任务指令
一、经济逻辑描述优化
视角一：市场摩擦的横截面测绘
核心经济逻辑：
市场摩擦创造系统性的定价延迟和反应差异。不同股票因流动性、投资者结构和交易机制差异，对相同市场信息的反应速度和程度不同。这些差异形成可预测的Alpha机会：
流动性溢价动态：低流动性股票因交易成本较高，需要更高的预期收益补偿。但流动性条件会随时间变化，形成动态的流动性溢价套利窗口。
信息扩散速度差异：机构持仓集中度高的股票信息反应更快，散户主导的股票反应更慢且易出现过度反应，创造套利空间。
交易冲击的持续性：大宗交易对价格的冲击在低流动性环境中衰减更慢，形成短期价格动量；在高流动性环境中衰减更快，易出现反转。
视角二：投资者注意力生态学
核心经济逻辑：
注意力是金融市场中的稀缺资源，其分配不均导致定价效率差异：
有限注意力约束：投资者无法同时处理所有信息，只能关注有限数量的股票，导致被忽视股票出现定价延迟。
注意力传染效应：当某行业或主题受到关注时，注意力会按特定路径扩散（龙头→二线→边缘），形成可预测的轮动模式。
注意力衰减曲线：事件驱动型关注会随时间衰减，但衰减速度因股票特质而异。快速衰减可能导致定价错误快速修正，缓慢衰减则可能维持定价偏差。
视角三：价格运动的形态语法
核心经济逻辑：
价格形态反映市场参与者的集体行为模式和心理预期：
技术分析的自我实现：广泛使用的技术指标（如支撑阻力位、均线系统）影响交易决策，形成可预测的价格行为。
叙事驱动的价格记忆：价格在关键历史位置的行为会形成市场“记忆”，影响未来在这些位置附近的交易决策。
多时间尺度协调：不同时间框架投资者的行为协调（共振）或冲突（背离）决定趋势的可持续性。
二、复合因子构建的经济逻辑规范
A. 领导力动量因子
经济逻辑：
成交量是市场关注度和资金流向的直接体现。大成交量股票通常由机构投资者主导，其价格变动反映更充分的信息和更强的共识。这种“聪明钱”效应使大成交量股票的动量信号更具预测性。同时，成交量的横截面分布反映不同股票在投资者注意力竞争中的相对地位。
经济学基础：
成交量与信息含量正相关（Kyle模型）
机构交易者具有信息优势
注意力驱动的资本流动
B. 状态自适应动量
经济逻辑：
市场波动率状态反映信息流的速度和市场不确定性水平。高波动环境通常伴随高频信息流和快速变化的预期，短期动量更有效；低波动环境反映稳定预期，长期动量更可靠。通过波动率状态动态调整动量窗口，可以避免在不同市场机制下使用不匹配的策略。
经济学基础：
波动率聚集现象
市场状态的持久性
信息处理速度与波动率的关系
C. 行业传导因子
经济逻辑：
行业间存在基本面关联（产业链）和资金面关联（配置资金流动）。强势行业的出现通常反映某种宏观或产业逻辑，这种逻辑会按特定顺序向相关行业传导（如上游→下游，龙头→配套）。传导速度受行业基本面关联度和市场情绪影响，创造可预测的轮动机会。
经济学基础：
产业价值链传递
资金配置的渐进调整
相关性结构的时变性
D. 情绪反转因子
经济逻辑：
交易活跃度反映市场情绪强度。过度交易往往伴随非理性繁荣或恐慌，此时趋势可能接近拐点；交易清淡则反映市场分歧或缺乏关注，趋势可能延续。结合趋势强度可以区分情绪驱动的短期反转和基本面驱动的长期反转。
经济学基础：
过度反应与修正
有限套利与情绪持续性
交易量作为情绪代理变量
三、参数选择的经济逻辑
回顾期选择依据：
5-10日：捕捉事件驱动型Alpha，反映短期信息冲击
20-30日：捕捉月度调仓效应和基本面预期调整
60-120日：捕捉季度业绩周期和行业轮动周期
阈值参数的经济含义：
0.5：中位数效应，反映平均或典型情况
0.7-0.8：极端情况识别，捕捉显著的异常或结构性变化
四、行业轮动的经济学原理
周期性轮动：宏观经济周期不同阶段对各行业影响不同（早周期、中周期、晚周期）
相对估值轮动：行业间估值差异回归均值驱动资金流动
风险偏好轮动：市场风险偏好变化影响不同风险特征行业的相对表现
政策驱动轮动：产业政策、监管变化创造结构性机会
技术创新扩散：新技术沿产业链扩散的顺序性
五、风险调整的经济逻辑
流动性风险补偿：低流动性股票需提供更高预期收益
波动率风险定价：高波动股票的风险溢价要求
相关性结构风险：行业间相关性变化对分散化效果的影响
尾部风险暴露：极端事件对不同行业的非对称影响
六、交易可行性的经济学考虑
交易成本内生性：流动性差的股票交易成本高，需要更强的Alpha信号
容量约束：策略容量受市场深度限制
市场影响成本：大额交易对价格的冲击
竞争性衰减：被广泛采用的Alpha会因套利而衰减
七、因子表达式的经济解释规范
每个表达式应明确回答：
捕捉什么市场异象？（例如：注意力驱动定价延迟、流动性溢价变化等）
为什么这个异象会持续存在？（行为偏差、制度约束、风险补偿等）
在什么市场环境下更有效？（高波动、低流动性、趋势市等）
可能失效的条件是什么？（市场机制变化、投资者结构变化等）
这样的经济逻辑描述确保了每个因子都有清晰的理论基础和经济直觉，而非纯粹的数据挖掘结果。
*=====*
输出格式：
输出必须是且仅是纯文本。
每一行是一个完整、独立、语法正确的WebSim表达式。
严禁任何形式的解释、编号、标点包裹（如引号）、Markdown格式或额外文本。
===================== !!! 重点(输出方式) !!! =====================
现在，请严格遵守以上所有规则，开始生成可立即在WebSim中运行的复合因子表达式。
**输出格式**(一行一个表达式, 每个表达式中间需要添加一个空行, 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
=================================================================
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, 以及我提供的数据集, 进行生成,组合 100 个alpha：

以下是我的账号有权限使用的操作符, 请严格按照操作符, 进行生成,组合因子

