任务指令
你是一个WorldQuant WebSim因子工程师。你的任务是生成100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
关键函数：
ts_delta, ts_mean, ts_regression（获取斜率rettype参数）
ts_decay_linear, ts_zscore, ts_rank
ts_scale, ts_av_diff, ts_std_dev
ts_corr, ts_covariance（用于行业内序列）
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
关键函数：
group_mean, group_std, group_rank
group_zscore, group_neutralize, group_scale
rank, zscore, quantile（横截面）
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
关键函数：
ts_rank, if_else, 条件判断运算符
ts_std_dev（用于波动率调整）
ts_regression（不同状态使用不同参数）
trade_when（条件触发）
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）
核心概念：捕捉行业间的动量溢出和相关性变化
关键函数：
ts_corr, ts_covariance（跨行业）
group_mean（用于行业指数）
向量操作：vec_avg, vec_sum
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
关键函数：
ts_corr(volume, close, d)（量价关系）
ts_rank（历史相对位置）
ts_zscore（极端值识别）
days_from_last_change（事件驱动）
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]
运算符使用策略：
算术运算：add, subtract, multiply, divide
非线性变换：log, power, sqrt, signed_power
条件逻辑：if_else, and, or, 比较运算符
标准化处理：normalize, winsorize, scale
防止过拟合建议：
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）
*=====*
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）。
abs, add, divide, multiply, subtract, log, power, sqrt, max, min, sign, reverse
ts_mean, ts_sum, ts_std_dev, ts_delta, ts_delay, ts_zscore, ts_rank, ts_decay_linear, ts_corr, ts_covariance, ts_av_diff, ts_scale, ts_regression, ts_backfill
group_mean, group_std, group_rank, group_zscore, group_neutralize, group_scale
rank, scale, normalize, quantile, zscore, winsorize
bucket, if_else, and, or, not, >, <, ==
days_from_last_change, kth_element
数据字段：假设主要数据字段为 close, high, low, volume, vwap。可安全使用。
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 100行纯文本。
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：
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100行可立即在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

========================= 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

Operator: abs(x)
Description: Absolute value of x
Operator: add(x, y, filter = false), x + y
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), 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), x * y
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), x - y
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: put_breakeven_180
DataFieldDescription: Price at which a stock's put options with expiration 180 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_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: call_breakeven_1080
DataFieldDescription: Price at which a stock's call options with expiration 1080 days in the future break even based on its recent bid/ask mean.
DataField: call_breakeven_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: 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: 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_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: 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_360
DataFieldDescription: Price at which a stock's put options with expiration 360 days in the future break even based on its recent bid/ask mean.
DataField: pcr_oi_1080
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 1080 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: option_breakeven_360
DataFieldDescription: Price at which a stock's options with expiration 360 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_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: 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: put_breakeven_10
DataFieldDescription: Price at which a stock's put options with expiration 10 days in the future break even based on its recent bid/ask mean.
DataField: option_breakeven_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: call_breakeven_90
DataFieldDescription: Price at which a stock's call options with expiration 90 days in the future break even based on its recent bid/ask mean.
DataField: call_breakeven_60
DataFieldDescription: Price at which a stock's call options with expiration 60 days in the future break even based on its recent bid/ask mean.
DataField: pcr_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_30
DataFieldDescription: Price at which a stock's options with expiration 30 days in the future break even based on its recent bid/ask mean.
DataField: pcr_oi_150
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 150 days in the future.
DataField: pcr_vol_90
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 90 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: 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_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: 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_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: forward_price_360
DataFieldDescription: Forward price at 360 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: 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: put_breakeven_20
DataFieldDescription: Price at which a stock's put options with expiration 20 days in the future break even based on its recent bid/ask mean.
