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

以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子

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

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

DataField: forward_price_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: call_breakeven_60
DataFieldDescription: Price at which a stock's call options with expiration 60 days in the future break even based on its recent bid/ask mean.
DataField: 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_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: call_breakeven_720
DataFieldDescription: Price at which a stock's call options with expiration 720 days in the future break even based on its recent bid/ask mean.
DataField: 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: pcr_vol_10
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 10 days in the future.
DataField: forward_price_180
DataFieldDescription: Forward price at 180 days derived from a synthetic long option with payoff similar to long stock + option dynamics. combination of long ATM call, and short ATM put.
DataField: forward_price_90
DataFieldDescription: Forward price at 90 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: option_breakeven_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: 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_720
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 720 days in the future.
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: 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_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: 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_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: option_breakeven_1080
DataFieldDescription: Price at which a stock's options with expiration 1080 days in the future break even based on its recent bid/ask mean.
DataField: 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: 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: 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: call_breakeven_180
DataFieldDescription: Price at which a stock's call options with expiration 180 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_20
DataFieldDescription: Forward price at 20 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: pcr_vol_all
DataFieldDescription: Ratio of put volume to call volume for all maturities on stock's options.
DataField: call_breakeven_270
DataFieldDescription: Price at which a stock's call options with expiration 270 days in the future break even based on its recent bid/ask mean.
DataField: pcr_vol_60
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 60 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: pcr_vol_90
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 90 days in the future.
DataField: fnd6_newqv1300_dlcq
DataFieldDescription: Debt in Current Liabilities
DataField: fnd6_newqeventv110_loq
DataFieldDescription: Liabilities - Other
DataField: fnd6_newqeventv110_spceq
DataFieldDescription: S&P Core Earnings
DataField: fnd6_newqeventv110_pnciepspq
DataFieldDescription: Core Pension Interest Adjustment Basic EPS Effect Preliminary
DataField: fnd6_newqeventv110_invoq
DataFieldDescription: Inventory - Other
DataField: fnd6_newa1v1300_ceq
DataFieldDescription: Common/Ordinary Equity - Total
DataField: fnd6_cptnewqeventv110_rectq
DataFieldDescription: Receivables - Total
DataField: fnd6_newa1v1300_chech
DataFieldDescription: Cash and Cash Equivalents - Increase/(Decrease)
DataField: fnd6_newqv1300_lul3q
DataFieldDescription: Liabilities Level 3 (Unobservable)
DataField: fnd6_newqeventv110_lul3q
DataFieldDescription: Liabilities Level 3 (Unobservable)
DataField: fnd6_newqeventv110_xoptd12p
DataFieldDescription: Implied Option 12MM EPS Diluted Preliminary
DataField: fnd6_cptnewqeventv110_nopiq
DataFieldDescription: Non-Operating Income (Expense) - Total
DataField: fnd6_newqv1300_loq
DataFieldDescription: Liabilities - Other
DataField: fnd6_newqeventv110_aul3q
DataFieldDescription: Assets Level 3 (Unobservable)
DataField: fnd6_ibs
DataFieldDescription: Income before Extraordinary Items
DataField: fnd6_newa1v1300_ibcom
DataFieldDescription: Income Before Extraordinary Items - Available for Common