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

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

DataField: 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: option_breakeven_360
DataFieldDescription: Price at which a stock's options with expiration 360 days in the future break even based on its recent bid/ask mean.
DataField: pcr_oi_270
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 270 days in the future.
DataField: option_breakeven_270
DataFieldDescription: Price at which a stock's options with expiration 270 days in the future break even based on its recent bid/ask mean.
DataField: 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_1080
DataFieldDescription: Price at which a stock's call options with expiration 1080 days in the future break even based on its recent bid/ask mean.
DataField: 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: pcr_vol_30
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 30 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: 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: put_breakeven_360
DataFieldDescription: Price at which a stock's put options with expiration 360 days in the future break even based on its recent bid/ask mean.
DataField: 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: forward_price_120
DataFieldDescription: Forward price at 120 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
DataField: 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: 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_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_20
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 20 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: pcr_oi_720
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 720 days in the future.
DataField: 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: pcr_vol_180
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 180 days in the future.
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: 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_180
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 180 days in the future.
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_180
DataFieldDescription: Forward price at 180 days derived from a synthetic long option with payoff similar to long stock + option dynamics. combination of long ATM call, and short ATM put.
DataField: 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: 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: pcr_vol_all
DataFieldDescription: Ratio of put volume to call volume for all maturities on stock's options.
