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_180
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 180 days in the future.
DataField: option_breakeven_30
DataFieldDescription: Price at which a stock's options with expiration 30 days in the future break even based on its recent bid/ask mean.
DataField: 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_120
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 120 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_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_oi_1080
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 1080 days in the future.
DataField: 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: 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_10
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 10 days in the future.
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: 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: 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_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_vol_60
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 60 days in the future.
DataField: option_breakeven_20
DataFieldDescription: Price at which a stock's options with expiration 20 days in the future break even based on its recent bid/ask mean.
DataField: option_breakeven_60
DataFieldDescription: Price at which a stock's options with expiration 60 days in the future break even based on its recent bid/ask mean.
DataField: put_breakeven_150
DataFieldDescription: Price at which a stock's put options with expiration 150 days in the future break even based on its recent bid/ask mean.
DataField: 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: pcr_vol_20
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 20 days in the future.
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: option_breakeven_720
DataFieldDescription: Price at which a stock's options with expiration 720 days in the future break even based on its recent bid/ask mean.
DataField: forward_price_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_30
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 30 days in the future.
DataField: forward_price_90
DataFieldDescription: Forward price at 90 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: option_breakeven_1080
DataFieldDescription: Price at which a stock's options with expiration 1080 days in the future break even based on its recent bid/ask mean.
DataField: 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: pcr_vol_150
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 150 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: put_breakeven_20
DataFieldDescription: Price at which a stock's put options with expiration 20 days in the future break even based on its recent bid/ask mean.
DataField: fnd6_newqeventv110_pncwiepq
DataFieldDescription: Core Pension Without Interest Adjustment Basic EPS Effect Preliminary
DataField: fnd6_ivst
DataFieldDescription: Short-Term Investments - Total
DataField: fnd6_newqv1300_invrmq
DataFieldDescription: Inventory - Raw Materials
DataField: fnd6_newqv1300_tfvceq
DataFieldDescription: Total Fair Value Changes including Earnings
DataField: fnd6_newa2v1300_mii
DataFieldDescription: Noncontrolling Interest (Income Account)
DataField: fnd6_newqeventv110_glcedq
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) Diluted EPS
DataField: fnd6_npq
DataFieldDescription: Notes Payable
DataField: fnd6_newqeventv110_reunaq
DataFieldDescription: Unadjusted Retained Earnings
DataField: fnd6_newqeventv110_prcpepsq
DataFieldDescription: Core Post-Retirement Adjustment Basic EPS Effect Preliminary
DataField: fnd6_newqeventv110_xidoq
DataFieldDescription: Extraordinary Items and Discontinued Operations
DataField: fnd6_newa2v1300_oancf
DataFieldDescription: Operating Activities - Net Cash Flow
DataField: fnd6_newqeventv110_esoptq
DataFieldDescription: Preferred ESOP Obligation - Total
DataField: fnd6_mfma2_recch
DataFieldDescription: Accounts Receivable - Decrease (Increase)
DataField: fnd6_cptrank_gvkeymap
DataFieldDescription: technical code for a company, no need to use it for research
DataField: fnd6_newqv1300_reunaq
DataFieldDescription: Unadjusted Retained Earnings
DataField: fnd6_newqeventv110_piq
DataFieldDescription: Pretax Income
DataField: fnd6_cptnewqeventv110_oibdpq
DataFieldDescription: Operating Income Before Depreciation - Quarterly
DataField: fnd6_newqeventv110_miiq
DataFieldDescription: Noncontrolling Interest - Income Account
DataField: fnd6_newqv1300_aoq