DataField: fnd6_newqeventv110_rcaq
DataFieldDescription: Restructuring Cost After-tax
DataField: fnd6_newqeventv110_glceeps12
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) Basic EPS Effect 12MM
DataField: capex
DataFieldDescription: Capital Expenditures
DataField: fnd6_newqeventv110_dpactq
DataFieldDescription: Depreciation, Depletion and Amortization (Accumulated)
DataField: fnd6_mfma2_oancf
DataFieldDescription: Operating Activities - Net Cash Flow
DataField: fnd6_newa1v1300_aoloch
DataFieldDescription: Assets and Liabilities - Other - Net Change
DataField: fnd6_newq_xoptqp
DataFieldDescription: Implied Option Expense Preliminary
DataField: fnd6_txdi
DataFieldDescription: Income Taxes - Deferred
DataField: fnd6_optvolq
DataFieldDescription: Volatility - Assumption (%)
DataField: fnd6_newqv1300_txditcq
DataFieldDescription: Deferred Taxes and Investment Tax Credit
DataField: fnd6_nxints
DataFieldDescription: Net Interest Income (Expense)
DataField: fnd6_eventv110_nrtxtdq
DataFieldDescription: Nonrecurring Income Taxes Diluted EPS Effect
DataField: fnd6_eventv110_wddq
DataFieldDescription: Writedowns Diluted EPS Effect
DataField: fnd6_newqeventv110_spceepsq
DataFieldDescription: S&P Core Earnings EPS Basic
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: min_adjusted_funds_from_operations_adj_guidance
DataFieldDescription: Minimum guidance value for Adjusted funds from operation
DataField: est_sales
DataFieldDescription: Sales - mean of estimations
DataField: anl4_qfd1_az_eps_number
DataFieldDescription: Earnings per share - number of estimations
DataField: min_ebit_guidance
DataFieldDescription: Minimum guidance value for Earnings Before Interest and Taxes (EBIT)
DataField: anl4_tbvps_number
DataFieldDescription: Tangible Book Value per Share - number of estimations
DataField: anl4_baz1v110_estvalue
DataFieldDescription: Estimation value
DataField: min_free_cashflow_guidance
DataFieldDescription: Minimum guidance value for Free Cash Flow
DataField: anl4_basicconltv110_pu
DataFieldDescription: The number of upper estimations
DataField: anl4_qfv4_actual
DataFieldDescription: Announced financial data
DataField: earnings_per_share_reported_value
DataFieldDescription: Reported Earnings Per Share - Actual Value
DataField: max_reported_pretax_income_guidance
DataFieldDescription: Reported Pretax income- maximum guidance value
DataField: anl4_fsguidanceafv4_maxguidance
DataFieldDescription: Maximum guidance value
DataField: earnings_per_share_median_value
DataFieldDescription: Earnings per share - median of estimations
DataField: min_net_income_guidance
DataFieldDescription: Net profit - minimum guidance value
DataField: anl4_netdebt_number
DataFieldDescription: Net debt - Number of estimations
DataField: anl4_cff_low
DataFieldDescription: Cash Flow From Financing - The lowest estimation
DataField: anl4_totgw_low
DataFieldDescription: Total Goodwill - The lowest estimation
DataField: anl4_qfv4_eps_high
DataFieldDescription: Earnings per share - The highest estimation
DataField: anl4_qf_az_wol_spfc
DataFieldDescription: Cash Flow Per Share - The lowest estimation
DataField: anl4_fcfps_low
DataFieldDescription: Free Cash Flow Per Share - the lowest estimation
DataField: max_stock_option_expense_guidance
DataFieldDescription: Stock option expense - Maximum guidance value for the annual period
DataField: anl4_eaz1laf_prevval
DataFieldDescription: The previous estimation of financial item
DataField: anl4_fsactualafv4_item
DataFieldDescription: Financial item
DataField: min_adjusted_funds_from_operations_guidance
DataFieldDescription: Funds from operation - minimum guidance value
DataField: pretax_income_reported_min_guidance
DataFieldDescription: Reported Pretax income - minimum guidance value
DataField: anl4_qf_az_div_mean
DataFieldDescription: Dividend per share - average of estimations
DataField: anl4_epsr_value
DataFieldDescription: GAAP Earnings per share - announced financial value
DataField: anl4_dez1basicqfv4_preest
DataFieldDescription: The previous estimation of finanicial item
DataField: eps_max_guidance_quarterly
DataFieldDescription: The maximum guidance value for Earnings Per Share.