DataField: fnd6_newqeventv110_drltq
DataFieldDescription: Deferred Revenue - Long-term
DataField: fnd6_eventv110_txdbcaq
DataFieldDescription: Current Deferred Tax Asset
DataField: fnd6_rank
DataFieldDescription: SP rank with the following meaning: // 0----invalid rank //1----A+//2----A//3----A-//4----B+//5----B//6----B-//7----C+//8----C//9----C-
DataField: fnd6_newqv1300_spceepspq
DataFieldDescription: S&P Core Earnings EPS Basic - Preliminary
DataField: fnd6_newqv1300_gdwlq
DataFieldDescription: Goodwill (net)
DataField: fnd6_txdbca
DataFieldDescription: Deferred Tax Asset - Current
DataField: ebit
DataFieldDescription: Earnings Before Interest and Taxes
DataField: fnd6_esubc
DataFieldDescription: Equity in Net Loss - Earnings
DataField: fnd6_newqv1300_lltq
DataFieldDescription: Long-Term Liabilities (Total)
DataField: fnd6_newq_xoptepsqp
DataFieldDescription: Implied Option EPS Basic Preliminary
DataField: fnd6_newqeventv110_cibegniq
DataFieldDescription: Comp Inc - Beginning Net Income
DataField: fnd6_newa2v1300_sale
DataFieldDescription: Sales/Turnover (Net)
DataField: fnd6_cptnewqv1300_saleq
DataFieldDescription: Sales/Turnover (Net)
DataField: fnd6_newa2v1300_rdipeps
DataFieldDescription: In Process R&D Expense Basic EPS Effect
DataField: fnd6_newa2v1300_ppent
DataFieldDescription: Property, Plant and Equipment - Total (Net)
DataField: fnd6_newqeventv110_xopt12
DataFieldDescription: Implied Option Expense - 12mm
DataField: fnd6_newqeventv110_loq
DataFieldDescription: Liabilities - Other
DataField: fnd6_newqv1300_seqoq
DataFieldDescription: Other Stockholders' Equity Adjustments
DataField: rd_expense
DataFieldDescription: Research And Development (Quarterly)
DataField: fnd6_acqintan
DataFieldDescription: Acquired Assets - Intangibles
DataField: fnd6_newqv1300_chq
DataFieldDescription: Cash
DataField: fnd6_aqi
DataFieldDescription: Acquisitions - Income Contribution
DataField: fnd6_reajo
DataFieldDescription: Retained Earnings - Other Adjustments
DataField: fnd6_dxd5
DataFieldDescription: Debt (excl Capitalized Leases) - Due in 5th Year
DataField: fnd6_newa1v1300_invt
DataFieldDescription: Inventories - Total
DataField: fnd6_newqeventv110_glcepq
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) Pretax
DataField: fnd6_newa1v1300_aqpl1
DataFieldDescription: Assets Level 1 (Quoted Prices)
DataField: fnd6_newqeventv110_invwipq
DataFieldDescription: Inventory - Work in Process
DataField: fnd6_cptmfmq_oibdpq
DataFieldDescription: Operating Income Before Depreciation - Quarterly
DataField: fnd6_xpp
DataFieldDescription: Prepaid Expenses
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_afv4_maxguidance
DataFieldDescription: Max guidance value
DataField: anl4_totgw_median
DataFieldDescription: Total Goodwill - median of estimations
DataField: min_shareholders_equity_guidance
DataFieldDescription: Minimum guidance value for Shareholders' Equity
DataField: anl4_ads1detailafv110_bk
DataFieldDescription: Broker name (int)
DataField: anl4_fsdtlestmtbscqv104_item
DataFieldDescription: Financial item
DataField: anl4_rd_exp_mean
DataFieldDescription: Research and Development Expense - mean of estimations
DataField: est_sales
DataFieldDescription: Sales - mean of estimations
DataField: max_book_value_per_share_guidance
DataFieldDescription: Book value per share - Maximum value among forecasts
DataField: anl4_rd_exp_median
DataFieldDescription: Research and Development Expense - Median of estimations
DataField: max_customized_eps_guidance
DataFieldDescription: The maximum guidance value for custom earnings per share on an annual basis.