DataField: fnd6_prstkc
DataFieldDescription: Purchase of Common and Preferred Stock
DataField: fnd6_lqpl1
DataFieldDescription: Liabilities Level 1 (Quoted Prices)
DataField: fnd6_incorp
DataFieldDescription: Incorporated
DataField: fnd6_pnrsho
DataFieldDescription: Nonred Pfd Shares Outs (000)
DataField: fnd6_newqv1300_ivstq
DataFieldDescription: Short-Term Investments - Total
DataField: fnd6_newa2v1300_tstkn
DataFieldDescription: Treasury Stock - Number of Common Shares
DataField: bookvalue_ps
DataFieldDescription: Book Value Per Share
DataField: fnd6_newqeventv110_pncwipq
DataFieldDescription: Core Pension Without Interest Adjustment Pretax
DataField: fnd6_mfma1_csho
DataFieldDescription: Common Shares Outstanding
DataField: inventory_turnover
DataFieldDescription: Inventory Turnover
DataField: fnd6_newqv1300_loq
DataFieldDescription: Liabilities - Other
DataField: fnd6_newqeventv110_xopteps12
DataFieldDescription: Implied Option EPS Basic 12MM
DataField: fnd6_newqv1300_glced12
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) Diluted EPS Effect 12MM
DataField: cogs
DataFieldDescription: Cost of Goods Sold
DataField: fnd6_dudd
DataFieldDescription: Debt - Unamortized Debt Discount and Other
DataField: fnd6_newqeventv110_dvpq
DataFieldDescription: Dividends - Preferred/Preference
DataField: fnd6_beta
DataFieldDescription: beta
DataField: fnd6_dxd5
DataFieldDescription: Debt (excl Capitalized Leases) - Due in 5th Year
DataField: fnd6_cik
DataFieldDescription: nonimportant technical code
DataField: fnd6_newqeventv110_txdbq
DataFieldDescription: Deferred Taxes - Balance Sheet
DataField: fnd6_optrfr
DataFieldDescription: Risk-Free Rate - Assumption (%)
DataField: fnd6_newa1v1300_aoloch
DataFieldDescription: Assets and Liabilities - Other - Net Change
DataField: fnd6_newqeventv110_prcd12
DataFieldDescription: Core Post Retirement Adjustment Diluted EPS Effect 12 MM
DataField: fnd6_newqeventv110_epsfiq
DataFieldDescription: Earnings Per Share (Diluted) - Including Extraordinary Items
DataField: fnd6_newqv1300_ciotherq
DataFieldDescription: Comp Inc - Other Adj
DataField: equity
DataFieldDescription: Common/Ordinary Equity - Total
DataField: pretax_income
DataFieldDescription: Pretax Income
DataField: debt_st
DataFieldDescription: Debt in Current Liabilities
DataField: fnd6_cptmfmq_opepsq
DataFieldDescription: Earnings Per Share from Operations
DataField: fnd6_newqeventv110_dilavq
DataFieldDescription: Dilution Available - Excluding Extraordinary Items
DataField: scl12_alltype_buzzvec
DataFieldDescription: sentiment volume
DataField: scl12_alltype_sentvec
DataFieldDescription: sentiment
DataField: scl12_alltype_typevec
DataFieldDescription: instrument type index
DataField: scl12_buzz
DataFieldDescription: relative sentiment volume
DataField: scl12_buzz_fast_d1
DataFieldDescription: relative sentiment volume
DataField: scl12_buzzvec
DataFieldDescription: sentiment volume
DataField: scl12_sentiment
DataFieldDescription: sentiment
DataField: scl12_sentiment_fast_d1
DataFieldDescription: sentiment
DataField: scl12_sentvec
DataFieldDescription: sentiment
DataField: scl12_typevec
DataFieldDescription: instrument type index
DataField: snt_buzz
DataFieldDescription: negative relative sentiment volume, fill nan with 0
DataField: snt_buzz_bfl
DataFieldDescription: negative relative sentiment volume, fill nan with 1
DataField: snt_buzz_bfl_fast_d1
DataFieldDescription: negative relative sentiment volume, fill nan with 1
DataField: snt_buzz_fast_d1
DataFieldDescription: negative relative sentiment volume, fill nan with 0
DataField: snt_buzz_ret
DataFieldDescription: negative return of relative sentiment volume
DataField: snt_buzz_ret_fast_d1
DataFieldDescription: negative return of relative sentiment volume
DataField: snt_value
DataFieldDescription: negative sentiment, fill nan with 0
DataField: snt_value_fast_d1
DataFieldDescription: negative sentiment, fill nan with 0
DataField: analyst_revision_rank_derivative
DataFieldDescription: Change in ranking for analyst revisions and momentum compared to previous period.