DataFieldDescription: Assets - Other - Total
DataField: fnd6_ranks
DataFieldDescription: Ranking
DataField: fnd6_newqeventv110_xoptdqp
DataFieldDescription: Implied Option EPS Diluted Preliminary
DataField: fnd6_ceql
DataFieldDescription: Common Equity - Liquidation Value
DataField: fnd6_newqeventv110_aqpl1q
DataFieldDescription: Assets Level 1 (Quoted Prices)
DataField: fnd6_newqeventv110_seteps12
DataFieldDescription: Settlement (Litigation/Insurance) Basic EPS Effect 12MM
DataField: fnd6_eventv110_nrtxtepsq
DataFieldDescription: Nonrecurring Income Taxes Basic EPS Effect
DataField: fnd6_esubc
DataFieldDescription: Equity in Net Loss - Earnings
DataField: fnd6_msa
DataFieldDescription: Marketable Securities Adjustment
DataField: fnd6_newqv1300_ciderglq
DataFieldDescription: Comp Inc - Derivative Gains/Losses
DataField: ppent
DataFieldDescription: Property Plant and Equipment - Total (Net)
DataField: fnd6_dltp
DataFieldDescription: Long-Term Debt - Tied to Prime
DataField: scl12_alltype_buzzvec
DataFieldDescription: sentiment volume
DataField: scl12_alltype_sentvec
DataFieldDescription: sentiment
DataField: scl12_alltype_typevec
DataFieldDescription: instrument type index
DataField: scl12_buzz
DataFieldDescription: relative sentiment volume
DataField: scl12_buzz_fast_d1
DataFieldDescription: relative sentiment volume
DataField: scl12_buzzvec
DataFieldDescription: sentiment volume
DataField: scl12_sentiment
DataFieldDescription: sentiment
DataField: scl12_sentiment_fast_d1
DataFieldDescription: sentiment
DataField: scl12_sentvec
DataFieldDescription: sentiment
DataField: scl12_typevec
DataFieldDescription: instrument type index
DataField: snt_buzz
DataFieldDescription: negative relative sentiment volume, fill nan with 0
DataField: snt_buzz_bfl
DataFieldDescription: negative relative sentiment volume, fill nan with 1
DataField: snt_buzz_bfl_fast_d1
DataFieldDescription: negative relative sentiment volume, fill nan with 1
DataField: snt_buzz_fast_d1
DataFieldDescription: negative relative sentiment volume, fill nan with 0
DataField: snt_buzz_ret
DataFieldDescription: negative return of relative sentiment volume
DataField: snt_buzz_ret_fast_d1
DataFieldDescription: negative return of relative sentiment volume
DataField: snt_value
DataFieldDescription: negative sentiment, fill nan with 0
DataField: snt_value_fast_d1
DataFieldDescription: negative sentiment, fill nan with 0
DataField: analyst_revision_rank_derivative
DataFieldDescription: Change in ranking for analyst revisions and momentum compared to previous period.
DataField: cashflow_efficiency_rank_derivative
DataFieldDescription: Change in ranking for cash flow generation and profitability compared to previous period.
DataField: composite_factor_score_derivative
DataFieldDescription: Change in overall composite factor score from the prior period.
DataField: earnings_certainty_rank_derivative
DataFieldDescription: Change in ranking for earnings sustainability and certainty compared to previous period.
DataField: fscore_bfl_growth
DataFieldDescription: The purpose of this metric is to qualify the expected MT growth potential of the stock.
DataField: fscore_bfl_momentum
DataFieldDescription: The purpose of this metric is to identify stocks which are currently undergoing either up or downward analyst revisions.
DataField: fscore_bfl_profitability
DataFieldDescription: The purpose of this metric is to rank stock based on their ability to generate cash flows.
DataField: fscore_bfl_quality
DataFieldDescription: The purpose of this metric is to measure both the sustainability and certainty of earnings.
DataField: fscore_bfl_surface
DataFieldDescription: The static score. An index between 0 & 100 is applied for each stock and each composite factor - The first ranking is a pentagon surface-based score. The larger the surface, the higher the rank.
DataField: fscore_bfl_surface_accel
DataFieldDescription: The derivative score. In a second step, we calculate the derivative of this score (ie: Is the surface of the pentagon increasing or decreasing from the previous month?).
DataField: fscore_bfl_total
DataFieldDescription: The final score M-Score is a weighted average of both the Pentagon surface score and the Pentagon acceleration score.
DataField: fscore_bfl_value
DataFieldDescription: The purpose of this metric is to see if the stock is under or overpriced given several well known valuation standards.
DataField: fscore_growth
DataFieldDescription: The purpose of this metric is to qualify the expected MT growth potential of the stock.