DataField: anl4_baz1v110_bk
DataFieldDescription: Broker name (int)
DataField: pv13_hierarchy_min100_2000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_industry_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_min2_1000_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_top3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_comproduct_company
DataFieldDescription: Company product
DataField: pv13_rha2_min10_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min50_f3_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min5_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min5_corr21_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_1l_scibr
DataFieldDescription: grouping fields
DataField: pv13_r2_min5_1000_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min52_1k_sector
DataFieldDescription: Grouping fields for top 1000
DataField: pv13_3l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min22_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f2_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min52_2k_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy23_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min30_3000_mapped_513_sector
DataFieldDescription: grouping fields
DataField: pv13_4l_scibr
DataFieldDescription: grouping fields
DataField: rel_num_comp
DataFieldDescription: number of the instrument's competitors
DataField: pv13_rha2_min5_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_industry_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f1_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_rha2_min5_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_pureplay_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min25_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f4_513_sector
DataFieldDescription: grouping fields
DataField: implied_volatility_mean_1080
DataFieldDescription: At-the-money option-implied volatility mean for 3 years
DataField: implied_volatility_call_720
DataFieldDescription: At-the-money option-implied volatility for call Option for 720 days
DataField: implied_volatility_put_60
DataFieldDescription: At-the-money option-implied volatility for Put Option for 60 days
DataField: implied_volatility_put_120
DataFieldDescription: At-the-money option-implied volatility for Put Option for 120 days
DataField: implied_volatility_call_120
DataFieldDescription: At-the-money option-implied volatility for call Option for 120 days
DataField: historical_volatility_120
DataFieldDescription: Close-to-close Historical volatility over 120 days
DataField: implied_volatility_mean_skew_120
DataFieldDescription: At-the-money option-implied volatility mean skew for 120 days
DataField: implied_volatility_call_60
DataFieldDescription: At-the-money option-implied volatility for call Option for 60 days
DataField: parkinson_volatility_120
DataFieldDescription: Parkinson model's historical volatility over 120 days
DataField: historical_volatility_180
DataFieldDescription: Close-to-close Historical volatility over 180 days
DataField: implied_volatility_put_720
DataFieldDescription: At-the-money option-implied volatility for Put Option for 720 days
DataField: implied_volatility_put_360
DataFieldDescription: At-the-money option-implied volatility for Put Option for 360 days
DataField: implied_volatility_call_20
DataFieldDescription: At-the-money option-implied volatility for call Option for 20 days
DataField: implied_volatility_mean_20
DataFieldDescription: At-the-money option-implied volatility mean for 20 days
DataField: implied_volatility_mean_skew_1080
DataFieldDescription: At-the-money option-implied volatility mean skew for 3 years
DataField: implied_volatility_put_90
DataFieldDescription: At-the-money option-implied volatility for Put Option for 90 days
DataField: implied_volatility_mean_skew_60
DataFieldDescription: At-the-money option-implied volatility mean skew for 60 days
DataField: implied_volatility_put_30
DataFieldDescription: At-the-money option-implied volatility for Put Option for 30 days
DataField: parkinson_volatility_180
DataFieldDescription: Parkinson model's historical volatility over 180 days
DataField: implied_volatility_put_270
DataFieldDescription: At-the-money option-implied volatility for Put Option for 270 days
DataField: implied_volatility_mean_skew_720
DataFieldDescription: At-the-money option-implied volatility mean skew for 720 days
DataField: historical_volatility_30
DataFieldDescription: Close-to-close Historical volatility over 30 days
DataField: implied_volatility_call_1080
DataFieldDescription: At-the-money option-implied volatility for call option for 1080 days
DataField: parkinson_volatility_30
DataFieldDescription: Parkinson model's historical volatility over 30 days
DataField: implied_volatility_mean_30
DataFieldDescription: At-the-money option-implied volatility mean for 30 days
DataField: implied_volatility_mean_120
DataFieldDescription: At-the-money option-implied volatility mean for 120 days
DataField: historical_volatility_20
DataFieldDescription: Close-to-close Historical volatility over 20 days
DataField: implied_volatility_mean_720
DataFieldDescription: At-the-money option-implied volatility mean for 720 days
DataField: implied_volatility_put_180
DataFieldDescription: At-the-money option-implied volatility for put option for 180 days
DataField: historical_volatility_90
DataFieldDescription: Close-to-close Historical volatility over 90 days
DataField: nws12_allz_provider
DataFieldDescription: index of name of the news provider
DataField: nws12_afterhsz_01p
DataFieldDescription: The minimum of L or S above for 10 minute bucket
DataField: nws12_prez_02p
DataFieldDescription: The minimum of L or S above for 20-minute bucket
DataField: nws12_mainz_02p
DataFieldDescription: The minimum of L or S above for 20-minute bucket
DataField: nws12_prez_maxdown
DataFieldDescription: Percent change from the price at the time of the news to the after the news low
DataField: news_mins_5_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 5 percentage points
DataField: nws12_mainz_opengap
DataFieldDescription: (DayOpen - PrevClose) / PrevClose
DataField: nws12_prez_mainvwap
DataFieldDescription: Main session volume-weighted average price
DataField: nws12_prez_30_seconds
DataFieldDescription: The percent change in price in the 30 seconds following the news release
DataField: nws12_mainz_1l
DataFieldDescription: Number of minutes that elapsed before price went up 1 percentage point
DataField: nws12_mainz_30_min
DataFieldDescription: The percent change in price in the first 30 minutes following the news release
DataField: nws12_mainz_57s
DataFieldDescription: Number of minutes that elapsed before price went down 7.5 percentage points
DataField: nws12_afterhsz_opengap
DataFieldDescription: (DayOpen - PrevClose) / PrevClose.
