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: pcr_vol_1080
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 1080 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: 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: 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: pcr_oi_120
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 120 days in the future.
DataField: pcr_vol_180
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 180 days in the future.
DataField: pcr_oi_20
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 20 days in the future.
DataField: put_breakeven_180
DataFieldDescription: Price at which a stock's put options with expiration 180 days in the future break even based on its recent bid/ask mean.
DataField: pcr_vol_270
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 270 days in the future.
DataField: pcr_oi_60
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 60 days in the future.
DataField: option_breakeven_150
DataFieldDescription: Price at which a stock's options with expiration 150 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_1080
DataFieldDescription: Forward price at 1080 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: 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: 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_270
DataFieldDescription: Price at which a stock's options with expiration 270 days in the future break even based on its recent bid/ask mean.
DataField: 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: call_breakeven_360
DataFieldDescription: Price at which a stock's call options with expiration 360 days in the future break even based on its recent bid/ask mean.
DataField: call_breakeven_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: 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: 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: 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_60
DataFieldDescription: Forward price at 60 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: pcr_vol_30
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 30 days in the future.
DataField: forward_price_150
DataFieldDescription: Forward price at 150 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: put_breakeven_90
DataFieldDescription: Price at which a stock's put options with expiration 90 days in the future break even based on its recent bid/ask mean.
DataField: 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: pcr_vol_90
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 90 days in the future.
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: 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: pcr_vol_all
DataFieldDescription: Ratio of put volume to call volume for all maturities on stock's options.
DataField: fnd6_newqv1300_tstknq
DataFieldDescription: Treasury Stock - Number of Common Shares
DataField: fnd6_newqeventv110_esopnrq
DataFieldDescription: Preferred ESOP Obligation - Non-Redeemable
DataField: fnd6_dd3
DataFieldDescription: Debt Due in 3rd Year
DataField: fnd6_newa2v1300_mib
DataFieldDescription: Minority Interest (Balance Sheet)
DataField: fnd6_txtubposdec
DataFieldDescription: Decrease - Current Tax Positions
DataField: fnd6_cptnewqv1300_oeps12
DataFieldDescription: Earnings Per Share from Operations - 12 Months Moving
DataField: fnd6_ocaxs
DataFieldDescription: Other Costs and Expenses
DataField: fnd6_sppiv
DataFieldDescription: Sale of Property, Plant and Equipment and Investments - Gain (Loss)
DataField: fnd6_newqeventv110_aociotherq
DataFieldDescription: Accum Other Comp Inc - Other Adjustments
DataField: fnd6_newqv1300_lnoq
DataFieldDescription: Liabilities Netting & Other Adjustments
DataField: fnd6_newqeventv110_aqpq
DataFieldDescription: Acquisition/Merger Pretax
DataField: fnd6_mfma1_at
DataFieldDescription: Assets - Total
DataField: interest_expense
DataFieldDescription: Interest and Related Expense - Total
DataField: fnd6_newqeventv110_ppentq
DataFieldDescription: Property Plant and Equipment - Total (Net)
DataField: fnd6_newqeventv110_pnc12
DataFieldDescription: Pension Core Adjustment - 12mm
DataField: fnd6_newqeventv110_pncwippq
DataFieldDescription: Core Pension w/o Interest Adjustment Pretax Preliminary
DataField: fnd6_eventv110_optdrq
DataFieldDescription: Dividend Rate - Assumption (%)
DataField: fnd6_cptnewqeventv110_actq
DataFieldDescription: Current Assets - Total
DataField: fnd6_city
DataFieldDescription: the city where a company's corporate headquarters or home office is located
DataField: fnd6_newqeventv110_glaq
DataFieldDescription: Gain/Loss After-Tax
DataField: fnd6_itci
DataFieldDescription: Investment Tax Credit (Income Account)
DataField: fnd6_cshtrq
DataFieldDescription: Common Shares Traded - Quarter
DataField: fnd6_idit
DataFieldDescription: Interest and Related Income - Total