DataField: fscore_momentum
DataFieldDescription: The purpose of this metric is to identify stocks which are currently undergoing either up or downward analyst revisions.
DataField: fscore_profitability
DataFieldDescription: The purpose of this metric is to rank stock based on their ability to generate cash flows.
DataField: fscore_quality
DataFieldDescription: The purpose of this metric is to measure both the sustainability and certainty of earnings.
DataField: fscore_surface
DataFieldDescription: The static score. An index between 0 & 100 is applied for each stock and each composite factor - The first ranking is a pentagon surface-based score. The larger the surface, the higher the rank.
DataField: fscore_surface_accel
DataFieldDescription: The derivative score. In a second step, we calculate the derivative of this score (ie: Is the surface of the pentagon increasing or decreasing from the previous month?).
DataField: fscore_total
DataFieldDescription: The final score M-Score is a weighted average of both the Pentagon surface score and the Pentagon acceleration score.
DataField: fscore_value
DataFieldDescription: The purpose of this metric is to see if the stock is under or overpriced given several well known valuation standards.
DataField: growth_potential_rank_derivative
DataFieldDescription: Change in ranking for medium-term growth potential compared to previous period.
DataField: multi_factor_acceleration_score_derivative
DataFieldDescription: Change in the acceleration of multi-factor score compared to previous period.
DataField: multi_factor_static_score_derivative
DataFieldDescription: Change in static multi-factor score compared to previous period.
DataField: relative_valuation_rank_derivative
DataFieldDescription: Change in ranking for valuation metrics compared to previous period.
DataField: snt_social_value
DataFieldDescription: Z score of sentiment
DataField: snt_social_volume
DataFieldDescription: Normalized tweet volume
DataField: beta_last_30_days_spy
DataFieldDescription: Beta to SPY in 30 Days
DataField: beta_last_360_days_spy
DataFieldDescription: Beta to SPY in 360 Days
DataField: beta_last_60_days_spy
DataFieldDescription: Beta to SPY in 60 Days
DataField: beta_last_90_days_spy
DataFieldDescription: Beta to SPY in 90 Days
DataField: correlation_last_30_days_spy
DataFieldDescription: Correlation to SPY in 30 Days
DataField: correlation_last_360_days_spy
DataFieldDescription: Correlation to SPY in 360 Days
DataField: correlation_last_60_days_spy
DataFieldDescription: Correlation to SPY in 60 Days
DataField: correlation_last_90_days_spy
DataFieldDescription: Correlation to SPY in 90 Days
DataField: systematic_risk_last_30_days
DataFieldDescription: Systematic Risk Last 30 Days
DataField: systematic_risk_last_360_days
DataFieldDescription: Systematic Risk Last 360 Days
DataField: systematic_risk_last_60_days
DataFieldDescription: Systematic Risk Last 60 Days
DataField: systematic_risk_last_90_days
DataFieldDescription: Systematic Risk Last 90 Days
DataField: unsystematic_risk_last_30_days
DataFieldDescription: Unsystematic Risk Last 30 Days - Relative to SPY
DataField: unsystematic_risk_last_360_days
DataFieldDescription: Unsystematic Risk Last 360 Days - Relative to SPY
DataField: unsystematic_risk_last_60_days
DataFieldDescription: Unsystematic Risk Last 60 Days - Relative to SPY
DataField: unsystematic_risk_last_90_days
DataFieldDescription: Unsystematic Risk Last 90 Days - Relative to SPY
DataField: anl4_tot_gw_ft
DataFieldDescription: Total Goodwill - forecast type (revision/new/...)
