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895 lines
54 KiB
895 lines
54 KiB
任务指令
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一、经济逻辑描述优化
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视角一：市场摩擦的横截面测绘
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核心经济逻辑：
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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：
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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。
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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。
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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。
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视角二：投资者注意力生态学
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核心经济逻辑：
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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：
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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。
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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。
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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。
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视角三：价格运动的形态语法
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核心经济逻辑：
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价格形态反映市场参与者的集体行为模式和心理预期：
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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。
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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。
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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。
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二、复合因子构建的经济逻辑规范
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A. 领导力动量因子
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经济逻辑：
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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。
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经济学基础：
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成交量与信息含量正相关（Kyle模型）
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机构交易者具有信息优势
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注意力驱动的资本流动
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B. 状态自适应动量
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经济逻辑：
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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。
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经济学基础：
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波动率聚集现象
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市场状态的持久性
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信息处理速度与波动率的关系
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C. 行业传导因子
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经济逻辑：
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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。
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经济学基础：
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产业价值链传递
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资金配置的渐进调整
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相关性结构的时变性
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D. 情绪反转因子
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经济逻辑：
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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。
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经济学基础：
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过度反应与修正
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有限套利与情绪持续性
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交易量作为情绪代理变量
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三、参数选择的经济逻辑
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回顾期选择依据：
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5-10日：捕捉事件驱动型Alpha，反映短期信息冲击
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20-30日：捕捉月度调仓效应和基本面预期调整
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60-120日：捕捉季度业绩周期和行业轮动周期
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阈值参数的经济含义：
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0.5：中位数效应，反映平均或典型情况
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0.7-0.8：极端情况识别，捕捉显著的异常或结构性变化
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四、行业轮动的经济学原理
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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）
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相对估值轮动：行业间估值差异回归均值驱动资金流动
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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
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政策驱动轮动：产业政策、监管变化创造结构性机会
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技术创新扩散：新技术沿产业链扩散的顺序性
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五、风险调整的经济逻辑
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流动性风险补偿：低流动性股票需提供更高预期收益
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波动率风险定价：高波动股票的风险溢价要求
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相关性结构风险：行业间相关性变化对分散化效果的影响
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尾部风险暴露：极端事件对不同行业的非对称影响
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六、交易可行性的经济学考虑
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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
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容量约束：策略容量受市场深度限制
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市场影响成本：大额交易对价格的冲击
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竞争性衰减：被广泛采用的Alpha会因套利而衰减
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七、因子表达式的经济解释规范
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每个表达式应明确回答：
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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）
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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）
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在什么市场环境下更有效？（高波动、低流动性、趋势市等）
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可能失效的条件是什么？（市场机制变化、投资者结构变化等）
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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。
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*=====*
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输出格式：
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输出必须是且仅是纯文本。
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每一行是一个完整、独立、语法正确的WebSim表达式。
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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。
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===================== !!! 重点(输出方式) !!! =====================
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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。
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**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)：
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表达式
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表达式
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表达式
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...
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表达式
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=================================================================
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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。
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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：
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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
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========================= 操作符开始 =======================================注意: Operator: 后面的是操作符,
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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
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特别注意!!!! 必须按照操作符字段Operator的使用说明生成 alphaOperator: abs(x)
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Description: Absolute value of x
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Operator: add(x, y, filter = false)
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Description: Add all inputs (at least 2 inputs required). If filter = true, filter all input NaN to 0 before adding
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Operator: densify(x)
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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
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Operator: divide(x, y)
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Description: x / y
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Operator: inverse(x)
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Description: 1 / x
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Operator: log(x)
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Description: Natural logarithm. For example: Log(high/low) uses natural logarithm of high/low ratio as stock weights.
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Operator: max(x, y, ..)
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Description: Maximum value of all inputs. At least 2 inputs are required
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Operator: min(x, y ..)
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Description: Minimum value of all inputs. At least 2 inputs are required
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Operator: multiply(x ,y, ... , filter=false)
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Description: Multiply all inputs. At least 2 inputs are required. Filter sets the NaN values to 1
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Operator: power(x, y)
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Description: x ^ y
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Operator: reverse(x)
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Description: - x
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Operator: sign(x)
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Description: if input > 0, return 1; if input < 0, return -1; if input = 0, return 0; if input = NaN, return NaN;
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Operator: signed_power(x, y)
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Description: x raised to the power of y such that final result preserves sign of x
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Operator: sqrt(x)
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Description: Square root of x
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Operator: subtract(x, y, filter=false)
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Description: x-y. If filter = true, filter all input NaN to 0 before subtracting
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Operator: and(input1, input2)
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Description: Logical AND operator, returns true if both operands are true and returns false otherwise
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Operator: if_else(input1, input2, input 3)
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Description: If input1 is true then return input2 else return input3.