DataField: fnd6_recco
DataFieldDescription: Receivables - Current - Other
DataField: fnd6_eventv110_nrtxtdq
DataFieldDescription: Nonrecurring Income Taxes Diluted EPS Effect
DataField: fnd6_newa2v1300_txt
DataFieldDescription: Income Taxes - Total
DataField: fnd6_divd
DataFieldDescription: Cash Dividends - Daily
DataField: fnd6_txtubposinc
DataFieldDescription: Increase - Current Tax Positions
DataField: fnd6_dltis
DataFieldDescription: Long-Term Debt - Issuance
DataField: fnd6_spce
DataFieldDescription: S&P Core Earnings
DataField: scl12_alltype_buzzvec
DataFieldDescription: sentiment volume
DataField: scl12_alltype_sentvec
DataFieldDescription: sentiment
DataField: scl12_alltype_typevec
DataFieldDescription: instrument type index
DataField: scl12_buzz
DataFieldDescription: relative sentiment volume
DataField: scl12_buzz_fast_d1
DataFieldDescription: relative sentiment volume
DataField: scl12_buzzvec
DataFieldDescription: sentiment volume
DataField: scl12_sentiment
DataFieldDescription: sentiment
DataField: scl12_sentiment_fast_d1
DataFieldDescription: sentiment
DataField: scl12_sentvec
DataFieldDescription: sentiment
DataField: scl12_typevec
DataFieldDescription: instrument type index
DataField: snt_buzz
DataFieldDescription: negative relative sentiment volume, fill nan with 0
DataField: snt_buzz_bfl
DataFieldDescription: negative relative sentiment volume, fill nan with 1
DataField: snt_buzz_bfl_fast_d1
DataFieldDescription: negative relative sentiment volume, fill nan with 1
DataField: snt_buzz_fast_d1
DataFieldDescription: negative relative sentiment volume, fill nan with 0
DataField: snt_buzz_ret
DataFieldDescription: negative return of relative sentiment volume
DataField: snt_buzz_ret_fast_d1
DataFieldDescription: negative return of relative sentiment volume
DataField: snt_value
DataFieldDescription: negative sentiment, fill nan with 0
DataField: snt_value_fast_d1
DataFieldDescription: negative sentiment, fill nan with 0
DataField: analyst_revision_rank_derivative
DataFieldDescription: Change in ranking for analyst revisions and momentum compared to previous period.
DataField: cashflow_efficiency_rank_derivative
DataFieldDescription: Change in ranking for cash flow generation and profitability compared to previous period.
DataField: composite_factor_score_derivative
DataFieldDescription: Change in overall composite factor score from the prior period.
DataField: earnings_certainty_rank_derivative
DataFieldDescription: Change in ranking for earnings sustainability and certainty compared to previous period.
DataField: fscore_bfl_growth
DataFieldDescription: The purpose of this metric is to qualify the expected MT growth potential of the stock.
DataField: fscore_bfl_momentum
DataFieldDescription: The purpose of this metric is to identify stocks which are currently undergoing either up or downward analyst revisions.
DataField: fscore_bfl_profitability
DataFieldDescription: The purpose of this metric is to rank stock based on their ability to generate cash flows.
DataField: fscore_bfl_quality
DataFieldDescription: The purpose of this metric is to measure both the sustainability and certainty of earnings.
DataField: fscore_bfl_surface
DataFieldDescription: The static score. An index between 0 & 100 is applied for each stock and each composite factor - The first ranking is a pentagon surface-based score. The larger the surface, the higher the rank.
DataField: fscore_bfl_surface_accel
DataFieldDescription: The derivative score. In a second step, we calculate the derivative of this score (ie: Is the surface of the pentagon increasing or decreasing from the previous month?).
DataField: fscore_bfl_total
DataFieldDescription: The final score M-Score is a weighted average of both the Pentagon surface score and the Pentagon acceleration score.
DataField: fscore_bfl_value
DataFieldDescription: The purpose of this metric is to see if the stock is under or overpriced given several well known valuation standards.
DataField: fscore_growth
DataFieldDescription: The purpose of this metric is to qualify the expected MT growth potential of the stock.
DataField: fscore_momentum
DataFieldDescription: The purpose of this metric is to identify stocks which are currently undergoing either up or downward analyst revisions.
DataField: fscore_profitability
DataFieldDescription: The purpose of this metric is to rank stock based on their ability to generate cash flows.
DataField: fscore_quality
DataFieldDescription: The purpose of this metric is to measure both the sustainability and certainty of earnings.
DataField: fscore_surface
DataFieldDescription: The static score. An index between 0 & 100 is applied for each stock and each composite factor - The first ranking is a pentagon surface-based score. The larger the surface, the higher the rank.