DataField: operating_profit_before_depr_amort_min_guidance_qtr
DataFieldDescription: Minimum guidance value for Earnings before interest, taxes, depreciation and amortization
DataField: anl4_fsgdncbscv4_maxguidance
DataFieldDescription: Max guidance value
DataField: anl4_qf_az_cfps_number
DataFieldDescription: Cash Flow Per Share - number of estimations
DataField: anl4_basicconltv110_pu
DataFieldDescription: The number of upper estimations
DataField: min_net_profit_guidance
DataFieldDescription: Minimum guidance value for Net Profit on an annual basis
DataField: funds_from_operations_max_guidance
DataFieldDescription: The maximum guidance value for Funds from operation - annual
DataField: free_cash_flow_per_share_reported_value
DataFieldDescription: Free cash flow per share- announced financial value
DataField: operating_profit_before_interest_tax
DataFieldDescription: Earnings Before Interest and Taxes (EBIT) - Actual Value
DataField: actual_sales_value_quarterly
DataFieldDescription: Sales - Value in financial services income statement (in millions)
DataField: net_profit_reported_value
DataFieldDescription: Net profit- announced financial value
DataField: est_tbv_ps
DataFieldDescription: Tangible Book Value per Share - mean of estimations
DataField: min_shares_outstanding_guidance
DataFieldDescription: Minimum guidance value for Shares
DataField: anl4_qfv4_div_number
DataFieldDescription: Dividend - number of estimations
DataField: anl4_eaz2lltv110_estvalue
DataFieldDescription: Estimation value
DataField: earnings_per_share_maximum
DataFieldDescription: Earnings per share - The highest estimation
DataField: net_debt_max_guidance_qtr
DataFieldDescription: Maximum guidance value for Net Debt
DataField: est_netprofit_adj
DataFieldDescription: Adjusted net income - Mean of estimations
DataField: anl4_netdebt_number
DataFieldDescription: Net debt - Number of estimations
DataField: earnings_per_share_reported
DataFieldDescription: Reported Earnings Per Share - Actual Value
DataField: max_adjusted_funds_from_operations_guidance_2
DataFieldDescription: Adjusted funds from operation - maximum guidance value for the annual period
DataField: pv13_hierarchy_min30_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy2_min2_1k_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_new_4l_scibr
DataFieldDescription: grouping fields
DataField: pv13_h_min51_f3_sector
DataFieldDescription: grouping fields
DataField: pv13_revere_city
DataFieldDescription: City code
DataField: pv13_hierarchy23_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_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_min40_3000_513_sector
DataFieldDescription: grouping fields
DataField: rel_num_comp
DataFieldDescription: number of the instrument's competitors
DataField: pv13_r2_min5_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min5_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min2_sector
DataFieldDescription: grouping fields
DataField: pv13_h_f3_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_f3_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min52_2k_sector
DataFieldDescription: grouping fields
DataField: pv13_6l_scibr
DataFieldDescription: grouping fields
DataField: pv13_h_f1_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min25_sector
DataFieldDescription: grouping fields
DataField: pv13_r2_liquid_min10_sector
DataFieldDescription: grouping fields
DataField: rel_num_part
DataFieldDescription: number of the instrument's partners
DataField: pv13_rha2_min20_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min2_focused_pureplay_sector
DataFieldDescription: grouping fields
DataField: pv13_rha2_min10_3000_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min20_3k_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min10_sector_3000_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min30_513_sector
DataFieldDescription: grouping fields
DataField: pv13_hierarchy_min30_3000_mapped_513_sector
DataFieldDescription: grouping fields
DataField: parkinson_volatility_150
DataFieldDescription: Parkinson model's historical volatility over 150 days
DataField: implied_volatility_call_180
DataFieldDescription: At-the-money option-implied volatility for call Option for 180 days
DataField: implied_volatility_call_90
DataFieldDescription: At-the-money option-implied volatility for call Option for 90 days
DataField: implied_volatility_mean_skew_30
DataFieldDescription: At-the-money option-implied volatility mean skew for 30 days
DataField: implied_volatility_mean_skew_360
DataFieldDescription: At-the-money option-implied volatility mean skew for 360 days
DataField: implied_volatility_mean_skew_10
DataFieldDescription: At-the-money option-implied volatility mean skew for 10 days
DataField: implied_volatility_put_30
DataFieldDescription: At-the-money option-implied volatility for Put Option for 30 days
DataField: implied_volatility_put_720
DataFieldDescription: At-the-money option-implied volatility for Put Option for 720 days
DataField: historical_volatility_90
DataFieldDescription: Close-to-close Historical volatility over 90 days
DataField: implied_volatility_mean_skew_150