DataField: cashflow_efficiency_rank_derivative
DataFieldDescription: Change in ranking for cash flow generation and profitability compared to previous period.
DataField: composite_factor_score_derivative
DataFieldDescription: Change in overall composite factor score from the prior period.
DataField: earnings_certainty_rank_derivative
DataFieldDescription: Change in ranking for earnings sustainability and certainty compared to previous period.
DataField: fscore_bfl_growth
DataFieldDescription: The purpose of this metric is to qualify the expected MT growth potential of the stock.
DataField: fscore_bfl_momentum
DataFieldDescription: The purpose of this metric is to identify stocks which are currently undergoing either up or downward analyst revisions.
DataField: fscore_bfl_profitability
DataFieldDescription: The purpose of this metric is to rank stock based on their ability to generate cash flows.
DataField: fscore_bfl_quality
DataFieldDescription: The purpose of this metric is to measure both the sustainability and certainty of earnings.
DataField: fscore_bfl_surface
DataFieldDescription: The static score. An index between 0 & 100 is applied for each stock and each composite factor - The first ranking is a pentagon surface-based score. The larger the surface, the higher the rank.
DataField: fscore_bfl_surface_accel
DataFieldDescription: The derivative score. In a second step, we calculate the derivative of this score (ie: Is the surface of the pentagon increasing or decreasing from the previous month?).
DataField: fscore_bfl_total
DataFieldDescription: The final score M-Score is a weighted average of both the Pentagon surface score and the Pentagon acceleration score.
DataField: fscore_bfl_value
DataFieldDescription: The purpose of this metric is to see if the stock is under or overpriced given several well known valuation standards.
DataField: fscore_growth
DataFieldDescription: The purpose of this metric is to qualify the expected MT growth potential of the stock.
DataField: fscore_momentum
DataFieldDescription: The purpose of this metric is to identify stocks which are currently undergoing either up or downward analyst revisions.
DataField: fscore_profitability
DataFieldDescription: The purpose of this metric is to rank stock based on their ability to generate cash flows.
DataField: fscore_quality
DataFieldDescription: The purpose of this metric is to measure both the sustainability and certainty of earnings.
DataField: fscore_surface
DataFieldDescription: The static score. An index between 0 & 100 is applied for each stock and each composite factor - The first ranking is a pentagon surface-based score. The larger the surface, the higher the rank.
DataField: fscore_surface_accel
DataFieldDescription: The derivative score. In a second step, we calculate the derivative of this score (ie: Is the surface of the pentagon increasing or decreasing from the previous month?).
DataField: fscore_total
DataFieldDescription: The final score M-Score is a weighted average of both the Pentagon surface score and the Pentagon acceleration score.
DataField: fscore_value
DataFieldDescription: The purpose of this metric is to see if the stock is under or overpriced given several well known valuation standards.
DataField: growth_potential_rank_derivative
DataFieldDescription: Change in ranking for medium-term growth potential compared to previous period.
DataField: multi_factor_acceleration_score_derivative
DataFieldDescription: Change in the acceleration of multi-factor score compared to previous period.
DataField: multi_factor_static_score_derivative
DataFieldDescription: Change in static multi-factor score compared to previous period.
DataField: relative_valuation_rank_derivative
DataFieldDescription: Change in ranking for valuation metrics compared to previous period.