DataField: fscore_surface_accel
DataFieldDescription: The derivative score. In a second step, we calculate the derivative of this score (ie: Is the surface of the pentagon increasing or decreasing from the previous month?).
DataField: fscore_total
DataFieldDescription: The final score M-Score is a weighted average of both the Pentagon surface score and the Pentagon acceleration score.
DataField: fscore_value
DataFieldDescription: The purpose of this metric is to see if the stock is under or overpriced given several well known valuation standards.
DataField: growth_potential_rank_derivative
DataFieldDescription: Change in ranking for medium-term growth potential compared to previous period.
DataField: multi_factor_acceleration_score_derivative
DataFieldDescription: Change in the acceleration of multi-factor score compared to previous period.
DataField: multi_factor_static_score_derivative
DataFieldDescription: Change in static multi-factor score compared to previous period.
DataField: relative_valuation_rank_derivative
DataFieldDescription: Change in ranking for valuation metrics compared to previous period.
DataField: snt_social_value
DataFieldDescription: Z score of sentiment
DataField: snt_social_volume
DataFieldDescription: Normalized tweet volume
DataField: beta_last_30_days_spy
DataFieldDescription: Beta to SPY in 30 Days
DataField: beta_last_360_days_spy
DataFieldDescription: Beta to SPY in 360 Days
DataField: beta_last_60_days_spy
DataFieldDescription: Beta to SPY in 60 Days
DataField: beta_last_90_days_spy
DataFieldDescription: Beta to SPY in 90 Days
DataField: correlation_last_30_days_spy
DataFieldDescription: Correlation to SPY in 30 Days
DataField: correlation_last_360_days_spy
DataFieldDescription: Correlation to SPY in 360 Days
DataField: correlation_last_60_days_spy
DataFieldDescription: Correlation to SPY in 60 Days
DataField: correlation_last_90_days_spy
DataFieldDescription: Correlation to SPY in 90 Days
DataField: systematic_risk_last_30_days
DataFieldDescription: Systematic Risk Last 30 Days
DataField: systematic_risk_last_360_days
DataFieldDescription: Systematic Risk Last 360 Days
DataField: systematic_risk_last_60_days
DataFieldDescription: Systematic Risk Last 60 Days
DataField: systematic_risk_last_90_days
DataFieldDescription: Systematic Risk Last 90 Days
DataField: unsystematic_risk_last_30_days
DataFieldDescription: Unsystematic Risk Last 30 Days - Relative to SPY
DataField: unsystematic_risk_last_360_days
DataFieldDescription: Unsystematic Risk Last 360 Days - Relative to SPY
DataField: unsystematic_risk_last_60_days
DataFieldDescription: Unsystematic Risk Last 60 Days - Relative to SPY
DataField: unsystematic_risk_last_90_days
DataFieldDescription: Unsystematic Risk Last 90 Days - Relative to SPY
DataField: min_share_count_guidance
DataFieldDescription: Minimum guidance for shares on an annual basis
DataField: book_value_per_share_min_guidance_qtr
DataFieldDescription: Book value per share - minimum guidance value
DataField: anl4_ebitda_std
DataFieldDescription: Earnings before interest, taxes, depreciation, and amortization - standard deviation of estimations
DataField: anl4_ptpr_median
DataFieldDescription: Reported pretax income - Median of estimations
DataField: anl4_netprofita_low
DataFieldDescription: Adjusted net income - the lowest estimation
DataField: anl4_qfv4_actual
DataFieldDescription: Announced financial data
DataField: actuals_value_currency_code
DataFieldDescription: Pricing Currency where the security trades
DataField: sales_estimate_average_quarterly
DataFieldDescription: Sales - mean of estimations
DataField: anl4_epsa_flag
DataFieldDescription: Earnings per share adjusted by excluding extraordinary items and stock option expenses - forecast type (revision/new/...)
DataField: earnings_per_share_nongaap_value
DataFieldDescription: Non-GAAP Earnings Per Share - Actual Value
DataField: max_adjusted_net_income_guidance
DataFieldDescription: The maximum guidance value for Adjusted net income.
DataField: anl4_medianepsbfam
DataFieldDescription: Earnings before interest, taxes, depreciation and amortization - median of estimations
DataField: actual_eps_value_quarterly
DataFieldDescription: Earnings Per Share (Income Statement/Per Share) (Actual)
DataField: cashflow_per_share_max_guidance_quarterly
DataFieldDescription: The maximum guidance value for Cash Flow Per Share.