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Operator: input1 < input2
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Description: If input1 < input2 return true, else return false
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Operator: input1 <= input2
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Description: Returns true if input1 <= input2, return false otherwise
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Operator: input1 == input2
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Description: Returns true if both inputs are same and returns false otherwise
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Operator: input1 > input2
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Description: Logic comparison operators to compares two inputs
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Operator: input1 >= input2
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Description: Returns true if input1 >= input2, return false otherwise
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Operator: input1!= input2
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Description: Returns true if both inputs are NOT the same and returns false otherwise
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Operator: is_nan(input)
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Description: If (input == NaN) return 1 else return 0
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Operator: not(x)
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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).
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Operator: or(input1, input2)
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Description: Logical OR operator returns true if either or both inputs are true and returns false otherwise
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Operator: days_from_last_change(x)
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Description: Amount of days since last change of x
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Operator: hump(x, hump = 0.01)
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Description: Limits amount and magnitude of changes in input (thus reducing turnover)
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Operator: kth_element(x, d, k)
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Description: Returns K-th value of input by looking through lookback days. This operator can be used to backfill missing data if k=1
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Operator: last_diff_value(x, d)
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Description: Returns last x value not equal to current x value from last d days
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Operator: ts_arg_max(x, d)
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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
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Operator: ts_arg_min(x, d)
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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.
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Operator: ts_av_diff(x, d)
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Description: Returns x - tsmean(x, d), but deals with NaNs carefully. That is NaNs are ignored during mean computation
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Operator: ts_backfill(x,lookback = d, k=1, ignore="NAN")
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Description: Backfill is the process of replacing the NAN or 0 values by a meaningful value (i.e., a first non-NaN value)
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Operator: ts_corr(x, y, d)
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Description: Returns correlation of x and y for the past d days
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Operator: ts_count_nans(x ,d)
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Description: Returns the number of NaN values in x for the past d days
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Operator: ts_covariance(y, x, d)
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Description: Returns covariance of y and x for the past d days
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Operator: ts_decay_linear(x, d, dense = false)
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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.
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Operator: ts_delay(x, d)
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Description: Returns x value d days ago
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Operator: ts_delta(x, d)
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Description: Returns x - ts_delay(x, d)
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Operator: ts_mean(x, d)
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Description: Returns average value of x for the past d days.
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Operator: ts_product(x, d)
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Description: Returns product of x for the past d days
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Operator: ts_quantile(x,d, driver="gaussian" )
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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.
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Operator: ts_rank(x, d, constant = 0)
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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.
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Operator: ts_regression(y, x, d, lag = 0, rettype = 0)
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Description: Returns various parameters related to regression function
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Operator: ts_scale(x, d, constant = 0)
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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
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Operator: ts_std_dev(x, d)
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Description: Returns standard deviation of x for the past d days
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Operator: ts_step(1)
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Description: Returns days' counter
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Operator: ts_sum(x, d)
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Description: Sum values of x for the past d days.
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Operator: ts_zscore(x, d)
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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.
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Operator: normalize(x, useStd = false, limit = 0.0)
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Description: Calculates the mean value of all valid alpha values for a certain date, then subtracts that mean from each element
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Operator: quantile(x, driver = gaussian, sigma = 1.0)
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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
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Operator: rank(x, rate=2)
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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
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Operator: scale(x, scale=1, longscale=1, shortscale=1)
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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
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Operator: winsorize(x, std=4)
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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.
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Operator: zscore(x)
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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
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Operator: vec_avg(x)
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Description: Taking mean of the vector field x
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Operator: vec_sum(x)
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Description: Sum of vector field x
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Operator: bucket(rank(x), range="0, 1, 0.1" or buckets = "2,5,6,7,10")
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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
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Operator: trade_when(x, y, z)
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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
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Operator: group_backfill(x, group, d, std = 4.0)
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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
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Operator: group_mean(x, weight, group)
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Description: All elements in group equals to the mean
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Operator: group_neutralize(x, group)
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Description: Neutralizes Alpha against groups. These groups can be subindustry, industry, sector, country or a constant
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Operator: group_rank(x, group)
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Description: Each elements in a group is assigned the corresponding rank in this group
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Operator: group_scale(x, group)
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Description: Normalizes the values in a group to be between 0 and 1. (x - groupmin) / (groupmax - groupmin)
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Operator: group_zscore(x, group)
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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.