DataFieldDescription: At-the-money option-implied volatility mean skew for 150 days
DataField: implied_volatility_mean_skew_720
DataFieldDescription: At-the-money option-implied volatility mean skew for 720 days
DataField: implied_volatility_put_270
DataFieldDescription: At-the-money option-implied volatility for Put Option for 270 days
DataField: implied_volatility_put_90
DataFieldDescription: At-the-money option-implied volatility for Put Option for 90 days
DataField: implied_volatility_put_120
DataFieldDescription: At-the-money option-implied volatility for Put Option for 120 days
DataField: implied_volatility_mean_360
DataFieldDescription: At-the-money option-implied volatility mean for 360 days
DataField: implied_volatility_call_30
DataFieldDescription: At-the-money option-implied volatility for call Option for 30 days
DataField: implied_volatility_put_180
DataFieldDescription: At-the-money option-implied volatility for put option for 180 days
DataField: implied_volatility_put_360
DataFieldDescription: At-the-money option-implied volatility for Put Option for 360 days
DataField: parkinson_volatility_10
DataFieldDescription: Parkinson model's historical volatility over 2 weeks
DataField: parkinson_volatility_90
DataFieldDescription: Parkinson model's historical volatility over 90 days
DataField: implied_volatility_put_1080
DataFieldDescription: At-the-money option-implied volatility for Put Option for 3 years
DataField: implied_volatility_mean_skew_60
DataFieldDescription: At-the-money option-implied volatility mean skew for 60 days
DataField: parkinson_volatility_120
DataFieldDescription: Parkinson model's historical volatility over 120 days
DataField: historical_volatility_10
DataFieldDescription: Close-to-close Historical volatility over 10 days
DataField: implied_volatility_put_20
DataFieldDescription: At-the-money option-implied volatility for Put Option for 20 days
DataField: implied_volatility_mean_270
DataFieldDescription: At-the-money option-implied volatility mean for 270 days
DataField: implied_volatility_call_120
DataFieldDescription: At-the-money option-implied volatility for call Option for 120 days
DataField: implied_volatility_call_270
DataFieldDescription: At-the-money option-implied volatility for call Option for 270 days
DataField: implied_volatility_mean_30
DataFieldDescription: At-the-money option-implied volatility mean for 30 days
DataField: historical_volatility_180
DataFieldDescription: Close-to-close Historical volatility over 180 days
DataField: nws12_mainz_open_vol
DataFieldDescription: Main open volume
DataField: nws12_mainz_allticks
DataFieldDescription: Total number of ticks for the trading day
DataField: nws12_mainz_rangeamt
DataFieldDescription: Session High Price - Session Low Price
DataField: nws12_mainz_3l
DataFieldDescription: Number of minutes that elapsed before price went up 3 percentage points
DataField: nws12_mainz_10_min
DataFieldDescription: The percent change in price in the first 10 minutes following the news release
DataField: nws12_afterhsz_2l
DataFieldDescription: Number of minutes that elapsed before price went up 2 percentage points
DataField: news_eod_low
DataFieldDescription: Lowest price reached between the time of news and the end of the session
DataField: nws12_afterhsz_newssess
DataFieldDescription: Index of the session in which the news was reported
DataField: nws12_prez_close_vol
DataFieldDescription: Main close volume
DataField: nws12_prez_1p
DataFieldDescription: The minimum of L or S above for 1-minute bucket
DataField: news_ton_high
DataFieldDescription: Highest price reached during the session before the time of news
DataField: nws12_mainz_90_min
DataFieldDescription: The percent change in price in the first 90 minutes following the news release
DataField: news_max_dn_amt
DataFieldDescription: The price at the time of the news minus the after the news low
DataField: nws12_afterhsz_vol_ratio
DataFieldDescription: Curr_Vol / Mov_Vol
DataField: nws12_prez_2l
DataFieldDescription: Number of minutes that elapsed before price went up 2 percentage points
DataField: news_eod_close
DataFieldDescription: Close price of the session
DataField: news_atr14
DataFieldDescription: 14-day Average True Range
DataField: nws12_prez_newrecord
DataFieldDescription: Tracks whether the news is the first instance or a duplicate
DataField: nws12_prez_prevday
DataFieldDescription: Percent change between the previous day's open and close
DataField: nws12_afterhsz_01s
DataFieldDescription: Number of minutes that elapsed before price went down 10 percentage points
DataField: nws12_afterhsz_57l
DataFieldDescription: Number of minutes that elapsed before price went up 7.5 percentage points
DataField: nws12_allz_result1
DataFieldDescription: Percent change between the price at the time of the news release and the price at the close of the session
DataField: news_max_up_ret
DataFieldDescription: Percent change from the price at the time of the news to the after the news high
DataField: nws12_allz_reportsess
DataFieldDescription: Index of Session on which the spreadsheet is reporting
DataField: nws12_prez_result_vs_index
