_a
DataFieldDescription: Accumulated amount of amortization of assets, excluding financial assets and goodwill, lacking physical substance with a finite life.
DataField: fn_assets_fair_val_q
DataFieldDescription: Asset Fair Value, Recurring, Total
DataField: fn_debt_instrument_interest_rate_stated_percentage_q
DataFieldDescription: Stated percentage of interest rate on debt
DataField: fn_proceeds_from_lt_debt_a
DataFieldDescription: Proceeds From Issuance Of Debt, Long Term
DataField: fn_treasury_stock_shares_q
DataFieldDescription: Number of common and preferred shares that were previously issued and that were repurchased by the issuing entity and held in treasury on the financial statement date. This stock has no voting rights and receives no dividends.
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_number_q
DataFieldDescription: Number of options outstanding, including both vested and non-vested options.
DataField: fn_derivative_notional_amount_a
DataFieldDescription: Nominal or face amount used to calculate payments on the derivative liability.
DataField: fn_liab_fair_val_l2_a
DataFieldDescription: Liabilities Fair Value, Recurring, Level 2
DataField: fnd2_a_dbplanservicecst
DataFieldDescription: The actuarial present value of benefits attributed by the pension benefit formula to services rendered by employees during the period. The portion of the expected postretirement benefit obligation attributed to employee service during the period. The service cost component is a portion of the benefit obligation and is unaffected by the funded status of the plan.
DataField: fn_interest_paid_net_a
DataFieldDescription: Net interest
DataField: fnd2_itxreclchgdfdtxava
DataFieldDescription: Amount 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 attributable to increase (decrease) in the valuation allowance for deferred tax assets.
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: fnd2_a_curritxexp
DataFieldDescription: Income Tax Expense, Current
DataField: fn_accum_oth_income_loss_fx_adj_net_of_tax_a
DataFieldDescription: Accumulated adjustment, net of tax, that results from the process of translating subsidiary financial statements and foreign equity investments into the reporting currency from the functional currency of the reporting entity, net of reclassification of realized foreign currency translation gains or losses.
DataField: fn_comp_options_exercisable_weighted_avg_q
DataFieldDescription: The weighted-average price as of the balance sheet date at which grantees can acquire the shares reserved for issuance on vested portions of options outstanding and currently exercisable under the stock option plan.
DataField: fn_accum_oth_income_loss_net_of_tax_a
DataFieldDescription: Accumulated change in equity from transactions and other events and circumstances from non-owner sources, net of tax effect, at period end. Excludes Net Income (Loss), and accumulated changes in equity from transactions resulting from investments by owners and distributions to owners. Includes foreign currency translation items, certain pension adjustments, unrealized gains and losses on certain investments in debt and equity securities, other than temporary impairment (OTTI) losses related to factors other than credit losses on available-for-sale and held-to-maturity debt securities that an entity does not intend to sell and it is not more likely than not that the entity will be required to sell before recovery of the amortized cost basis, as well as changes in the fair value of derivatives related to the effective portion of a designated cash flow hedge.
DataField: fnd2_asdm
DataFieldDescription: Assets, Domestic
DataField: fn_accum_oth_income_loss_net_of_tax_q
DataFieldDescription: Accumulated change in equity from transactions and other events and circumstances from non-owner sources, net of tax effect, at period end. Excludes Net Income (Loss), and accumulated changes in equity from transactions resulting from investments by owners and distributions to owners. Includes foreign currency translation items, certain pension adjustments, unrealized gains and losses on certain investments in debt and equity securities, other than temporary impairment (OTTI) losses related to factors other than credit losses on available-for-sale and held-to-maturity debt securities that an entity does not intend to sell and it is not more likely than not that the entity will be required to sell before recovery of the amortized cost basis, as well as changes in the fair value of derivatives related to the effective portion of a designated cash flow hedge.
DataField: fn_interest_payable_q
DataFieldDescription: Carrying value as of the balance sheet date of accrued interest payable on all forms of debt, including trade payables, that has been incurred and is unpaid. For classified balance sheets, used to reflect the current portion of the liabilities (due within 1 year or within the normal operating cycle if longer); for unclassified balance sheets, used to reflect the total liabilities (regardless of due date).
DataField: fn_new_shares_options_q
DataFieldDescription: Number of share options (or share units) exercised during the current period.
DataField: fn_accum_depr_depletion_and_amortization_ppne_q
DataFieldDescription: Amount of accumulated depreciation, depletion and amortization for physical assets used in the normal conduct of business to produce goods and services.
DataField: fn_antidilutive_securities_excl_from_eps_q
DataFieldDescription: Securities (including those issuable pursuant to contingent stock agreements) that could potentially dilute basic earnings per share (EPS) or earnings per unit (EPU) in the future that were not included in the computation of diluted EPS or EPU because to do so would increase EPS or EPU amounts or decrease loss per share or unit amounts for the period presented.
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_number_of_shares_authorized_q
DataFieldDescription: The maximum number of shares (or other type of equity) originally approved (usually by shareholders and board of directors), net of any subsequent amendments and adjustments, for awards under the equity-based compensation plan. As stock or unit options and equity instruments other than options are awarded to participants, the shares or units remain authorized and become reserved for issuance under outstanding awards (not necessarily vested).
DataField: fn_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: 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 =======================================