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========================= 操作符结束 =======================================
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========================= 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
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DataField: pcr_vol_360
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DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 360 days in the future.
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DataField: pcr_oi_60
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DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 60 days in the future.
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DataField: call_breakeven_10
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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.
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DataField: option_breakeven_180
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DataFieldDescription: Price at which a stock's options with expiration 180 days in the future break even based on its recent bid/ask mean.
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DataField: forward_price_90
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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.
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DataField: option_breakeven_20
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DataFieldDescription: Price at which a stock's options with expiration 20 days in the future break even based on its recent bid/ask mean.
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DataField: forward_price_150
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DataFieldDescription: Forward price at 150 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
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DataField: call_breakeven_60
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DataFieldDescription: Price at which a stock's call options with expiration 60 days in the future break even based on its recent bid/ask mean.
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DataField: pcr_oi_30
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DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 30 days in the future.
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DataField: option_breakeven_360
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DataFieldDescription: Price at which a stock's options with expiration 360 days in the future break even based on its recent bid/ask mean.
|
|
DataField: call_breakeven_20
|
|
DataFieldDescription: Price at which a stock's call options with expiration 20 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: put_breakeven_60
|
|
DataFieldDescription: Price at which a stock's put options with expiration 60 days in the future break even based on its recent bid/ask mean.
|
|
DataField: option_breakeven_90
|
|
DataFieldDescription: Price at which a stock's options with expiration 90 days in the future break even based on its recent bid/ask mean.
|
|
DataField: call_breakeven_720
|
|
DataFieldDescription: Price at which a stock's call options with expiration 720 days in the future break even based on its recent bid/ask mean.
|
|
DataField: 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_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: pcr_oi_20
|
|
DataFieldDescription: Ratio of put open interest to call open interest on a stock's options with expiration 20 days in the future.
|
|
DataField: put_breakeven_90
|
|
DataFieldDescription: Price at which a stock's put options with expiration 90 days in the future break even based on its recent bid/ask mean.
|
|
DataField: 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_vol_180
|
|
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 180 days in the future.
|
|
DataField: pcr_vol_all
|
|
DataFieldDescription: Ratio of put volume to call volume for all maturities on stock's options.
|
|
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_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: 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_150
|
|
DataFieldDescription: Ratio of put volume to call volume on a stock's options with expiration 150 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: forward_price_120
|
|
DataFieldDescription: Forward price at 120 days derived from a synthetic long option with payoff similar to long stock + option dynamics. Combination of long ATM call and short ATM put.
|
|
DataField: put_breakeven_180
|
|
DataFieldDescription: Price at which a stock's put options with expiration 180 days in the future break even based on its recent bid/ask mean.
|
|
DataField: fnd6_esopct
|
|
DataFieldDescription: Common ESOP Obligation - Total
|
|
DataField: fnd6_newqeventv110_prcpd12
|
|
DataFieldDescription: Core Post-Retirement Adjustment 12MM Diluted EPS Effect Preliminary
|
|
DataField: fnd6_ciother
|
|
DataFieldDescription: Comp. Inc. - Other Adj.