DataField: news_mins_3_pct_up
DataFieldDescription: Number of minutes that elapsed before price went up 3 percentage points
DataField: nws12_prez_reportsess
DataFieldDescription: Index of Session on which the spreadsheet is reporting
DataField: nws12_mainz_2l
DataFieldDescription: Number of minutes that elapsed before price went up 2 percentage points
DataField: nws12_afterhsz_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_mainz_90_min
DataFieldDescription: The percent change in price in the first 90 minutes following the news release
DataField: news_atr14
DataFieldDescription: 14-day Average True Range
DataField: news_close_vol
DataFieldDescription: Main close volume
DataField: nws12_prez_5_min
DataFieldDescription: The percent change in price in the first 5 minutes following the news release
DataField: nws12_afterhsz_provider
DataFieldDescription: index of name of the news provider
DataField: nws12_afterhsz_epsactual
DataFieldDescription: The actual Earnings Per Share value that was conveyed by the news release
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: nws12_prez_sl
DataFieldDescription: Whether a long or short position would have been more advantageous: If (EODHigh - Last) > (Last - EODLow) Then LS = 1; If (EODHigh - Last) = (Last - EODLow) Then LS = 0; If (EODHigh - Last) < (Last - EODLow) Then LS = -1.
DataField: nws12_prez_div_y
DataFieldDescription: Annual yield
DataField: nws12_prez_60_min
DataFieldDescription: The percent change in price in the first 60 minutes following the news release
DataField: news_pct_60min
DataFieldDescription: The percent change in price in the first 60 minutes following the news release
DataField: nws12_mainz_57p
DataFieldDescription: The minimum of L or S above for 7.5-minute bucket
DataField: news_low_exc_stddev
DataFieldDescription: (TONLast - EODLow) / StdDev, where StdDev is one standard deviation for the close price for 30 calendar days
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: rp_nip_ptg
DataFieldDescription: News impact projection of price target news
DataField: rp_nip_inverstor
DataFieldDescription: News impact projection of investor relations news
DataField: rp_ess_ptg
DataFieldDescription: Event sentiment score of price target news
DataField: rp_nip_business
DataFieldDescription: News impact projection of business-related news
DataField: rp_ess_legal
DataFieldDescription: Event sentiment score of legal news
DataField: rp_nip_insider
DataFieldDescription: News impact projection of insider trading news
DataField: rp_ess_dividends
DataFieldDescription: Event sentiment score of dividends news
DataField: rp_css_insider
DataFieldDescription: Composite sentiment score of insider trading news
DataField: nws18_ber
DataFieldDescription: News sentiment specializing in earnings result
DataField: rp_css_marketing
DataFieldDescription: Composite sentiment score of marketing news
DataField: rp_ess_revenue
DataFieldDescription: Event sentiment score of revenue news
DataField: rp_ess_technical
DataFieldDescription: Event sentiment score based on technical analysis
DataField: rp_css_credit
DataFieldDescription: Composite sentiment score of credit news
DataField: rp_ess_equity
DataFieldDescription: Event sentiment score of equity action news
DataField: rp_css_earnings
DataFieldDescription: Composite sentiment score of earnings news
DataField: rp_nip_price
DataFieldDescription: News impact projection of stock price news
DataField: rp_css_dividends
DataFieldDescription: Composite sentiment score of dividends news
DataField: rp_ess_mna
DataFieldDescription: Event sentiment score of mergers and acquisitions-related news
DataField: rp_css_society
DataFieldDescription: Composite sentiment score of society-related news
DataField: rp_nip_equity
DataFieldDescription: News impact projection of equity action news
DataField: rp_nip_technical
DataFieldDescription: News impact projection based on technical analysis
DataField: rp_css_ratings
DataFieldDescription: Composite sentiment score of analyst ratings-related news
DataField: rp_ess_business
DataFieldDescription: Event sentiment score of business-related news
DataField: rp_css_business
DataFieldDescription: Composite sentiment score of business-related news
DataField: nws18_nip
DataFieldDescription: Degree of impact of the news
DataField: rp_ess_credit
DataFieldDescription: Event sentiment score of credit news
DataField: nws18_event_similarity_days
DataFieldDescription: Days since a similar event was detected
DataField: nws18_qep
DataFieldDescription: News sentiment based on positive and negative words on global equity
DataField: rp_css_revenue
DataFieldDescription: Composite sentiment score of revenue news
DataField: rp_nip_legal
DataFieldDescription: News impact projection of legal news
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: fn_oth_income_loss_derivatives_qualifying_as_hedges_of_tax_q
DataFieldDescription: Amount after tax and reclassification adjustments, of increase (decrease) in accumulated gain (loss) from derivative instruments designated and qualifying as the effective portion of cash flow hedges and an entity's share of an equity investee's increase (decrease) in deferred hedging gain (loss).