DataField: anl4_eaz2lqfv110_estvalue
DataFieldDescription: Estimation value
DataField: dividend_estimate_median_value
DataFieldDescription: Dividend per share - median of estimations
DataField: anl4_afv4_div_median
DataFieldDescription: Dividend per share - Median value among forecasts
DataField: anl4_ptp_high
DataFieldDescription: Pretax income - the highest estimation
DataField: earnings_per_share_reported_value
DataFieldDescription: Reported Earnings Per Share - Actual Value
DataField: min_gross_income_guidance_2
DataFieldDescription: The minimum guidance for Gross Income on an annual basis.
DataField: min_free_cash_flow_guidance
DataFieldDescription: The minimum guidance value for Free Cash Flow on an annual basis.
DataField: anl4_tbvps_number
DataFieldDescription: Tangible Book Value per Share - number of estimations
DataField: net_profit_adjusted_value
DataFieldDescription: Adjusted net income- announced financial value
DataField: anl4_ads1detailqfv110_prevval
DataFieldDescription: The previous estimation of financial item
DataField: anl4_cfo_mean
DataFieldDescription: Cash Flow From Operations - mean of estimations
DataField: guidance_previous_estimate_value_qtr
DataFieldDescription: The previous estimation of finanicial item
DataField: anl4_netprofita_median
DataFieldDescription: Adjusted net income - median of estimations
DataField: reporting_currency_code_9
DataFieldDescription: Home currency of instrument
DataField: anl4_cfi_median
DataFieldDescription: Cash Flow From Investing - median of estimations
DataField: anl4_netdebt_number
DataFieldDescription: Net debt - Number of estimations
DataField: pv13_h2_min2_1k_sector
DataFieldDescription: Grouping fields for top 1000
DataField: pv13_hierarchy_min51_f4_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min30_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min10_513_sector
DataFieldDescription: grouping fields
DataField: rel_ret_all
DataFieldDescription: Averaged one-day return of the companies whose product overlapped with the instrument
DataField: pv13_hierarchy_min52_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min51_f3_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_index_cap
DataFieldDescription: Company market capitalization
DataField: pv13_hierarchy_min10_top3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_reportperiodlen
DataFieldDescription: The number of units which the report covers prior to the stated end date
DataField: pv13_hierarchy_min100_corr21_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_reporttype
DataFieldDescription: Type of report
DataField: pv13_revere_company_total
DataFieldDescription: Total number of companies in the sector
DataField: pv13_hierarchy_min2_focused_pureplay_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min10_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min22_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f4_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min30_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f2_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min5_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f3_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_pureplay_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min20_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_new_3l_scibr
DataFieldDescription: grouping fields
DataField: pv13_ustomergraphrank_auth_rank
DataFieldDescription: the HITS authority score of customers
DataField: pv13_hierarchy_min2_focused_pureplay_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_2k_sector
DataFieldDescription: grouping fields
DataField: implied_volatility_put_60
DataFieldDescription: At-the-money option-implied volatility for Put Option for 60 days
DataField: implied_volatility_mean_skew_60
DataFieldDescription: At-the-money option-implied volatility mean skew for 60 days
DataField: implied_volatility_mean_skew_90
DataFieldDescription: At-the-money option-implied volatility mean skew for 90 days
DataField: implied_volatility_call_120
DataFieldDescription: At-the-money option-implied volatility for call Option for 120 days
DataField: implied_volatility_put_10
DataFieldDescription: At-the-money option-implied volatility for Put Option for 10 days
DataField: implied_volatility_mean_skew_10
DataFieldDescription: At-the-money option-implied volatility mean skew for 10 days
DataField: implied_volatility_mean_360
DataFieldDescription: At-the-money option-implied volatility mean for 360 days
DataField: historical_volatility_10
DataFieldDescription: Close-to-close Historical volatility over 10 days
DataField: parkinson_volatility_90
DataFieldDescription: Parkinson model's historical volatility over 90 days
DataField: historical_volatility_60
DataFieldDescription: Close-to-close Historical volatility over 60 days