DataField: anl4_bvps_value
DataFieldDescription: Book value per share - announced financial value
DataField: max_reported_pretax_income_guidance_2
DataFieldDescription: Reported Pretax income- maximum guidance value
DataField: anl4_dei3lqfv110_item
DataFieldDescription: Financial item
DataField: anl4_netprofita_low
DataFieldDescription: Adjusted net income - the lowest estimation
DataField: anl4_eaz1laf_person
DataFieldDescription: Broker Id
DataField: total_assets_reported_value
DataFieldDescription: Total Assets - actual value
DataField: anl4_fsactualafv4_actual
DataFieldDescription: Announced financial data
DataField: anl4_bac1detailafv110_item
DataFieldDescription: Financial item
DataField: financing_cashflow_reported_value
DataFieldDescription: Cash Flow From Financing - Value
DataField: anl4_fsguidanceafv4_item
DataFieldDescription: Financial item
DataField: dividend_estimate_standard_deviation
DataFieldDescription: Dividend per share - standard deviation of estimations
DataField: anl4_cff_value
DataFieldDescription: Cash Flow From Financing - announced financial value
DataField: max_operating_cashflow_guidance_2
DataFieldDescription: The maximum guidance value for Cash Flow from Operations on an annual basis.
DataField: sales_estimate_average
DataFieldDescription: Sales - mean of estimations with a delay of 1 quarter
DataField: anl4_eaz2lltv110_estvalue
DataFieldDescription: Estimation value
DataField: shareholders_equity_reported_value
DataFieldDescription: Shareholders' Equity - Total Value
DataField: anl4_bac1detaillt_item
DataFieldDescription: Financial item
DataField: anl4_basicdetaillt_estvalue
DataFieldDescription: Estimation value
DataField: previous_recommendation_value
DataFieldDescription: The previous estimation of financial item for recommendation
DataField: anl4_ebitda_flag
DataFieldDescription: Earnings before interest, taxes, depreciation and amortization - forecast type (revision/new/...)
DataField: highest_sales_estimate
DataFieldDescription: Sales - The highest estimation for the annual period
DataField: anl4_median_epsreported
DataFieldDescription: GAAP Earnings per share - median of estimations
DataField: anl4_ads1detailafv110_person
DataFieldDescription: Broker Id
DataField: cashflow_per_share_max_guidance
DataFieldDescription: The maximum guidance value for Cash Flow Per Share on an annual basis.
DataField: anl4_fsdtlestmtafv4_item
DataFieldDescription: Financial item
DataField: anl4_basicconafv110_high
DataFieldDescription: The highest estimation
DataField: anl4_guiafv4_est
DataFieldDescription: Estimation value
DataField: anl4_fcfps_low
DataFieldDescription: Free Cash Flow Per Share - the lowest estimation
DataField: min_financing_cashflow_guidance
DataFieldDescription: Minimum guidance value for Cash Flow From Financing
DataField: pv13_hierarchy_min50_f3_513_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min2_focused_pureplay_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_513_sector
DataFieldDescription: grouping fields
DataField: pv13_ompetitorgraphrank_hub_rank
DataFieldDescription: the HITS hub score of competitors
DataField: rel_num_all
DataFieldDescription: number of the companies whose product overlapped with the instrument
DataField: pv13_6l_scibr
DataFieldDescription: grouping fields
DataField: pv13_h_min30_3000_mapped_sector
DataFieldDescription: grouping fields
DataField: pv13_h_min51_f3_sector
DataFieldDescription: grouping fields
DataField: pv13_reportperiodend
DataFieldDescription: Stated end date for the report
DataField: pv13_hierarchy_min22_1000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_2k_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_min5_1000_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min5_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min52_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy23_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f4_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min20_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min51_f2_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy2_min2_1k_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_1000_513_sector
DataFieldDescription: grouping fields
DataField: primary_sector_focused_company_count
DataFieldDescription: Number of companies primarily focused in a given sector.