DataField: snt_social_value
DataFieldDescription: Z score of sentiment
DataField: snt_social_volume
DataFieldDescription: Normalized tweet volume
DataField: beta_last_30_days_spy
DataFieldDescription: Beta to SPY in 30 Days
DataField: beta_last_360_days_spy
DataFieldDescription: Beta to SPY in 360 Days
DataField: beta_last_60_days_spy
DataFieldDescription: Beta to SPY in 60 Days
DataField: beta_last_90_days_spy
DataFieldDescription: Beta to SPY in 90 Days
DataField: correlation_last_30_days_spy
DataFieldDescription: Correlation to SPY in 30 Days
DataField: correlation_last_360_days_spy
DataFieldDescription: Correlation to SPY in 360 Days
DataField: correlation_last_60_days_spy
DataFieldDescription: Correlation to SPY in 60 Days
DataField: correlation_last_90_days_spy
DataFieldDescription: Correlation to SPY in 90 Days
DataField: systematic_risk_last_30_days
DataFieldDescription: Systematic Risk Last 30 Days
DataField: systematic_risk_last_360_days
DataFieldDescription: Systematic Risk Last 360 Days
DataField: systematic_risk_last_60_days
DataFieldDescription: Systematic Risk Last 60 Days
DataField: systematic_risk_last_90_days
DataFieldDescription: Systematic Risk Last 90 Days
DataField: unsystematic_risk_last_30_days
DataFieldDescription: Unsystematic Risk Last 30 Days - Relative to SPY
DataField: unsystematic_risk_last_360_days
DataFieldDescription: Unsystematic Risk Last 360 Days - Relative to SPY
DataField: unsystematic_risk_last_60_days
DataFieldDescription: Unsystematic Risk Last 60 Days - Relative to SPY
DataField: unsystematic_risk_last_90_days
DataFieldDescription: Unsystematic Risk Last 90 Days - Relative to SPY
DataField: anl4_eaz1laf_bk
DataFieldDescription: Broker name (int)
DataField: anl4_basicdetaillt_prevval
DataFieldDescription: The Previous Estimation of Financial Item
DataField: cash_flow_from_investing
DataFieldDescription: Cash Flow from Investing - Value
DataField: max_adjusted_eps_guidance
DataFieldDescription: The maximum guidance value for adjusted earnings per share.
DataField: min_adjusted_funds_from_operations_guidance
DataFieldDescription: Funds from operation - minimum guidance value
DataField: sales_estimate_standard_deviation
DataFieldDescription: Sales - standard deviation of estimations
DataField: anl4_fcf_median
DataFieldDescription: Free cash flow - aggregation on estimations, 50th percentile
DataField: funds_from_operations_max_guidance
DataFieldDescription: The maximum guidance value for Funds from operation - annual
DataField: eps_reported_min_guidance_qtr
DataFieldDescription: Reported Earnings Per Share - Minimum guidance value
DataField: selling_general_admin_expense
DataFieldDescription: Selling, General & Administrative Expense Value
DataField: anl4_capex_high
DataFieldDescription: Capital Expenditures - The highest estimation
DataField: min_total_assets_guidance
DataFieldDescription: Minimum guidance value for Total Assets
DataField: anl4_median_capexp
DataFieldDescription: Capital Expenditures - median of estimations
DataField: anl4_qf_az_wol_spe
DataFieldDescription: Earnings per share - The lowest estimation
DataField: anl4_qf_az_hgih_spe
DataFieldDescription: Earnings per share - The highest estimation
DataField: anl4_ads1detailafv110_person
DataFieldDescription: Broker Id
DataField: anl4_ebitda_flag
DataFieldDescription: Earnings before interest, taxes, depreciation and amortization - forecast type (revision/new/...)
DataField: anl4_bac1detailafv110_item
DataFieldDescription: Financial item
DataField: anl4_fcf_mean
DataFieldDescription: Free Cash Flow - mean of estimations
DataField: anl4_epsr_value
DataFieldDescription: GAAP Earnings per share - announced financial value
DataField: anl4_fsdtlestmtqfv4_item
DataFieldDescription: Financial item
DataField: sales_estimate_value
DataFieldDescription: Sales - Estimated value
DataField: capital_expenditure_guidance_value
DataFieldDescription: Capital Expenditures - Total value for the annual guidance
DataField: max_net_profit_guidance
DataFieldDescription: The maximum guidance value for net profit on an annual basis.
