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: 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: option_breakeven_180
DataFieldDescription: Price at which a stock's options with expiration 180 days in the future break even based on its recent bid/ask mean.
DataField: pcr_vol_20
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 20 days in the future.
DataField: pcr_oi_10
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 10 days in the future.
DataField: pcr_vol_30
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 30 days in the future.
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: 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_20
DataFieldDescription: Price at which a stock's options with expiration 20 days in the future break even based on its recent bid/ask mean.
DataField: option_breakeven_10
DataFieldDescription: Price at which a stock's options with expiration 10 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_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: 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: pcr_oi_720
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 720 days in the future.
DataField: 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: call_breakeven_60
DataFieldDescription: Price at which a stock's call options with expiration 60 days in the future break even based on its recent bid/ask mean.
DataField: pcr_oi_90
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 90 days in the future.
DataField: put_breakeven_1080
DataFieldDescription: Price at which a stock's put options with expiration 1080 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_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: forward_price_120
DataFieldDescription: Forward price at 120 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: put_breakeven_720
DataFieldDescription: Price at which a stock's put options with expiration 720 days in the future break even based on its recent bid/ask mean.
DataField: call_breakeven_120
DataFieldDescription: Price at which a stock's call options with expiration 120 days in the future break even based on its recent bid/ask mean.
DataField: pcr_vol_360
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 360 days in the future.
DataField: forward_price_30
DataFieldDescription: Forward price at 30 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: pcr_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: put_breakeven_30
DataFieldDescription: Price at which a stock's put options with expiration 30 days in the future break even based on its recent bid/ask mean.
DataField: 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: forward_price_720
DataFieldDescription: Forward price at 720 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_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: 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_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: fnd6_lcoxdr
DataFieldDescription: Current Liabilities - Other - Excluding Deferred Revenue
DataField: fnd6_newqeventv110_pnciepsq
DataFieldDescription: Core Pension Interest Adjustment Basic EPS Effect
DataField: fnd6_tfva
DataFieldDescription: Total Fair Value Assets
DataField: fnd6_newqv1300_rcpq
DataFieldDescription: Restructuring Cost Pretax
DataField: fnd6_aldo
DataFieldDescription: Long-term Assets of Discontinued Operations
DataField: fnd6_newqeventv110_altoq
DataFieldDescription: Other Long-term Assets
DataField: fnd6_idesindq_curcd
DataFieldDescription: ISO Currency Code - Company Annual Market
DataField: fnd6_newqeventv110_csh12q
DataFieldDescription: Common Shares Used to Calculate Earnings Per Share - 12 Months Moving
DataField: fnd6_newa2v1300_oancf
DataFieldDescription: Operating Activities - Net Cash Flow
DataField: bookvalue_ps
DataFieldDescription: Book Value Per Share
DataField: fnd6_pidom
DataFieldDescription: Pretax Income - Domestic
DataField: cashflow
DataFieldDescription: Cashflow (Annual)
DataField: fnd6_cld2
DataFieldDescription: Capitalized Leases - Due in 2nd Year
DataField: fnd6_newqeventv110_glcea12
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) After-tax 12MM
DataField: fnd6_newqeventv110_xopt12
DataFieldDescription: Implied Option Expense - 12mm
DataField: fnd6_newqv1300_txdiq
DataFieldDescription: Income Taxes - Deferred
DataField: fnd6_dlto
DataFieldDescription: Debt - Long-Term - Other
DataField: fnd6_txdfo
DataFieldDescription: Deferred Taxes - Foreign
DataField: operating_expense
DataFieldDescription: Operating Expense - Total
DataField: fnd6_cptnewqv1300_dlttq
DataFieldDescription: Long-Term Debt - Total
DataField: fnd6_eventv110_pncepsq
DataFieldDescription: Core Pension Adjustment Basic EPS Effect
DataField: fnd6_newa1v1300_csho
DataFieldDescription: Common Shares Outstanding
DataField: fnd6_newa2v1300_spceeps
DataFieldDescription: S&P Core Earnings EPS Basic
DataField: fnd6_newqv1300_dpactq
DataFieldDescription: Depreciation, Depletion and Amortization (Accumulated)
DataField: fnd6_dd1
DataFieldDescription: Long-Term Debt Due in 1 Year
DataField: fnd6_dd5
DataFieldDescription: Debt Due in 5th Year
DataField: fnd6_cptnewqeventv110_epsfxq
DataFieldDescription: Earnings Per Share (Diluted) - Excluding Extraordinary items
DataField: fnd6_newqeventv110_glceepsq
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) Basic EPS Effect
DataField: fnd6_newqeventv110_lnoq
DataFieldDescription: Liabilities Netting & Other Adjustments
DataField: fnd6_newqeventv110_cshfdq
DataFieldDescription: Common Shares for Diluted EPS
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: max_shareholders_equity_guidance
DataFieldDescription: The maximum guidance value for Total Shareholders' Equity.