DataField: pv13_r2_liquid_min10_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min20_3k_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_513_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_country
DataFieldDescription: Country code
DataField: pv13_r2_min20_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_term
DataFieldDescription: Indicates when a sector is the terminal sector (i.e., no sub-sectors)
DataField: pv13_hierarchy_min51_f4_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min5_3000_513_sector
DataFieldDescription: grouping fields
DataField: historical_volatility_20
DataFieldDescription: Close-to-close Historical volatility over 20 days
DataField: implied_volatility_call_150
DataFieldDescription: At-the-money option-implied volatility for call Option for 150 days
DataField: implied_volatility_call_1080
DataFieldDescription: At-the-money option-implied volatility for call option for 1080 days
DataField: historical_volatility_150
DataFieldDescription: Close-to-close Historical volatility over 150 days
DataField: parkinson_volatility_30
DataFieldDescription: Parkinson model's historical volatility over 30 days
DataField: implied_volatility_mean_skew_20
DataFieldDescription: At-the-money option-implied volatility mean skew for 20 days
DataField: implied_volatility_mean_1080
DataFieldDescription: At-the-money option-implied volatility mean for 3 years
DataField: implied_volatility_put_720
DataFieldDescription: At-the-money option-implied volatility for Put Option for 720 days
DataField: implied_volatility_put_30
DataFieldDescription: At-the-money option-implied volatility for Put Option for 30 days
DataField: implied_volatility_call_60
DataFieldDescription: At-the-money option-implied volatility for call Option for 60 days
DataField: implied_volatility_mean_skew_30
DataFieldDescription: At-the-money option-implied volatility mean skew for 30 days
DataField: implied_volatility_call_720
DataFieldDescription: At-the-money option-implied volatility for call Option for 720 days
DataField: historical_volatility_90
DataFieldDescription: Close-to-close Historical volatility over 90 days
DataField: historical_volatility_10
DataFieldDescription: Close-to-close Historical volatility over 10 days
DataField: implied_volatility_mean_skew_90
DataFieldDescription: At-the-money option-implied volatility mean skew for 90 days
DataField: implied_volatility_mean_skew_60
DataFieldDescription: At-the-money option-implied volatility mean skew for 60 days
DataField: implied_volatility_mean_720
DataFieldDescription: At-the-money option-implied volatility mean for 720 days
DataField: parkinson_volatility_90
DataFieldDescription: Parkinson model's historical volatility over 90 days
DataField: implied_volatility_put_150
DataFieldDescription: At-the-money option-implied volatility for Put Option for 150 days
DataField: implied_volatility_mean_skew_120
DataFieldDescription: At-the-money option-implied volatility mean skew for 120 days
DataField: implied_volatility_mean_skew_360
DataFieldDescription: At-the-money option-implied volatility mean skew for 360 days
DataField: implied_volatility_call_180
DataFieldDescription: At-the-money option-implied volatility for call Option for 180 days
DataField: implied_volatility_put_60
DataFieldDescription: At-the-money option-implied volatility for Put Option for 60 days
DataField: parkinson_volatility_150
DataFieldDescription: Parkinson model's historical volatility over 150 days
DataField: implied_volatility_mean_10
DataFieldDescription: At-the-money option-implied volatility mean for 10 days
DataField: implied_volatility_mean_skew_10
DataFieldDescription: At-the-money option-implied volatility mean skew for 10 days
DataField: implied_volatility_mean_skew_180
DataFieldDescription: At-the-money option-implied volatility mean skew for 180 days
DataField: implied_volatility_put_180
DataFieldDescription: At-the-money option-implied volatility for put option for 180 days
DataField: implied_volatility_mean_360
DataFieldDescription: At-the-money option-implied volatility mean for 360 days
DataField: parkinson_volatility_180
DataFieldDescription: Parkinson model's historical volatility over 180 days
DataField: news_session_range
DataFieldDescription: Session High Price - Session Low Price
DataField: news_mins_20_chg
DataFieldDescription: The minimum of L or S above for 20-minute bucket
DataField: nws12_mainz_prevclose
DataFieldDescription: Previous trading day's close price
DataField: nws12_prez_opengap
DataFieldDescription: (DayOpen - PrevClose) / PrevClose.