DataField: implied_volatility_call_360
DataFieldDescription: At-the-money option-implied volatility for call Option for 360 days
DataField: historical_volatility_90
DataFieldDescription: Close-to-close Historical volatility over 90 days
DataField: historical_volatility_120
DataFieldDescription: Close-to-close Historical volatility over 120 days
DataField: implied_volatility_mean_150
DataFieldDescription: At-the-money option-implied volatility mean for 150 days
DataField: implied_volatility_mean_20
DataFieldDescription: At-the-money option-implied volatility mean for 20 days
DataField: parkinson_volatility_120
DataFieldDescription: Parkinson model's historical volatility over 120 days
DataField: implied_volatility_mean_1080
DataFieldDescription: At-the-money option-implied volatility mean for 3 years
DataField: implied_volatility_put_150
DataFieldDescription: At-the-money option-implied volatility for Put Option for 150 days
DataField: parkinson_volatility_60
DataFieldDescription: Parkinson model's historical volatility over 60 days
DataField: implied_volatility_call_20
DataFieldDescription: At-the-money option-implied volatility for call Option for 20 days
DataField: implied_volatility_mean_skew_30
DataFieldDescription: At-the-money option-implied volatility mean skew for 30 days
DataField: implied_volatility_mean_270
DataFieldDescription: At-the-money option-implied volatility mean for 270 days
DataField: implied_volatility_call_150
DataFieldDescription: At-the-money option-implied volatility for call Option for 150 days
DataField: implied_volatility_mean_skew_270
DataFieldDescription: At-the-money option-implied volatility mean skew for 270 days
DataField: implied_volatility_mean_30
DataFieldDescription: At-the-money option-implied volatility mean for 30 days
DataField: parkinson_volatility_150
DataFieldDescription: Parkinson model's historical volatility over 150 days
DataField: parkinson_volatility_180
DataFieldDescription: Parkinson model's historical volatility over 180 days
DataField: historical_volatility_150
DataFieldDescription: Close-to-close Historical volatility over 150 days
DataField: implied_volatility_put_90
DataFieldDescription: At-the-money option-implied volatility for Put Option for 90 days
DataField: implied_volatility_call_10
DataFieldDescription: At-the-money option-implied volatility for call Option for 10 days
DataField: news_pct_5_min
DataFieldDescription: The percent change in price in the first 5 minutes following the news release
DataField: nws12_mainz_02l
DataFieldDescription: Number of minutes that elapsed before price went up 20 percentage points
DataField: nws12_prez_57p
DataFieldDescription: The minimum of L or S above for 7.5-minute bucket
DataField: nws12_mainz_4s
DataFieldDescription: Number of minutes that elapsed before price went down 4 percentage points
DataField: nws12_prez_open_vol
DataFieldDescription: Main open volume
DataField: news_eod_vwap
DataFieldDescription: Volume weighted average price between the time of news and the end of the session
DataField: news_mins_20_chg
DataFieldDescription: The minimum of L or S above for 20-minute bucket
DataField: nws12_prez_4s
DataFieldDescription: Number of minutes that elapsed before price went down 4 percentage points
DataField: nws12_prez_57l
DataFieldDescription: Number of minutes that elapsed before price went up 7.5 percentage points
DataField: nws12_afterhsz_90_min
DataFieldDescription: The percent change in price in the first 90 minutes following the news release
DataField: nws12_afterhsz_5l
DataFieldDescription: Number of minutes that elapsed before price went up 5 percentage points
DataField: nws12_afterhsz_01p
DataFieldDescription: The minimum of L or S above for 10 minute bucket
DataField: news_mins_3_pct_up
DataFieldDescription: Number of minutes that elapsed before price went up 3 percentage points
DataField: nws12_afterhsz_tonlow
DataFieldDescription: Lowest price reached during the session before the time of the news
DataField: news_mins_10_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: nws12_mainz_rangeamt
DataFieldDescription: Session High Price - Session Low Price
DataField: nws12_afterhsz_57l
DataFieldDescription: Number of minutes that elapsed before price went up 7.5 percentage points
DataField: nws12_afterhsz_01l
DataFieldDescription: Number of minutes that elapsed before price went up 10 percentage points
DataField: nws12_mainz_prev_vol
DataFieldDescription: Previous day's session volume
DataField: news_pct_10min
DataFieldDescription: The percent change in price in the first 10 minutes following the news release
DataField: nws12_allz_reportsess
DataFieldDescription: Index of Session on which the spreadsheet is reporting
DataField: nws12_mainz_prevclose