DataField: fnd2_ebitfr
DataFieldDescription: EBIT, Foreign
DataField: fnd2_dfdfeditxexp
DataFieldDescription: Income Tax Expense, Deferred - Federal
DataField: fnd2_dbplanchgbnfolintcst
DataFieldDescription: Defined Benefit Plan Change In Benefit Obligation Interest Cost
DataField: fn_avg_diluted_sharesout_adj_a
DataFieldDescription: The sum of dilutive potential common shares or units used in the calculation of the diluted per-share or per-unit computation.
DataField: fnd2_sbcpnshardpreops
DataFieldDescription: Share-based compensation shares authorized under stock option plans exercise price range number of exercisable options
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_comp_options_out_number_q
DataFieldDescription: Number of options outstanding, including both vested and non-vested options.
DataField: fn_comp_options_grants_weighted_avg_q
DataFieldDescription: Weighted average price at which grantees could have acquired the underlying shares with respect to stock options that were terminated.
DataField: fn_assets_fair_val_l1_a
DataFieldDescription: Asset Fair Value, Recurring, Level 1
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_propplteqmuflmameqmt
DataFieldDescription: PPE, Equipment, Useful Life, Maximum
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_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_derivative_fair_value_of_derivative_asset_q
DataFieldDescription: Fair value, before effects of master netting arrangements, of a financial asset or other contract with one or more underlyings, notional amount or payment provision or both, and the contract can be net settled by means outside the contract or delivery of an asset. Includes assets elected not to be offset. Excludes assets not subject to a master netting arrangement.
DataField: fn_accrued_liab_curr_q
DataFieldDescription: Carrying value as of the balance sheet date of obligations incurred and payable, pertaining to costs that are statutory in nature, are incurred on contractual obligations, or accumulate over time and for which invoices have not yet been received or will not be rendered.
DataField: fn_payments_for_repurchase_of_common_stock_a
DataFieldDescription: Value reported on Cash Flow Statement. May include shares repurchased as part of a buyback plan, as well as shares purchased for employee compensation, etc.
DataField: fnd2_dfdtxlbsgwllandintas
DataFieldDescription: Amount of deferred tax liability attributable to taxable temporary differences from intangible assets including goodwill.
DataField: fn_comp_options_forfeitures_and_expirations_q
DataFieldDescription: For presentations that combine terminations, the number of shares under options that were cancelled during the reporting period as a result of occurrence of a terminating event specified in contractual agreements pertaining to the stock option plan or that expired.
DataField: fn_debt_instrument_face_amount_q
DataFieldDescription: Debt face amount
DataField: fn_def_tax_assets_liab_net_a
DataFieldDescription: Amount, after allocation of valuation allowances and deferred tax liability, of deferred tax asset attributable to deductible differences and carryforwards, without jurisdictional netting.
DataField: fnd2_a_opclpsnprtmbnfplansajnt
DataFieldDescription: Amount after tax and reclassification adjustments, of (increase) decrease in accumulated other comprehensive (income) loss related to pension and other postretirement defined benefit plans.
DataField: fn_liab_fair_val_l1_q
DataFieldDescription: Liabilities Fair Value, Recurring, Level 1
DataField: fn_repayments_of_debt_a
DataFieldDescription: The cash outflow during the period from the repayment of aggregate short-term and long-term debt. Excludes payment of capital lease obligations.
DataField: fn_interest_payable_a
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_comprehensive_income_net_of_tax_q
DataFieldDescription: Amount after tax of increase (decrease) in equity from transactions and other events and circumstances from net income and other comprehensive income, attributable to parent entity. Excludes changes in equity resulting from investments by owners and distributions to owners.
DataField: fn_op_lease_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_accum_oth_income_loss_fx_adj_net_of_tax_q
DataFieldDescription: Accumulated adjustment, net of tax, that results from the process of translating subsidiary financial statements and foreign equity investments into the reporting currency from the functional currency of the reporting entity, net of reclassification of realized foreign currency translation gains or losses.
DataField: fnd2_propplteqmuflmblgland
DataFieldDescription: PPE, Buildings & land, Useful Life, Minimum
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 =======================================