DataField: sales_estimate_average_annual
DataFieldDescription: Sales - mean of estimations
DataField: total_assets_amount
DataFieldDescription: Total Assets - actual value
DataField: anl4_qfv4_cfps_number
DataFieldDescription: Cash Flow Per Share - number of estimations
DataField: anl4_eaz2lafv110_person
DataFieldDescription: Broker Id
DataField: anl4_basicconltv110_pu
DataFieldDescription: The number of upper estimations
DataField: min_free_cash_flow_guidance
DataFieldDescription: The minimum guidance value for Free Cash Flow on an annual basis.
DataField: min_free_cashflow_guidance
DataFieldDescription: Minimum guidance value for Free Cash Flow
DataField: anl4_fcf_number
DataFieldDescription: Free Cash Flow - number of estimations
DataField: min_ebitda_guidance
DataFieldDescription: Minimum guidance value for Earnings Before Interest, Taxes, Depreciation, and Amortization (EBITDA) - Annual
DataField: anl4_ebit_number
DataFieldDescription: Earnings before interest and taxes - number of estimations
DataField: min_net_profit_guidance
DataFieldDescription: Minimum guidance value for Net Profit on an annual basis
DataField: anl4_ady_high
DataFieldDescription: The highest estimation
DataField: est_ffo
DataFieldDescription: Funds From Operation - Summary on Estimations, Mean
DataField: anl4_detailrecv4_est
DataFieldDescription: Estimation value for recommendation detail
DataField: earnings_per_share_guidance_value
DataFieldDescription: Earnings Per Share - guidance value for annual frequency
DataField: anl4_eaz2lafv110_bk
DataFieldDescription: Broker name (int)
DataField: anl4_totgw_low
DataFieldDescription: Total Goodwill - The lowest estimation
DataField: max_free_cash_flow_guidance
DataFieldDescription: The maximum guidance value for Free Cash Flow on an annual basis.
DataField: anl4_bac1actualqfv110_item
DataFieldDescription: Financial item
DataField: anl4_qfd1_az_cfps_median
DataFieldDescription: Cash Flow Per Share - Median value among forecasts
DataField: guidance_estimate_value
DataFieldDescription: Estimated value for basic annual financial guidance
DataField: anl4_fcf_low
DataFieldDescription: Free Cash Flow - The lowest estimation
DataField: anl4_gric_flag
DataFieldDescription: Gross income - forecast type (revision/new/...)
DataField: dividend_estimate_minimum
DataFieldDescription: Dividend per share - The lowest value among forecasts - D1
DataField: min_total_assets_guidance
DataFieldDescription: Minimum guidance value for Total Assets
DataField: anl4_ady_low
DataFieldDescription: The lowest estimation
DataField: shareholders_equity_max_guidance
DataFieldDescription: The maximum guidance value for Shareholder's Equity on an annual basis.
DataField: anl4_flag_erbfintax
DataFieldDescription: Earnings before interest and taxes - forecast type (revision/new/...)