DataField: anl4_fsgdncbscv4_minguidance
DataFieldDescription: Minimum guidance value
DataField: max_investing_cashflow_guidance
DataFieldDescription: The maximum guidance value for Cash Flow from Investing.
DataField: earnings_per_share_min_guidance
DataFieldDescription: Minimum guidance value for Earnings Per Share on an annual basis.
DataField: anl4_basicdetaillt_estvalue
DataFieldDescription: Estimation value
DataField: anl4_basicdetailqfv110_prevval
DataFieldDescription: The previous estimation of financial item
DataField: est_sales
DataFieldDescription: Sales - mean of estimations
DataField: pv13_hierarchy_min100_corr21_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_2k_513_sector
DataFieldDescription: grouping fields
DataField: pv13_region
DataFieldDescription: Unique code of the region
DataField: pv13_r2_min2_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_min10_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f2_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f1_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f2_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min100_corr21_513_sector
DataFieldDescription: grouping fields
DataField: pv13_1l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f3_513_sector
DataFieldDescription: grouping fields
DataField: pv13_3l_scibr
DataFieldDescription: grouping fields
DataField: pv13_revere_term_sector_total
DataFieldDescription: Number of terminal sectors for the company
DataField: pv13_revere_comproduct_company
DataFieldDescription: Company product
DataField: pv13_rha2_min2_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min22_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f4_sector
DataFieldDescription: grouping fields
DataField: pv13_ustomergraphrank_page_rank
DataFieldDescription: the PageRank of customers
DataField: pv13_revere_zipcode
DataFieldDescription: Zip code
DataField: pv13_hierarchys32_sector
DataFieldDescription: grouping fields
DataField: rel_ret_all
DataFieldDescription: Averaged one-day return of the companies whose product overlapped with the instrument
DataField: pv13_h_min2_focused_sector
DataFieldDescription: Grouping fields for top 200
DataField: pv13_hierarchy_min40_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min40_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min5_500_sector
DataFieldDescription: Grouping fields
DataField: pv13_hierarchy_min2_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_liquid_min2_sector
DataFieldDescription: grouping fields
DataField: implied_volatility_put_270
DataFieldDescription: At-the-money option-implied volatility for Put Option for 270 days
DataField: implied_volatility_mean_270
DataFieldDescription: At-the-money option-implied volatility mean for 270 days
DataField: historical_volatility_150
DataFieldDescription: Close-to-close Historical volatility over 150 days
DataField: historical_volatility_20
DataFieldDescription: Close-to-close Historical volatility over 20 days
DataField: implied_volatility_mean_skew_30
DataFieldDescription: At-the-money option-implied volatility mean skew for 30 days
DataField: implied_volatility_call_60
DataFieldDescription: At-the-money option-implied volatility for call Option for 60 days
DataField: parkinson_volatility_60
DataFieldDescription: Parkinson model's historical volatility over 60 days
DataField: implied_volatility_put_30
DataFieldDescription: At-the-money option-implied volatility for Put Option for 30 days
DataField: historical_volatility_90
DataFieldDescription: Close-to-close Historical volatility over 90 days
DataField: parkinson_volatility_120
DataFieldDescription: Parkinson model's historical volatility over 120 days
DataField: implied_volatility_put_120
DataFieldDescription: At-the-money option-implied volatility for Put Option for 120 days
DataField: parkinson_volatility_10
DataFieldDescription: Parkinson model's historical volatility over 2 weeks
DataField: implied_volatility_put_180
DataFieldDescription: At-the-money option-implied volatility for put option for 180 days
DataField: implied_volatility_mean_180