DataFieldDescription: ((EODClose - TONLast) / TONLast) - ((SPYClose - SPYLast) / SPYLast)
DataField: nws12_prez_reportsess
DataFieldDescription: Index of Session on which the spreadsheet is reporting
DataField: nws12_afterhsz_reportsess
DataFieldDescription: Index of Session on which the spreadsheet is reporting
DataField: nws12_prez_allticks
DataFieldDescription: Total number of ticks for the trading day
DataField: news_atr_ratio
DataFieldDescription: Ratio of today's range to 20-day average true range
DataField: nws12_mainz_result2
DataFieldDescription: Percent change between the price at the time of the news release to the price at the close of the session
DataField: top1000
DataFieldDescription: 20140630
DataField: top200
DataFieldDescription: 20140630
DataField: top3000
DataFieldDescription: 20140630
DataField: top500
DataFieldDescription: 20140630
DataField: topsp500
DataFieldDescription: 20140630
DataField: rp_css_technical
DataFieldDescription: Composite sentiment score based on technical analysis
DataField: rp_ess_ratings
DataFieldDescription: Event sentiment score of analyst ratings-related news
DataField: rp_nip_earnings
DataFieldDescription: News impact projection of earnings news
DataField: rp_nip_mna
DataFieldDescription: News impact projection of mergers and acquisitions-related news
DataField: rp_css_product
DataFieldDescription: Composite sentiment score of product and service-related news
DataField: rp_css_ptg
DataFieldDescription: Composite sentiment score of price target news
DataField: rp_css_legal
DataFieldDescription: Composite sentiment score of legal news
DataField: rp_ess_price
DataFieldDescription: Event sentiment score of stock price news
DataField: nws18_nip
DataFieldDescription: Degree of impact of the news
DataField: rp_ess_technical
DataFieldDescription: Event sentiment score based on technical analysis
DataField: rp_nip_business
DataFieldDescription: News impact projection of business-related news
DataField: rp_css_credit
DataFieldDescription: Composite sentiment score of credit news
DataField: rp_css_inverstor
DataFieldDescription: Composite sentiment score of investor relations news
DataField: rp_nip_inverstor
DataFieldDescription: News impact projection of investor relations news
DataField: nws18_ssc
DataFieldDescription: Sentiment of the news calculated using multiple techniques
DataField: rp_css_revenue
DataFieldDescription: Composite sentiment score of revenue news
DataField: rp_nip_partner
DataFieldDescription: News impact projection of partnership news
DataField: nws18_relevance
DataFieldDescription: Relevance of news to the company
DataField: rp_css_insider
DataFieldDescription: Composite sentiment score of insider trading news
DataField: nws18_qmb
DataFieldDescription: News sentiment specializing in editorials on global markets
DataField: rp_ess_society
DataFieldDescription: Event sentiment score of society-related news
DataField: rp_ess_assets
DataFieldDescription: Event sentiment score of assets news
DataField: rp_nip_marketing
DataFieldDescription: News impact projection of marketing news
DataField: rp_nip_ptg
DataFieldDescription: News impact projection of price target news
DataField: rp_ess_product
DataFieldDescription: Event sentiment score of product and service-related news
DataField: rp_ess_ptg
DataFieldDescription: Event sentiment score of price target news
DataField: rp_nip_equity
DataFieldDescription: News impact projection of equity action news
DataField: rp_ess_partner
DataFieldDescription: Event sentiment score of partnership news
DataField: rp_css_marketing
DataFieldDescription: Composite sentiment score of marketing news
DataField: rp_ess_earnings
DataFieldDescription: Event sentiment score of earnings news
DataField: fnd2_q_flintasamt1expythree
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 3rd 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_op_lease_min_pay_due_after_5y_a
DataFieldDescription: Amount of required minimum rental payments for operating leases having an initial or remaining non-cancelable lease term in excess of one year due after the 5th fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: fnd2_unrgtxbnfinregfprtxps
DataFieldDescription: Amount of increase in unrecognized tax benefits resulting from tax positions taken in prior period tax returns.
DataField: fn_liab_fair_val_l2_q
DataFieldDescription: Liabilities Fair Value, Recurring, Level 2
DataField: fn_income_tax_expense_q
DataFieldDescription: Income Tax Expense (Benefit)
DataField: fn_repurchased_shares_q
DataFieldDescription: Number of shares that have been repurchased during the period.
DataField: fnd2_a_flintasamt1expnext12m
DataFieldDescription: Amount of amortization expense for assets, excluding financial assets and goodwill, lacking physical substance with a finite life expected to be recognized during the next fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: fnd2_a_frtandfixturesg
DataFieldDescription: Amount before accumulated depreciation of equipment commonly used in offices and stores that have no permanent connection to the structure of a building or utilities. Examples include, but are not limited to, desks, chairs, tables, and bookcases.