DataField: cashflow_per_share_min_guidance_quarterly
DataFieldDescription: Minimum guidance value for Cash Flow Per Share
DataField: rel_num_part
DataFieldDescription: number of the instrument's partners
DataField: pv13_hierarchy_min52_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f4_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_sector_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f1_513_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min10_all_sector
DataFieldDescription: grouping fields
DataField: rel_ret_cust
DataFieldDescription: averaged one-day-return of the instrument's customers
DataField: rel_ret_all
DataFieldDescription: Averaged one-day return of the companies whose product overlapped with the instrument
DataField: pv13_revere_company_total
DataFieldDescription: Total number of companies in the sector
DataField: pv13_3l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_sector_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min10_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_reportperiodend
DataFieldDescription: Stated end date for the report
DataField: pv13_rha2_min10_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min50_f3_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_2k_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min20_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_liquid_min5_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_index_cap
DataFieldDescription: Company market capitalization
DataField: pv13_6l_scibr
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_pureplay_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min10_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_di_6l
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min30_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f3_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min52_2k_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min5_1000_513_sector
DataFieldDescription: grouping fields
DataField: implied_volatility_put_10
DataFieldDescription: At-the-money option-implied volatility for Put Option for 10 days
DataField: parkinson_volatility_30
DataFieldDescription: Parkinson model's historical volatility over 30 days
DataField: implied_volatility_put_180
DataFieldDescription: At-the-money option-implied volatility for put option for 180 days
DataField: implied_volatility_put_270
DataFieldDescription: At-the-money option-implied volatility for Put Option for 270 days
DataField: parkinson_volatility_90
DataFieldDescription: Parkinson model's historical volatility over 90 days
DataField: implied_volatility_call_60
DataFieldDescription: At-the-money option-implied volatility for call Option for 60 days
DataField: parkinson_volatility_150
DataFieldDescription: Parkinson model's historical volatility over 150 days
DataField: implied_volatility_mean_skew_720
DataFieldDescription: At-the-money option-implied volatility mean skew for 720 days
DataField: implied_volatility_put_60
DataFieldDescription: At-the-money option-implied volatility for Put Option for 60 days
DataField: parkinson_volatility_120
DataFieldDescription: Parkinson model's historical volatility over 120 days
DataField: parkinson_volatility_180
DataFieldDescription: Parkinson model's historical volatility over 180 days
DataField: implied_volatility_call_270
DataFieldDescription: At-the-money option-implied volatility for call Option for 270 days
DataField: implied_volatility_call_20
DataFieldDescription: At-the-money option-implied volatility for call Option for 20 days
DataField: implied_volatility_mean_720
DataFieldDescription: At-the-money option-implied volatility mean for 720 days
DataField: implied_volatility_mean_30
DataFieldDescription: At-the-money option-implied volatility mean for 30 days
DataField: implied_volatility_mean_skew_30
DataFieldDescription: At-the-money option-implied volatility mean skew for 30 days
DataField: implied_volatility_mean_360
DataFieldDescription: At-the-money option-implied volatility mean for 360 days
DataField: implied_volatility_call_720
DataFieldDescription: At-the-money option-implied volatility for call Option for 720 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: implied_volatility_mean_10
DataFieldDescription: At-the-money option-implied volatility mean for 10 days
DataField: implied_volatility_mean_20
DataFieldDescription: At-the-money option-implied volatility mean for 20 days
DataField: implied_volatility_put_120
DataFieldDescription: At-the-money option-implied volatility for Put Option for 120 days
DataField: historical_volatility_90
DataFieldDescription: Close-to-close Historical volatility over 90 days
DataField: implied_volatility_mean_1080
DataFieldDescription: At-the-money option-implied volatility mean for 3 years
DataField: implied_volatility_mean_skew_90
DataFieldDescription: At-the-money option-implied volatility mean skew for 90 days
DataField: parkinson_volatility_20
DataFieldDescription: Parkinson model's historical volatility over 20 days
DataField: historical_volatility_60
DataFieldDescription: Close-to-close Historical volatility over 60 days
DataField: implied_volatility_mean_150
DataFieldDescription: At-the-money option-implied volatility mean for 150 days
DataField: implied_volatility_mean_120
DataFieldDescription: At-the-money option-implied volatility mean for 120 days
DataField: nws12_afterhsz_prevwap
DataFieldDescription: Pre session volume weighted average price
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_afterhsz_2s
DataFieldDescription: Number of minutes that elapsed before price went down 2 percentage points
DataField: nws12_mainz_result_vs_index
DataFieldDescription: ((EODClose - TONLast) / TONLast) - ((SPYClose - SPYLast) / SPYLast)
DataField: nws12_mainz_sl
DataFieldDescription: Whether a long or short position would have been more advantageous: If (EODHigh - Last) > (Last - EODLow) Then LS = 1; If (EODHigh - Last) = (Last - EODLow) Then LS = 0; If (EODHigh - Last) < (Last - EODLow) Then LS = -1.