|
|
DataField: fnd6_newa1v1300_aco
|
|
DataFieldDescription: Current Assets - Other - Total
|
|
DataField: fnd6_newa2v1300_spced
|
|
DataFieldDescription: S&P Core Earnings EPS Diluted
|
|
DataField: fnd6_newqeventv110_pnc12
|
|
DataFieldDescription: Pension Core Adjustment - 12mm
|
|
DataField: fnd6_xaccq
|
|
DataFieldDescription: Accrued Expenses
|
|
DataField: fnd6_recd
|
|
DataFieldDescription: Receivables - Estimated Doubtful
|
|
DataField: fnd6_newa1v1300_cshi
|
|
DataFieldDescription: Common Shares Issued
|
|
DataField: fnd6_newqv1300_cisecglq
|
|
DataFieldDescription: Comp Inc - Securities Gains/Losses
|
|
DataField: fnd6_newa1v1300_cogs
|
|
DataFieldDescription: Cost of Goods Sold
|
|
DataField: receivable
|
|
DataFieldDescription: Receivables - Total
|
|
DataField: fnd6_rea
|
|
DataFieldDescription: Retained Earnings - Restatement
|
|
DataField: fnd6_optvolq
|
|
DataFieldDescription: Volatility - Assumption (%)
|
|
DataField: fnd6_dm
|
|
DataFieldDescription: Debt - Mortgages & Other Secured
|
|
DataField: fnd6_newqeventv110_lcoq
|
|
DataFieldDescription: Current Liabilities - Other - Total
|
|
DataField: fnd6_txfo
|
|
DataFieldDescription: Income Taxes - Foreign
|
|
DataField: fnd6_newqv1300_acomincq
|
|
DataFieldDescription: Accumulated Other Comprehensive Income (Loss)
|
|
DataField: fnd6_txfed
|
|
DataFieldDescription: Income Taxes - Federal
|
|
DataField: fnd6_dltr
|
|
DataFieldDescription: Long-Term Debt - Reduction
|
|
DataField: fnd6_newqv1300_xoptq
|
|
DataFieldDescription: Implied Option Expense
|
|
DataField: fnd6_newqv1300_xsgaq
|
|
DataFieldDescription: Selling, General and Administrative Expenses
|
|
DataField: fnd6_newqeventv110_glcea12
|
|
DataFieldDescription: Gain/Loss on Sale (Core Earnings Adjusted) After-tax 12MM
|
|
DataField: fnd6_newa2v1300_oiadp
|
|
DataFieldDescription: Operating Income After Depreciation
|
|
DataField: fnd6_divd
|
|
DataFieldDescription: Cash Dividends - Daily
|
|
DataField: fnd6_dd3
|
|
DataFieldDescription: Debt Due in 3rd Year
|
|
DataField: fnd6_newa1v1300_aocidergl
|
|
DataFieldDescription: Accum Other Comp Inc - Derivatives Unrealized Gain/Loss
|
|
DataField: fnd6_cisecgl
|
|
DataFieldDescription: Comp Inc - Securities Gains/Losses
|
|
DataField: fnd6_adesinda_curcd
|
|
DataFieldDescription: ISO Currency Code - Company Annual Market
|
|
DataField: fnd6_mfma1_dp
|
|
DataFieldDescription: Depreciation and Amortization
|
|
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_qfv4_eps_mean
|
|
DataFieldDescription: Earnings per share - mean of estimations
|
|
DataField: min_gross_income_guidance
|
|
DataFieldDescription: The minimum guidance value for Gross Income.
|
|
DataField: cashflow_per_share_median_value
|
|
DataFieldDescription: Cash Flow Per Share - Median value among forecasts
|
|
DataField: anl4_qf_az_div_mean
|
|
DataFieldDescription: Dividend per share - average of estimations
|
|
DataField: free_cash_flow_per_share_reported_value
|
|
DataFieldDescription: Free cash flow per share- announced financial value
|
|
DataField: ebitda_reported_value
|
|
DataFieldDescription: EBITDA value for the quarter.
|
|
DataField: anl4_af_eps_value
|
|
DataFieldDescription: Earnings Per Share - Actual Value
|
|
DataField: anl4_ptpr_flag
|
|
DataFieldDescription: Reported Pretax income - forecast type (revision/new/...)
|
|
DataField: anl4_af_cfps_value
|
|
DataFieldDescription: Cash Flow Per Share - Actual Value
|
|
DataField: anl4_qf_az_wol_spe
|
|
DataFieldDescription: Earnings per share - The lowest estimation
|
|
DataField: anl4_capex_number
|
|
DataFieldDescription: Capital Expenditures - number of estimations
|
|
DataField: min_capital_expenditure_guidance
|
|
DataFieldDescription: Minimum guidance value for Capital Expenditures
|
|
DataField: anl4_fcf_high
|
|
DataFieldDescription: Free cash flow - aggregation on estimations, max
|
|
DataField: anl4_bvps_low
|
|
DataFieldDescription: Book value - the lowest estimation, per share
|
|
DataField: min_tangible_book_value_per_share_guidance
|
|
DataFieldDescription: Tangible Book Value per Share - minimum guidance value
|
|
DataField: anl4_basicdetaillt_person
|
|
DataFieldDescription: Broker Id
|
|
DataField: anl4_eaz2lrec_person
|
|
DataFieldDescription: Broker Id
|
|
DataField: min_pretax_profit_guidance_2
|
|
DataFieldDescription: The minimum guidance value for Pretax income on an annual basis.