DataFieldDescription: Previous trading day's close price
DataField: nws12_prez_curr_vol
DataFieldDescription: Current day's session volume
DataField: news_all_vwap
DataFieldDescription: Volume weighted average price of all sessions
DataField: nws12_mainz_mktcap
DataFieldDescription: Reported market capitalization for the calendar day of the session
DataField: nws12_prez_90_min
DataFieldDescription: The percent change in price in the first 90 minutes following the news release
DataField: nws12_prez_allvwap
DataFieldDescription: Volume weighted average price of all sessions
DataField: news_mins_7_5_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 7.5 percentage points
DataField: news_main_vwap
DataFieldDescription: Main session volume weighted average price
DataField: nws12_afterhsz_prev_vol
DataFieldDescription: Previous day's session volume
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: rp_ess_mna
DataFieldDescription: Event sentiment score of mergers and acquisitions-related news
DataField: rp_nip_revenue
DataFieldDescription: News impact projection of revenue news
DataField: rp_nip_price
DataFieldDescription: News impact projection of stock price news
DataField: rp_ess_technical
DataFieldDescription: Event sentiment score based on technical analysis
DataField: rp_nip_ratings
DataFieldDescription: News impact projection of analyst ratings-related news
DataField: rp_css_business
DataFieldDescription: Composite sentiment score of business-related news
DataField: rp_nip_earnings
DataFieldDescription: News impact projection of earnings news
DataField: rp_ess_assets
DataFieldDescription: Event sentiment score of assets news
DataField: rp_nip_insider
DataFieldDescription: News impact projection of insider trading news
DataField: rp_ess_equity
DataFieldDescription: Event sentiment score of equity action news
DataField: rp_ess_business
DataFieldDescription: Event sentiment score of business-related news
DataField: rp_nip_society
DataFieldDescription: News impact projection of society-related news
DataField: nws18_qcm
DataFieldDescription: News sentiment of relevant news with high confidence
DataField: rp_ess_price
DataFieldDescription: Event sentiment score of stock price news
DataField: rp_ess_ratings
DataFieldDescription: Event sentiment score of analyst ratings-related news
DataField: nws18_bee
DataFieldDescription: News sentiment specializing in growth of earnings
DataField: rp_ess_society
DataFieldDescription: Event sentiment score of society-related news
DataField: rp_css_assets
DataFieldDescription: Composite sentiment score of assets news
DataField: rp_ess_dividends
DataFieldDescription: Event sentiment score of dividends news
DataField: nws18_acb
DataFieldDescription: News sentiment specializing in corporate action announcements
DataField: rp_nip_assets
DataFieldDescription: News impact projection of assets news
DataField: rp_css_price
DataFieldDescription: Composite sentiment score of stock price news
DataField: rp_nip_technical
DataFieldDescription: News impact projection based on technical analysis
DataField: rp_ess_revenue
DataFieldDescription: Event sentiment score of revenue news
DataField: rp_ess_credit
DataFieldDescription: Event sentiment score of credit news
DataField: nws18_qmb
DataFieldDescription: News sentiment specializing in editorials on global markets
DataField: rp_nip_legal
DataFieldDescription: News impact projection of legal news
DataField: rp_ess_legal
DataFieldDescription: Event sentiment score of legal news
DataField: nws18_sse
DataFieldDescription: Sentiment of phrases impacting the company
DataField: rp_nip_credit_ratings
DataFieldDescription: News impact projection of credit ratings news
DataField: fn_prepaid_expense_a
DataFieldDescription: Carrying amount for an unclassified balance sheet date of expenditures made in advance of when the economic benefit of the cost will be realized, and which will be expensed in future periods with the passage of time or when a triggering event occurs. For a classified balance sheet, represents the noncurrent portion of prepaid expenses (the current portion has a separate concept).
DataField: fn_finite_lived_intangible_assets_gross_a
DataFieldDescription: Amount before amortization of assets, excluding financial assets and goodwill, lacking physical substance with a finite life.
DataField: fn_debt_instrument_interest_rate_stated_percentage_q
DataFieldDescription: Stated percentage of interest rate on debt
DataField: fn_comp_not_rec_q
DataFieldDescription: Unrecognized cost of unvested share-based compensation awards.
DataField: fn_assets_fair_val_a
DataFieldDescription: Asset Fair Value, Recurring, Total
DataField: fnd2_a_sbcpnargmsawpfipwerpr
DataFieldDescription: Weighted average price of options that were either forfeited or expired.