DataFieldDescription: At-the-money option-implied volatility mean for 180 days
DataField: historical_volatility_30
DataFieldDescription: Close-to-close Historical volatility over 30 days
DataField: implied_volatility_call_20
DataFieldDescription: At-the-money option-implied volatility for call Option for 20 days
DataField: implied_volatility_mean_skew_180
DataFieldDescription: At-the-money option-implied volatility mean skew for 180 days
DataField: implied_volatility_put_10
DataFieldDescription: At-the-money option-implied volatility for Put Option for 10 days
DataField: implied_volatility_mean_30
DataFieldDescription: At-the-money option-implied volatility mean for 30 days
DataField: implied_volatility_call_360
DataFieldDescription: At-the-money option-implied volatility for call Option for 360 days
DataField: implied_volatility_mean_skew_20
DataFieldDescription: At-the-money option-implied volatility mean skew for 20 days
DataField: implied_volatility_put_360
DataFieldDescription: At-the-money option-implied volatility for Put Option for 360 days
DataField: implied_volatility_call_30
DataFieldDescription: At-the-money option-implied volatility for call Option for 30 days
DataField: implied_volatility_call_10
DataFieldDescription: At-the-money option-implied volatility for call Option for 10 days
DataField: implied_volatility_put_1080
DataFieldDescription: At-the-money option-implied volatility for Put Option for 3 years
DataField: historical_volatility_60
DataFieldDescription: Close-to-close Historical volatility over 60 days
DataField: parkinson_volatility_30
DataFieldDescription: Parkinson model's historical volatility over 30 days
DataField: implied_volatility_mean_90
DataFieldDescription: At-the-money option-implied volatility mean for 90 days
DataField: parkinson_volatility_90
DataFieldDescription: Parkinson model's historical volatility over 90 days
DataField: implied_volatility_call_1080
DataFieldDescription: At-the-money option-implied volatility for call option for 1080 days
DataField: nws12_afterhsz_01s
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: nws12_prez_01p
DataFieldDescription: The minimum of L or S above for 10-minute bucket
DataField: nws12_mainz_open_vol
DataFieldDescription: Main open volume
DataField: nws12_mainz_mov_vol
DataFieldDescription: 30-day moving average session volume
DataField: nws12_prez_1s
DataFieldDescription: Number of minutes that elapsed before price went down 1 percentage point
DataField: nws12_afterhsz_tonlow
DataFieldDescription: Lowest price reached during the session before the time of the news
DataField: nws12_prez_57p
DataFieldDescription: The minimum of L or S above for 7.5-minute bucket
DataField: nws12_afterhsz_allticks
DataFieldDescription: Total number of ticks for the trading day
DataField: nws12_afterhsz_opengap
DataFieldDescription: (DayOpen - PrevClose) / PrevClose.
DataField: nws12_prez_lowexcstddev
DataFieldDescription: (TONLast - EODLow)/StdDev, where StdDev is one standard deviation for the close price for 30 calendar days
DataField: nws12_mainz_57p
DataFieldDescription: The minimum of L or S above for 7.5-minute bucket
DataField: nws12_afterhsz_rangeamt
DataFieldDescription: Session High Price - Session Low Price
DataField: nws12_prez_newssess
DataFieldDescription: Index of session in which the news was reported
DataField: news_mins_7_5_chg
DataFieldDescription: The minimum of L or S above for 7.5-minute bucket
DataField: nws12_afterhsz_spylast
DataFieldDescription: Last Price of the SPY at the time of the news
DataField: nws12_afterhsz_3s
DataFieldDescription: Number of minutes that elapsed before price went down 3 percentage points
DataField: nws12_prez_div_y
DataFieldDescription: Annual yield
DataField: nws12_mainz_maxupamt
DataFieldDescription: The after-the-news high minus the price at the time of the news
DataField: nws12_prez_57l
DataFieldDescription: Number of minutes that elapsed before price went up 7.5 percentage points
DataField: nws12_afterhsz_range
DataFieldDescription: Session High Price - Session Low Price) / Session Low Price.