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: fn_accrued_liab_curr_q
DataFieldDescription: Carrying value as of the balance sheet date of obligations incurred and payable, pertaining to costs that are statutory in nature, are incurred on contractual obligations, or accumulate over time and for which invoices have not yet been received or will not be rendered.
DataField: fn_finite_lived_intangible_assets_gross_q
DataFieldDescription: Amount before amortization of assets, excluding financial assets and goodwill, lacking physical substance with a finite life.
DataField: fnd2_a_sbcpnargmpmtwvadpgwepr
DataFieldDescription: As of the balance sheet date, the weighted-average exercise price for outstanding stock options that are fully vested or expected to vest.
DataField: fnd2_a_lhdiprtsg
DataFieldDescription: Amount before accumulated depreciation of additions or improvements to assets held under a lease arrangement.
DataField: fn_comp_non_opt_nonvested_number_a
DataFieldDescription: The number of non-vested equity-based payment instruments, excluding stock (or unit) options, that validly exist and are outstanding as of the balance sheet date.
DataField: fn_income_from_equity_investments_q
DataFieldDescription: Income From Equity Method Investments
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: 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: fn_accrued_liab_q
DataFieldDescription: Carrying value as of the balance sheet date of obligations incurred and payable, pertaining to costs that are statutory in nature, are incurred on contractual obligations, or accumulate over time and for which invoices have not yet been received or will not be rendered.
DataField: fn_proceeds_from_issuance_of_common_stock_a
DataFieldDescription: The cash inflow from the additional capital contribution to the entity.
DataField: fnd2_dbplanactuarialgl
DataFieldDescription: Defined Benefit Plan, Benefits Paid, Plan Assets
DataField: fn_new_shares_options_a
DataFieldDescription: Number of share options (or share units) exercised during the current period.
DataField: fn_business_combination_purchase_price_q
DataFieldDescription: Business Combination, Purchase Price
DataField: fnd2_a_bnscbmacqrcsts
DataFieldDescription: This element represents acquisition-related costs incurred to effect a business combination which costs have been expensed during the period. Such costs include finder's fees; advisory, legal, accounting, valuation, and other professional or consulting fees; general administrative costs, including the costs of maintaining an internal acquisitions department; and may include costs of registering and issuing debt and equity securities.
DataField: fn_taxes_payable_a
DataFieldDescription: Carrying value as of the balance sheet date of obligations incurred and payable for statutory income, sales, use, payroll, excise, real, property, and other taxes. For classified balance sheets, used to reflect the current portion of the liabilities (due within 1 year or within the normal operating cycle if longer); for unclassified balance sheets, used to reflect the total liabilities (regardless of due date).
DataField: fn_income_taxes_paid_q
DataFieldDescription: The amount of cash paid during the current period to foreign, federal, state, and local authorities as taxes on income.
DataField: fnd2_dbplanepdfbnfpy5
DataFieldDescription: Amount of benefits from a defined benefit plan expected to be paid 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_op_lease_min_pay_due_in_3y_a
DataFieldDescription: Amount of required minimum rental payments for operating leases having an initial or remaining non-cancelable lease term in excess of one year due in the 3rd fiscal year following the latest fiscal year. Excludes interim and annual periods when interim periods are reported on a rolling approach, from latest balance sheet date.
DataField: fn_accum_oth_income_loss_fx_adj_net_of_tax_a
DataFieldDescription: Accumulated adjustment, net of tax, that results from the process of translating subsidiary financial statements and foreign equity investments into the reporting currency from the functional currency of the reporting entity, net of reclassification of realized foreign currency translation gains or losses.
DataField: fnd2_a_sbcpnargmsawpfipwerpr
DataFieldDescription: Weighted average price of options that were either forfeited or expired.
DataField: fn_derivative_fair_value_of_derivative_liability_a
DataFieldDescription: Fair value, before effects of master netting arrangements, of a financial liability or contract with one or more underlyings, notional amount or payment provision or both, and the contract can be net settled by means outside the contract or delivery of an asset. Includes liabilities elected not to be offset. Excludes liabilities not subject to a master netting arrangement.
DataField: 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
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