DataField: nws12_mainz_02p
DataFieldDescription: The minimum of L or S above for 20-minute bucket
DataField: news_mins_4_pct_up
DataFieldDescription: Number of minutes that elapsed before price went up 4 percentage points
DataField: nws12_afterhsz_57s
DataFieldDescription: Number of minutes that elapsed before price went down 7.5 percentage points
DataField: nws12_allz_newssess
DataFieldDescription: Index of session in which the news was reported
DataField: news_pct_30min
DataFieldDescription: The percent change in price in the first 30 minutes following the news release
DataField: news_mins_2_pct_up
DataFieldDescription: Number of minutes that elapsed before price went up 2 percentage points
DataField: nws12_afterhsz_01p
DataFieldDescription: The minimum of L or S above for 10 minute bucket
DataField: news_eod_vwap
DataFieldDescription: Volume weighted average price between the time of news and the end of the session
DataField: nws12_afterhsz_1p
DataFieldDescription: The minimum of L or S above for 1-minute bucket
DataField: nws12_prez_vol_ratio
DataFieldDescription: Curr_Vol / Mov_Vol
DataField: nws12_prez_rangestddev
DataFieldDescription: (RangeAmt-AvgRange)/RangeStdDev, where AvgRange is the average of the daily range, and RangeStdDev is one standard deviation for the daily range, both for 30 calendar days
DataField: nws12_mainz_epsactual
DataFieldDescription: The actual Earnings Per Share value that was conveyed by the news release
DataField: nws12_prez_30_seconds
DataFieldDescription: The percent change in price in the 30 seconds following the news release
DataField: nws12_mainz_tonlast
DataFieldDescription: Price at the time of news
DataField: nws12_prez_2p
DataFieldDescription: The minimum of L or S above for 2-minute bucket
DataField: nws12_afterhsz_div_y
DataFieldDescription: Annual yield
DataField: nws12_mainz_01s
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
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_highexcstddev
DataFieldDescription: (EODHigh - TONLast)/StdDev, where StdDev is one standard deviation for the close price for 30 calendar days
DataField: nws12_afterhsz_57p
DataFieldDescription: The minimum of L or S above for 7.5-minute bucket
DataField: news_ton_high
DataFieldDescription: Highest price reached during the session before the time of news
DataField: nws12_mainz_provider
DataFieldDescription: index of name of the news provider
DataField: nws12_afterhsz_prevday
DataFieldDescription: Percent change between the previous day's open and close
DataField: nws12_mainz_prevwap
DataFieldDescription: Pre session volume weighted average price
DataField: nws12_afterhsz_120_min
DataFieldDescription: The percent change in price in the first 120 minutes following the news release
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: rp_nip_price
DataFieldDescription: News impact projection of stock price news
DataField: rp_ess_product
DataFieldDescription: Event sentiment score of product and service-related news
DataField: rp_ess_revenue
DataFieldDescription: Event sentiment score of revenue news
DataField: rp_css_revenue
DataFieldDescription: Composite sentiment score of revenue news
DataField: nws18_qep
DataFieldDescription: News sentiment based on positive and negative words on global equity
DataField: rp_css_business
DataFieldDescription: Composite sentiment score of business-related news
DataField: rp_nip_partner
DataFieldDescription: News impact projection of partnership news
DataField: rp_nip_credit
DataFieldDescription: News impact projection of credit news
DataField: rp_css_ptg
DataFieldDescription: Composite sentiment score of price target news
DataField: nws18_ssc
DataFieldDescription: Sentiment of the news calculated using multiple techniques
DataField: rp_ess_technical
DataFieldDescription: Event sentiment score based on technical analysis
DataField: rp_nip_labor
DataFieldDescription: News impact projection of labor issues news
DataField: rp_ess_dividends
DataFieldDescription: Event sentiment score of dividends news
DataField: rp_nip_insider
DataFieldDescription: News impact projection of insider trading news
DataField: rp_nip_society
DataFieldDescription: News impact projection of society-related news
DataField: rp_nip_equity
DataFieldDescription: News impact projection of equity action news
DataField: rp_css_labor
DataFieldDescription: Composite sentiment score of labor issues news
DataField: nws18_bee
DataFieldDescription: News sentiment specializing in growth of earnings
DataField: rp_css_ratings
DataFieldDescription: Composite sentiment score of analyst ratings-related news
DataField: rp_nip_business
DataFieldDescription: News impact projection of business-related news
DataField: rp_css_inverstor
DataFieldDescription: Composite sentiment score of investor relations news
DataField: rp_nip_assets
DataFieldDescription: News impact projection of assets news
DataField: nws18_sse
DataFieldDescription: Sentiment of phrases impacting the company
DataField: rp_css_assets
DataFieldDescription: Composite sentiment score of assets news
DataField: rp_css_equity
DataFieldDescription: Composite sentiment score of equity action news
DataField: rp_nip_revenue
DataFieldDescription: News impact projection of revenue news
DataField: rp_ess_insider
DataFieldDescription: Event sentiment score of insider trading news
DataField: rp_nip_technical
DataFieldDescription: News impact projection based on technical analysis
DataField: rp_ess_business
DataFieldDescription: Event sentiment score of business-related news
DataField: rp_nip_legal
DataFieldDescription: News impact projection of legal news
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_propplteqmuflmeqmt
DataFieldDescription: PPE, Equipment, Useful Life, Minimum
DataField: fnd2_q_atdlsecexfcepsastkos
DataFieldDescription: Antidilutive Shares Excluded From Earnings Per Share Amount, Stock Options
DataField: fn_allocated_share_based_compensation_expense_a
DataFieldDescription: Represents the expense recognized during the period arising from equity-based compensation arrangements (for example, shares of stock, unit, stock options or other equity instruments) with employees, directors and certain consultants qualifying for treatment as employees.