|
|
DataField: anl4_bvps_flag
|
|
DataFieldDescription: Book value per share - forecast type (revision/new/...)
|
|
DataField: anl4_cfi_number
|
|
DataFieldDescription: Cash Flow From Investing - number of estimations
|
|
DataField: sales_max_guidance_value
|
|
DataFieldDescription: Maximum guidance value for annual sales
|
|
DataField: est_fcf_ps
|
|
DataFieldDescription: Free Cash Flow Per Share - Mean of Estimations
|
|
DataField: anl4_cuo1guidaf_item
|
|
DataFieldDescription: Financial item
|
|
DataField: dividend_min_guidance_value
|
|
DataFieldDescription: Minimum guidance value for Dividend per share on an annual basis
|
|
DataField: anl4_netdebt_mean
|
|
DataFieldDescription: Net debt - mean of estimations
|
|
DataField: anl4_qfd1_az_div_number
|
|
DataFieldDescription: Dividend per share - number of estimations
|
|
DataField: min_ebit_guidance
|
|
DataFieldDescription: Minimum guidance value for Earnings Before Interest and Taxes (EBIT)
|
|
DataField: min_free_cash_flow_guidance
|
|
DataFieldDescription: The minimum guidance value for Free Cash Flow on an annual basis.
|
|
DataField: anl4_afv4_div_high
|
|
DataFieldDescription: Dividend per share - The highest estimation for the annual forecast.
|
|
DataField: shareholders_equity_actual_value
|
|
DataFieldDescription: Shareholders' Equity - Total Value
|
|
DataField: pv13_hierarchys32_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_rha2_min2_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min51_f1_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min5_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_h_min30_3000_mapped_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy2_min2_1k_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_new_1l_scibr
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_3l_scibr
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min20_3k_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_new_6l_scibr
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_r2_min2_1000_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min51_f1_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_revere_comproduct_company
|
|
DataFieldDescription: Company product
|
|
DataField: pv13_custretsig_retsig
|
|
DataFieldDescription: Sign of customer return
|
|
DataField: pv13_r2_min5_1000_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_reveremap
|
|
DataFieldDescription: Mapping data
|
|
DataField: pv13_hierarchy_min10_sector_3000_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_revere_level
|
|
DataFieldDescription: Level of the sector within the hierarchy
|
|
DataField: pv13_hierarchy_min2_pureplay_only_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min100_corr21_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_ustomergraphrank_page_rank
|
|
DataFieldDescription: the PageRank of customers
|
|
DataField: pv13_hierarchy_min2_focused_pureplay_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_h_min2_focused_pureplay_3000_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_hierarchy_min2_focused_only_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_revere_country
|
|
DataFieldDescription: Country code
|
|
DataField: pv13_reportperiodlen
|
|
DataFieldDescription: The number of units which the report covers prior to the stated end date
|
|
DataField: pv13_rha2_min10_3000_513_sector
|
|
DataFieldDescription: grouping fields
|
|
DataField: pv13_revere_key_sector_total
|
|
DataFieldDescription: Number of key focus sectors for the company
|
|
DataField: rel_ret_comp
|
|
DataFieldDescription: Averaged one-day return of the competing companies
|
|
DataField: pv13_5l_scibr
|
|
DataFieldDescription: grouping fields
|
|
DataField: implied_volatility_mean_skew_90
|
|
DataFieldDescription: At-the-money option-implied volatility mean skew for 90 days
|
|
DataField: implied_volatility_put_1080
|
|
DataFieldDescription: At-the-money option-implied volatility for Put Option for 3 years
|
|
DataField: implied_volatility_put_120
|
|
DataFieldDescription: At-the-money option-implied volatility for Put Option for 120 days
|
|
DataField: implied_volatility_call_360
|
|
DataFieldDescription: At-the-money option-implied volatility for call Option for 360 days
|
|
DataField: implied_volatility_mean_120
|
|
DataFieldDescription: At-the-money option-implied volatility mean for 120 days
|
|
DataField: implied_volatility_mean_1080
|
|
DataFieldDescription: At-the-money option-implied volatility mean for 3 years
|
|
DataField: parkinson_volatility_180
|
|
DataFieldDescription: Parkinson model's historical volatility over 180 days
|
|
DataField: implied_volatility_call_60
|
|
DataFieldDescription: At-the-money option-implied volatility for call Option for 60 days
|
|
DataField: parkinson_volatility_150
|
|
DataFieldDescription: Parkinson model's historical volatility over 150 days
|
|
DataField: implied_volatility_put_90
|
|
DataFieldDescription: At-the-money option-implied volatility for Put Option for 90 days
|
|
DataField: implied_volatility_mean_270
|
|
DataFieldDescription: At-the-money option-implied volatility mean for 270 days
|
|
DataField: implied_volatility_call_270
|
|