DataField: news_vol_stddev
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: news_open_vol
DataFieldDescription: Main open volume
DataField: nws12_afterhsz_tonlast
DataFieldDescription: Price at the time of news
DataField: nws12_prez_4s
DataFieldDescription: Number of minutes that elapsed before price went down 4 percentage points
DataField: news_atr14
DataFieldDescription: 14-day Average True Range
DataField: news_eod_vwap
DataFieldDescription: Volume weighted average price between the time of news and the end of the session
DataField: news_eod_high
DataFieldDescription: Highest price reached between the time of news and the end of the session
DataField: nws12_mainz_1p
DataFieldDescription: The minimum of L or S above for 1-minute bucket
DataField: news_low_exc_stddev
DataFieldDescription: (TONLast - EODLow) / StdDev, where StdDev is one standard deviation for the close price for 30 calendar days
DataField: nws12_afterhsz_close_vol
DataFieldDescription: Main close volume
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: rp_nip_earnings
DataFieldDescription: News impact projection of earnings news
DataField: rp_nip_legal
DataFieldDescription: News impact projection of legal news
DataField: rp_css_society
DataFieldDescription: Composite sentiment score of society-related news
DataField: rp_css_dividends
DataFieldDescription: Composite sentiment score of dividends news
DataField: rp_nip_product
DataFieldDescription: News impact projection of product and service-related news
DataField: rp_nip_insider
DataFieldDescription: News impact projection of insider trading news
DataField: rp_nip_ptg
DataFieldDescription: News impact projection of price target news
DataField: rp_css_mna
DataFieldDescription: Composite sentiment score of mergers and acquisitions-related news
DataField: rp_css_technical
DataFieldDescription: Composite sentiment score based on technical analysis
DataField: rp_ess_equity
DataFieldDescription: Event sentiment score of equity action news
DataField: rp_ess_ptg
DataFieldDescription: Event sentiment score of price target news
DataField: rp_css_partner
DataFieldDescription: Composite sentiment score of partnership news
DataField: nws18_acb
DataFieldDescription: News sentiment specializing in corporate action announcements
DataField: nws18_ghc_lna
DataFieldDescription: Change in analyst recommendation
DataField: rp_nip_mna
DataFieldDescription: News impact projection of mergers and acquisitions-related news
DataField: nws18_qep
DataFieldDescription: News sentiment based on positive and negative words on global equity
DataField: rp_css_ptg
DataFieldDescription: Composite sentiment score of price target news
DataField: rp_ess_revenue
DataFieldDescription: Event sentiment score of revenue news
DataField: rp_ess_partner
DataFieldDescription: Event sentiment score of partnership news
DataField: rp_ess_credit_ratings
DataFieldDescription: Event sentiment score of credit ratings news
DataField: rp_css_inverstor
DataFieldDescription: Composite sentiment score of investor relations news
DataField: rp_nip_equity
DataFieldDescription: News impact projection of equity action news
DataField: nws18_nip
DataFieldDescription: Degree of impact of the news
DataField: rp_ess_business
DataFieldDescription: Event sentiment score of business-related news
DataField: nws18_event_similarity_days
DataFieldDescription: Days since a similar event was detected
DataField: rp_ess_technical
DataFieldDescription: Event sentiment score based on technical analysis
DataField: rp_nip_price
DataFieldDescription: News impact projection of stock price news
DataField: nws18_ssc
DataFieldDescription: Sentiment of the news calculated using multiple techniques
DataField: nws18_event_relevance
DataFieldDescription: Relevance of the event to the story
DataField: nws18_ber
DataFieldDescription: News sentiment specializing in earnings result
DataField: fn_def_tax_assets_liab_net_q
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: 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: fn_debt_instrument_face_amount_q
DataFieldDescription: Debt face amount
DataField: fn_op_lease_min_pay_due_after_5y_a
DataFieldDescription: Amount of required minimum rental payments for operating leases having an initial or remaining non-cancelable lease term in excess of one year due after 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_options_exercises_weighted_avg_a
DataFieldDescription: Share-Based Compensation, Options Assumed, Weighted Average Exercise Price
DataField: fnd2_a_fedstyitxrt
DataFieldDescription: Effective Income Tax Rate Reconciliation - Federal Statutory Income Tax Rate %
DataField: fn_allowance_for_doubtful_accounts_receivable_a
DataFieldDescription: For an unclassified balance sheet, a valuation allowance for receivables due a company that are expected to be uncollectible.