DataField: fn_oth_income_loss_available_for_sale_securities_adj_of_tax_a
DataFieldDescription: Amount after tax and reclassification adjustments, of appreciation (loss) in value of unsold available-for-sale securities. Excludes amounts related to other than temporary impairment (OTTI) loss.
DataField: fnd2_dbplanbnfpaid
DataFieldDescription: The amount of payments made for which participants are entitled under a pension plan, including pension benefits, death benefits, and benefits due on termination of employment. Also includes payments made under a postretirement benefit plan, including prescription drug benefits, health care benefits, life insurance benefits, and legal, educational and advisory services. This item represents a periodic decrease to the plan obligations and a decrease to plan assets.
DataField: fnd2_dfdfritxexp
DataFieldDescription: Income Tax Expense, Deferred - Foreign
DataField: fnd2_unrgtxbnfinregfcrps
DataFieldDescription: Amount of increase in unrecognized tax benefits resulting from tax positions that have been or will be taken in current period tax return.
DataField: fnd2_a_consinprogressg
DataFieldDescription: Amount of structure or a modification to a structure under construction. Includes recently completed structures or modifications to structures that have not been placed into service.
DataField: fn_comp_options_out_intrinsic_value_q
DataFieldDescription: The intrinsic value of a stock option is the amount by which the market value of the underlying stock exceeds the exercise price of the option.
DataField: fn_intangible_assets_accum_amort_q
DataFieldDescription: Accumulated amount of amortization of assets, excluding financial assets and goodwill, lacking physical substance with a finite life.
DataField: fnd2_a_ltrmdmrepoplinytwo
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 2nd fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: fnd2_currfedtxexp
DataFieldDescription: Income Tax Expense, Current - Federal
DataField: fnd2_ebitfr
DataFieldDescription: EBIT, Foreign
DataField: fn_business_acq_ppne_q
DataFieldDescription: Business Combination, Assumed Property Plant And Equipment
DataField: fn_payments_for_repurchase_of_common_stock_a
DataFieldDescription: Value reported on Cash Flow Statement. May include shares repurchased as part of a buyback plan, as well as shares purchased for employee compensation, etc.
DataField: fnd2_a_dbplanepdrtnplas
DataFieldDescription: An amount calculated as a basis for determining the extent of delayed recognition of the effects of changes in the fair value of assets. The expected return on plan assets is determined based on the expected long-term rate of return on plan assets and the market-related value of plan assets.
DataField: fnd2_q_flintasamt1expy5
DataFieldDescription: Amount of amortization expense for assets, excluding financial assets and goodwill, lacking physical substance with a finite life expected to be recognized during the 5th fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: fn_repurchased_shares_q
DataFieldDescription: Number of shares that have been repurchased during the period.
DataField: fnd2_a_gwllimrml
DataFieldDescription: Amount of loss from the write-down of an asset representing the future economic benefits arising from other assets acquired in a business combination that are not individually identified and separately recognized.
DataField: fnd2_q_flintasamt1expytwo
DataFieldDescription: Amount of amortization expense for assets, excluding financial assets and goodwill, lacking physical substance with a finite life expected to be recognized during the 2nd fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: 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_op_lease_min_pay_due_a
DataFieldDescription: Amount of required minimum rental payments for leases having an initial or remaining non-cancelable letter-terms in excess of 1 year.
DataField: fn_interest_payable_q
DataFieldDescription: Carrying value as of the balance sheet date of accrued interest payable on all forms of debt, including trade payables, that has been incurred and is unpaid. For classified balance sheets, used to reflect the current portion of the liabilities (due within 1 year or within the normal operating cycle if longer); for unclassified balance sheets, used to reflect the total liabilities (regardless of due date).
DataField: fnd2_a_eplsbvdcpcstnrgsbaoo
DataFieldDescription: Unrecognized cost of unvested other share-based compensation awards.
DataField: fn_proceeds_from_issuance_of_debt_a
DataFieldDescription: The cash inflow during the period from additional borrowings in aggregate debt. Includes proceeds from short-term and long-term debt.
DataField: fn_finite_lived_intangible_assets_net_q
DataFieldDescription: Finite Lived Intangible Assets, Net
DataField: fnd2_a_stkdrgprdvalnewissues
DataFieldDescription: Equity impact of the value of new stock issued during the period. Includes shares issued in an initial public offering or a secondary public offering.
DataField: 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 =======================================