DataFieldDescription: At-the-money option-implied volatility for call Option for 270 days
|
|
DataField: historical_volatility_150
|
|
DataFieldDescription: Close-to-close Historical volatility over 150 days
|
|
DataField: implied_volatility_call_20
|
|
DataFieldDescription: At-the-money option-implied volatility for call Option for 20 days
|
|
DataField: implied_volatility_put_30
|
|
DataFieldDescription: At-the-money option-implied volatility for Put Option for 30 days
|
|
DataField: implied_volatility_call_10
|
|
DataFieldDescription: At-the-money option-implied volatility for call Option for 10 days
|
|
DataField: implied_volatility_mean_skew_180
|
|
DataFieldDescription: At-the-money option-implied volatility mean skew for 180 days
|
|
DataField: implied_volatility_put_10
|
|
DataFieldDescription: At-the-money option-implied volatility for Put Option for 10 days
|
|
DataField: implied_volatility_put_360
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|
DataFieldDescription: At-the-money option-implied volatility for Put Option for 360 days
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|
DataField: historical_volatility_120
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|
DataFieldDescription: Close-to-close Historical volatility over 120 days
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DataField: implied_volatility_mean_skew_10
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|
DataFieldDescription: At-the-money option-implied volatility mean skew for 10 days
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|
DataField: historical_volatility_20
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|
DataFieldDescription: Close-to-close Historical volatility over 20 days
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DataField: implied_volatility_mean_20
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|
DataFieldDescription: At-the-money option-implied volatility mean for 20 days
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|
DataField: historical_volatility_30
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|
DataFieldDescription: Close-to-close Historical volatility over 30 days
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DataField: implied_volatility_mean_skew_720
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|
DataFieldDescription: At-the-money option-implied volatility mean skew for 720 days
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|
DataField: historical_volatility_10
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|
DataFieldDescription: Close-to-close Historical volatility over 10 days
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|
DataField: implied_volatility_mean_skew_60
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|
DataFieldDescription: At-the-money option-implied volatility mean skew for 60 days
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DataField: implied_volatility_call_150
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|
DataFieldDescription: At-the-money option-implied volatility for call Option for 150 days
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DataField: implied_volatility_mean_skew_120
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|
DataFieldDescription: At-the-money option-implied volatility mean skew for 120 days
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DataField: parkinson_volatility_30
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DataFieldDescription: Parkinson model's historical volatility over 30 days
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DataField: nws12_prez_02l
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DataFieldDescription: Number of minutes that elapsed before price went up 20 percentage points
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DataField: news_mins_20_chg
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|
DataFieldDescription: The minimum of L or S above for 20-minute bucket
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DataField: nws12_mainz_mainvwap
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DataFieldDescription: Main session volume weighted average price
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DataField: nws12_prez_57s
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DataFieldDescription: Number of minutes that elapsed before price went down 7.5 percentage points
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DataField: nws12_prez_eodclose
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DataFieldDescription: Close price of the session
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DataField: nws12_afterhsz_1_minute
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DataFieldDescription: The percent change in price in the first minute following the news release
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DataField: news_ls
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DataFieldDescription: Whether a long or short position would have been more advantageous: If (EODHigh - Last) > (Last - EODLow) Then LS = 1; If (EODHigh - Last) = (Last - EODLow) Then LS= 0; If (EODHigh - Last) < (Last - EODLow) Then LS = -1.