DataField: nws12_prez_maxdown
DataFieldDescription: Percent change from the price at the time of the news to the after the news low
DataField: nws12_afterhsz_dayopen
DataFieldDescription: Price at the session open
DataField: nws12_mainz_57s
DataFieldDescription: Number of minutes that elapsed before price went down 7.5 percentage points
DataField: news_mins_10_pct_dn
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: news_indx_perf
DataFieldDescription: ((EODClose - TONLast) / TONLast) - ((SPYClose - SPYLast) / SPYLast)
DataField: nws12_afterhsz_lowexcstddev
DataFieldDescription: (TONLast - EODLow) / StdDev, where StdDev is one standard deviation for the close price for 30 calendar days
DataField: nws12_afterhsz_1_minute
DataFieldDescription: The percent change in price in the first minute following the news release
DataField: nws12_afterhsz_epsactual
DataFieldDescription: The actual Earnings Per Share value that was conveyed by the news release
DataField: nws12_prez_60_min
DataFieldDescription: The percent change in price in the first 60 minutes following the news release
DataField: nws12_afterhsz_41rta
DataFieldDescription: 14-day Average True Range
DataField: nws12_allz_reportsess
DataFieldDescription: Index of Session on which the spreadsheet is reporting
DataField: nws12_mainz_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_afterhsz_1p
DataFieldDescription: The minimum of L or S above for 1-minute bucket
DataField: nws12_prez_tonhigh
DataFieldDescription: Highest price reached during the session before the time of the news
DataField: nws12_allz_provider
DataFieldDescription: index of name of the news provider
DataField: nws12_prez_tonlow
DataFieldDescription: Lowest price reached during the session before the time of the news
DataField: nws12_afterhsz_3s
DataFieldDescription: Number of minutes that elapsed before price went down 3 percentage points
DataField: nws12_prez_10_min
DataFieldDescription: The percent change in price in the first 10 minutes following the news release
DataField: nws12_mainz_short_interest
DataFieldDescription: Total number of shares sold short divided by total number of shares outstanding
DataField: nws12_prez_5_min
DataFieldDescription: The percent change in price in the first 5 minutes following the news release
DataField: news_pct_1min
DataFieldDescription: The percent change in price in the first minute following the news release
DataField: nws12_prez_mov_vol
DataFieldDescription: 30-day moving average session volume
DataField: nws12_mainz_2p
DataFieldDescription: The minimum of L or S above for 2 minute bucket
DataField: nws12_afterhsz_2l
DataFieldDescription: Number of minutes that elapsed before price went up 2 percentage points
DataField: news_close_vol
DataFieldDescription: Main close volume
DataField: nws12_afterhsz_3l
DataFieldDescription: Number of minutes that elapsed before price went up 3 percentage points
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_nip_marketing
DataFieldDescription: News impact projection of marketing news
DataField: rp_ess_dividends
DataFieldDescription: Event sentiment score of dividends news
DataField: rp_ess_labor
DataFieldDescription: Event sentiment score of labor issues news
DataField: rp_css_marketing
DataFieldDescription: Composite sentiment score of marketing news
DataField: nws18_ghc_lna
DataFieldDescription: Change in analyst recommendation
DataField: rp_ess_credit_ratings
DataFieldDescription: Event sentiment score of credit ratings news
DataField: rp_css_legal
DataFieldDescription: Composite sentiment score of legal news
DataField: nws18_relevance
DataFieldDescription: Relevance of news to the company
DataField: rp_css_mna
DataFieldDescription: Composite sentiment score of mergers and acquisitions-related news
DataField: rp_css_society
DataFieldDescription: Composite sentiment score of society-related news
DataField: rp_css_business
DataFieldDescription: Composite sentiment score of business-related news
DataField: nws18_ber
DataFieldDescription: News sentiment specializing in earnings result
DataField: rp_ess_technical
DataFieldDescription: Event sentiment score based on technical analysis
DataField: rp_css_inverstor
DataFieldDescription: Composite sentiment score of investor relations news
DataField: rp_css_labor
DataFieldDescription: Composite sentiment score of labor issues news
DataField: nws18_qep
DataFieldDescription: News sentiment based on positive and negative words on global equity
DataField: rp_ess_business
DataFieldDescription: Event sentiment score of business-related news
DataField: nws18_nip
DataFieldDescription: Degree of impact of the news
DataField: nws18_sse
DataFieldDescription: Sentiment of phrases impacting the company
DataField: nws18_ssc
DataFieldDescription: Sentiment of the news calculated using multiple techniques
DataField: nws18_event_similarity_days
DataFieldDescription: Days since a similar event was detected
DataField: rp_css_credit
DataFieldDescription: Composite sentiment score of credit news
DataField: rp_css_technical
DataFieldDescription: Composite sentiment score based on technical analysis
DataField: rp_ess_society
DataFieldDescription: Event sentiment score of society-related news
DataField: rp_nip_technical
DataFieldDescription: News impact projection based on technical analysis
DataField: rp_css_ptg
DataFieldDescription: Composite sentiment score of price target news
DataField: rp_nip_assets
DataFieldDescription: News impact projection of assets news
DataField: rp_nip_ratings
DataFieldDescription: News impact projection of analyst ratings-related news
DataField: rp_ess_earnings
DataFieldDescription: Event sentiment score of earnings news
DataField: fnd2_a_inventoryrawmaterials
DataFieldDescription: Amount before valuation and LIFO reserves of raw materials expected to be sold, or consumed within 1 year or operating cycle, if longer.