DataField: fn_comp_non_opt_forfeited_q
DataFieldDescription: The number of equity-based payment instruments, excluding stock (or unit) options, that were forfeited during the reporting period.
DataField: fn_assets_fair_val_l3_q
DataFieldDescription: Asset Fair Value, Recurring, Level 3
DataField: fnd2_a_ltrmdmrepopliny5
DataFieldDescription: Amount of long-term debt payable, sinking fund requirements, and other securities issued that are redeemable by holder at fixed or determinable prices and dates maturing in 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_allowance_for_doubtful_accounts_receivable_q
DataFieldDescription: For an unclassified balance sheet, a valuation allowance for receivables due a company that are expected to be uncollectible.
DataField: fnd2_a_restructuringcharges
DataFieldDescription: Amount of expenses associated with exit or disposal activities pursuant to an authorized plan. Excludes expenses related to a discontinued operation or an asset retirement obligation.
DataField: fn_liab_fair_val_l3_a
DataFieldDescription: Liabilities Fair Value, Recurring, Level 3
DataField: fn_profit_loss_q
DataFieldDescription: The consolidated profit or loss for the period, net of income taxes, including the portion attributable to the noncontrolling interest.
DataField: fnd2_dbplanchgbnfolintcst
DataFieldDescription: Defined Benefit Plan Change In Benefit Obligation Interest Cost
DataField: fn_oth_comp_grants_weighted_avg_grant_date_fair_value_q
DataFieldDescription: Quarterly Share-Based Compensation Equity Instruments Other Than Options Nonvested Weighted Average Grant Date Fair Value
DataField: fn_payments_to_acquire_businesses_net_of_cash_acquired_a
DataFieldDescription: The cash outflow associated with the acquisition of a business, net of the cash acquired from the purchase.
DataField: fn_comp_options_grants_fair_value_a
DataFieldDescription: Annual Share-Based Compensation Arrangement by Share-Based Payment Award Options Grants in Period Weighted Average Grant Date Fair Value
DataField: fnd2_a_gsles1xtinguishmentofd
DataFieldDescription: Difference between the fair value of payments made and the carrying amount of debt which is extinguished prior to maturity.
DataField: fn_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_dbplanbnfol
DataFieldDescription: 1) For defined benefit pension plans, the benefit obligation is the projected benefit obligation, which is the actuarial present value as of a date of all benefits attributed by the pension benefit formula to employee service rendered prior to that date. 2) For other postretirement defined benefit plans, the benefit obligation is the accumulated postretirement benefit obligation, which is the actuarial present value of benefits attributed to employee service rendered to a particular date.
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_proceeds_from_lt_debt_q
DataFieldDescription: Proceeds From Issuance Of Debt, Long Term
DataField: fnd2_a_alsbcmpexrsus
DataFieldDescription: Allocated Share-Based Compensation Expense, Restricted Stock Units
DataField: fnd2_dbplanepdfbnfpyfour
DataFieldDescription: Amount of benefits from a defined benefit plan expected to be paid in the 4th fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: fnd2_a_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_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_debt_instrument_face_amount_a
DataFieldDescription: Debt face amount
DataField: fnd2_a_ltrmdmrepoplinyfour
DataFieldDescription: Amount of long-term debt payable, sinking fund requirements, and other securities issued that are redeemable by holder at fixed or determinable prices and dates maturing in the 4th fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: fnd2_a_dbplannpicbnfcst
DataFieldDescription: The total amount of net periodic benefit cost for defined benefit plans for the period. Periodic benefit costs include the following components: service cost, interest cost, expected return on plan assets, gain (loss), prior service cost or credit, transition asset or obligation, and gain (loss) due to settlements or curtailments.
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 =======================================