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DataField: nws12_prez_prevwap
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DataFieldDescription: Pre-session volume weighted average price
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DataField: nws12_afterhsz_41rta
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DataFieldDescription: 14-day Average True Range
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DataField: nws12_allz_result1
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DataFieldDescription: Percent change between the price at the time of the news release and the price at the close of the session
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DataField: news_mins_3_pct_dn
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|
DataFieldDescription: Number of minutes that elapsed before price went down 3 percentage points
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DataField: nws12_afterhsz_tonlast
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|
DataFieldDescription: Price at the time of news
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DataField: news_low_exc_stddev
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DataFieldDescription: (TONLast - EODLow) / StdDev, where StdDev is one standard deviation for the close price for 30 calendar days
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DataField: nws12_mainz_newrecord
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|
DataFieldDescription: Tracks whether the news is first instance or a duplicate
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DataField: news_indx_perf
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DataFieldDescription: ((EODClose - TONLast) / TONLast) - ((SPYClose - SPYLast) / SPYLast)
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DataField: nws12_prez_1s
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|
DataFieldDescription: Number of minutes that elapsed before price went down 1 percentage point
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|
DataField: nws12_prez_open_vol
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|
DataFieldDescription: Main open volume
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|
DataField: nws12_mainz_close_vol
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|
DataFieldDescription: Main close volume
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|
DataField: news_mins_7_5_pct_up
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|
DataFieldDescription: Number of minutes that elapsed before price went up 7.5 percentage points
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|
DataField: nws12_afterhsz_5_min
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|
DataFieldDescription: The percent change in price in the first 5 minutes following the news release
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|
DataField: nws12_afterhsz_4p
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|
DataFieldDescription: The minimum of L or S above for 4-minute bucket
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|
DataField: nws12_afterhsz_30_min
|
|
DataFieldDescription: The percent change in price in the first 30 minutes following the news release
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|
DataField: news_pct_30min
|
|
DataFieldDescription: The percent change in price in the first 30 minutes following the news release
|
|
DataField: nws12_prez_5s
|
|
DataFieldDescription: Number of minutes that elapsed before price went down 5 percentage points
|
|
DataField: nws12_mainz_02l
|
|
DataFieldDescription: Number of minutes that elapsed before price went up 20 percentage points
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|
DataField: nws12_afterhsz_02l
|
|
DataFieldDescription: Number of minutes that elapsed before price went up 20 percentage points
|
|
DataField: news_mins_3_pct_up
|
|
DataFieldDescription: Number of minutes that elapsed before price went up 3 percentage points
|
|
DataField: nws12_afterhsz_rangeamt
|
|
DataFieldDescription: Session High Price - Session Low Price
|
|
DataField: news_max_dn_ret
|
|
DataFieldDescription: Percent change from the price at the time of the news to the after the news low
|
|
DataField: nws12_afterhsz_eodclose
|
|
DataFieldDescription: Close price 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_price
|
|
DataFieldDescription: Composite sentiment score of stock price news
|
|
DataField: rp_css_partner
|
|
DataFieldDescription: Composite sentiment score of partnership news
|
|
DataField: rp_ess_technical
|
|
DataFieldDescription: Event sentiment score based on technical analysis
|
|
DataField: rp_css_ptg
|
|
DataFieldDescription: Composite sentiment score of price target news
|
|
DataField: rp_ess_earnings
|
|
DataFieldDescription: Event sentiment score of earnings news
|
|
DataField: rp_css_dividends
|
|
DataFieldDescription: Composite sentiment score of dividends news
|
|
DataField: rp_css_assets
|
|
DataFieldDescription: Composite sentiment score of assets news
|
|
DataField: nws18_qcm
|
|
DataFieldDescription: News sentiment of relevant news with high confidence
|
|