DataField: fnd2_ebitfr
DataFieldDescription: EBIT, Foreign
DataField: fnd2_itxreclstatelocalitxes
DataFieldDescription: Amount of the difference between reported income tax expense (benefit) and expected income tax expense (benefit) computed by applying the domestic federal statutory income tax rates to pretax income (loss) from continuing operations attributable to state and local income tax expense (benefit).
DataField: fn_assets_fair_val_l1_a
DataFieldDescription: Asset Fair Value, Recurring, Level 1
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: fn_new_shares_options_q
DataFieldDescription: Number of share options (or share units) exercised during the current period.
DataField: fn_comp_fair_value_assumptions_weighted_avg_vol_rate_a
DataFieldDescription: Weighted average expected volatility rate of share-based compensation awards.
DataField: fn_repayments_of_lines_of_credit_a
DataFieldDescription: Amount of cash outflow for payment of an obligation from a lender, including but not limited to, letter of credit, standby letter of credit and revolving credit arrangements.
DataField: fnd2_dbplanfvalpnas
DataFieldDescription: Fair value of assets that have been segregated and restricted to provide pension or postretirement benefits. Assets include, but are not limited to, stocks, bonds, other investments, earnings from investments, and contributions by the employer and employees.
DataField: fnd2_a_eplsbvdcpcstnrgsbaoo
DataFieldDescription: Unrecognized cost of unvested other share-based compensation awards.
DataField: fn_op_lease_min_pay_due_in_5y_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 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_liab_fair_val_l1_q
DataFieldDescription: Liabilities Fair Value, Recurring, Level 1
DataField: fn_def_tax_liab_q
DataFieldDescription: Amount, after deferred tax asset, of deferred tax liability attributable to taxable differences without jurisdictional netting.
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_income_from_equity_investments_a
DataFieldDescription: Income From Equity Method Investments
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: 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_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: fnd2_dbplanchgbnfolintcst
DataFieldDescription: Defined Benefit Plan Change In Benefit Obligation Interest Cost
DataField: fnd2_q_inventoryrawmaterials
DataFieldDescription: Amount before valuation and LIFO reserves of raw materials expected to be sold, or consumed within 1 year or operating cycle, if longer.
DataField: fn_repayments_of_lines_of_credit_q
DataFieldDescription: Amount of cash outflow for payment of an obligation from a lender, including but not limited to, letter of credit, standby letter of credit and revolving credit arrangements.
DataField: fn_business_combination_assets_aquired_goodwill_q
DataFieldDescription: Business Combination, Portion of Purchase Price Allocated to Goodwill
DataField: fn_comp_options_exercises_weighted_avg_a
DataFieldDescription: Share-Based Compensation, Options Assumed, Weighted Average Exercise Price
DataField: fn_op_lease_rent_exp_a
DataFieldDescription: Rental expense for the reporting period incurred under operating leases, including minimum and any contingent rent expense, net of related sublease income.
DataField: fnd2_a_lhdiprtsg
DataFieldDescription: Amount before accumulated depreciation of additions or improvements to assets held under a lease arrangement.
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: fn_comp_not_rec_stock_options_a
DataFieldDescription: Unrecognized cost of unvested stock option awards.
DataField: fn_business_acq_ppne_a
DataFieldDescription: Business Combination, Assumed Property, Plant and Equipment
DataField: fnd2_a_sbcpnargmpmwggil
DataFieldDescription: Amount by which the current fair value of the underlying stock exceeds the exercise price of fully vested and expected to vest options outstanding.
DataField: 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 =======================================