DataField: fn_derivative_fair_value_of_derivative_liability_a
DataFieldDescription: Fair value, before effects of master netting arrangements, of a financial liability or contract with one or more underlyings, notional amount or payment provision or both, and the contract can be net settled by means outside the contract or delivery of an asset. Includes liabilities elected not to be offset. Excludes liabilities not subject to a master netting arrangement.
DataField: fn_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_gsles1xtinguishmentofd
DataFieldDescription: Difference between the fair value of payments made and the carrying amount of debt which is extinguished prior to maturity.
DataField: fn_oth_comp_grants_weighted_avg_grant_date_fair_value_a
DataFieldDescription: Annual Share-Based Compensation Equity Instruments Other Than Options Nonvested Weighted Average Grant Date Fair Value
DataField: fnd2_a_sbcpnargmsawpfipwerpr
DataFieldDescription: Weighted average price of options that were either forfeited or expired.
DataField: fn_op_lease_min_pay_due_in_4y_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 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: 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: fnd2_oprlsfmpdcurr
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 next 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_currfrtxexp
DataFieldDescription: Income Tax Expense, Current - Foreign
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: fnd2_dfdfeditxexp
DataFieldDescription: Income Tax Expense, Deferred - Federal
DataField: fnd2_dbplanepdfbnfp5ytherea
DataFieldDescription: Amount of benefits from a defined benefit plan expected to be paid in the 5 fiscal years 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: fnd2_a_sbcpnargmsptawervl
DataFieldDescription: Amount of accumulated difference between fair value of underlying shares on dates of exercise and exercise price on options exercised (or share units converted) into shares.
DataField: fn_proceeds_from_lt_debt_q
DataFieldDescription: Proceeds From Issuance Of Debt, Long Term
DataField: fnd2_a_eplsbvdcpcstnrgsbaoo
DataFieldDescription: Unrecognized cost of unvested other share-based compensation awards.
DataField: fnd2_propplteqmuflmamfrt
DataFieldDescription: PPE, Furniture, Useful Life, Maximum
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: fn_comp_options_out_number_q
DataFieldDescription: Number of options outstanding, including both vested and non-vested options.
DataField: fn_oth_income_loss_net_of_tax_a
DataFieldDescription: Amount after tax and reclassification adjustments of other comprehensive income (loss).
DataField: fnd2_a_bnsacqproformarvn
DataFieldDescription: The pro forma revenue for a period as if the business combination or combinations had been completed at the beginning of the period.
DataField: fnd2_a_flintasamt1expnext12m
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 next 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_def_income_tax_expense_a
DataFieldDescription: Income Tax Expense, Deferred
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_proceeds_from_issuance_of_debt_q
DataFieldDescription: The cash inflow during the period from additional borrowings in aggregate debt. Includes proceeds from short-term and long-term debt.
DataField: fnd2_a_sbcpnargmpmtwstgm
DataFieldDescription: As of the balance sheet date, the number of shares into which fully vested and expected to vest stock options outstanding can be converted under the option plan.
DataField: fn_goodwill_acquired_during_period_q
DataFieldDescription: Amount of increase in asset representing future economic benefits arising from other assets acquired in a business combination that are not individually identified and separately recognized resulting from a business combination.
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 =======================================