DataField: rp_ess_assets
|
|
DataFieldDescription: Event sentiment score of assets news
|
|
DataField: nws18_ghc_lna
|
|
DataFieldDescription: Change in analyst recommendation
|
|
DataField: rp_css_credit_ratings
|
|
DataFieldDescription: Composite sentiment score of credit ratings news
|
|
DataField: rp_nip_product
|
|
DataFieldDescription: News impact projection of product and service-related news
|
|
DataField: rp_css_credit
|
|
DataFieldDescription: Composite sentiment score of credit news
|
|
DataField: rp_ess_price
|
|
DataFieldDescription: Event sentiment score of stock price news
|
|
DataField: rp_nip_inverstor
|
|
DataFieldDescription: News impact projection of investor relations news
|
|
DataField: rp_nip_technical
|
|
DataFieldDescription: News impact projection based on technical analysis
|
|
DataField: rp_css_mna
|
|
DataFieldDescription: Composite sentiment score of mergers and acquisitions-related news
|
|
DataField: rp_nip_price
|
|
DataFieldDescription: News impact projection of stock price news
|
|
DataField: rp_ess_equity
|
|
DataFieldDescription: Event sentiment score of equity action news
|
|
DataField: rp_css_marketing
|
|
DataFieldDescription: Composite sentiment score of marketing news
|
|
DataField: rp_ess_insider
|
|
DataFieldDescription: Event sentiment score of insider trading news
|
|
DataField: rp_css_insider
|
|
DataFieldDescription: Composite sentiment score of insider trading news
|
|
DataField: rp_nip_marketing
|
|
DataFieldDescription: News impact projection of marketing news
|
|
DataField: nws18_sse
|
|
DataFieldDescription: Sentiment of phrases impacting the company
|
|
DataField: rp_css_technical
|
|
DataFieldDescription: Composite sentiment score based on technical analysis
|
|
DataField: rp_ess_mna
|
|
DataFieldDescription: Event sentiment score of mergers and acquisitions-related news
|
|
DataField: rp_ess_ratings
|
|
DataFieldDescription: Event sentiment score of analyst ratings-related news
|
|
DataField: rp_nip_credit
|
|
DataFieldDescription: News impact projection of credit news
|
|
DataField: rp_nip_dividends
|
|
DataFieldDescription: News impact projection of dividends news
|
|
DataField: rp_nip_business
|
|
DataFieldDescription: News impact projection of business-related news
|
|
DataField: fn_allocated_share_based_compensation_expense_q
|
|
DataFieldDescription: Represents the expense recognized during the period arising from equity-based compensation arrangements (for example, shares of stock, units, stock options, or other equity instruments) with employees, directors, and certain consultants qualifying for treatment as employees.
|
|
DataField: fn_income_from_equity_investments_q
|
|
DataFieldDescription: Income From Equity Method Investments
|
|
DataField: fn_assets_fair_val_l1_q
|
|
DataFieldDescription: Asset Fair Value, Recurring, Level 1
|
|
DataField: fnd2_a_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_comp_non_opt_vested_q
|
|
DataFieldDescription: The number of equity-based payment instruments, excluding stock (or unit) options, that vested during the reporting period.
|
|
DataField: fn_finite_lived_intangible_assets_acq_q
|
|
DataFieldDescription: Amount of assets, excluding financial assets and goodwill, lacking physical substance with a finite life acquired.
|
|
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_propplteqmuflmameqmt
|
|
DataFieldDescription: PPE, Equipment, Useful Life, Maximum
|
|
DataField: fnd2_eixrtreclstatelocalitxes
|
|
DataFieldDescription: Percentage 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 applicable to state and local income tax expense (benefit), net of federal tax expense (benefit).
|
|
DataField: fn_avg_diluted_sharesout_adj_a
|
|
DataFieldDescription: The sum of dilutive potential common shares or units used in the calculation of the diluted per-share or per-unit computation.
|
|
DataField: fn_def_income_tax_expense_q
|
|
DataFieldDescription: Income Tax Expense, Deferred
|
|
DataField: fnd2_dfdtxastxdfdexprssaccrs
|
|
DataFieldDescription: Amount before allocation of valuation allowances of deferred tax asset attributable to deductible temporary differences from reserves and accruals.
|
|
DataField: fn_comp_options_grants_fair_value_q
|
|
DataFieldDescription: Annual Share-Based Compensation Arrangement by Share-Based Payment Award Options Grants in Period Weighted Average Grant Date Fair Value
|
|
DataField: fn_repurchased_shares_a
|
|
DataFieldDescription: Number of shares that have been repurchased during the period.
|
|
DataField: fnd2_a_gsles1xtinguishmentofd
|
|
DataFieldDescription: Difference between the fair value of payments made and the carrying amount of debt which is extinguished prior to maturity.
|
|
DataField: fn_liab_fair_val_l2_q
|
|
DataFieldDescription: Liabilities Fair Value, Recurring, Level 2
|
|
DataField: fn_comp_options_exercisable_number_q
|
|
DataFieldDescription: The number of shares into which fully or partially vested stock options outstanding as of the balance sheet date can be currently converted under the option plan.
|
|
DataField: fn_proceeds_from_stock_options_exercised_q
|
|
DataFieldDescription: The cash inflow associated with the amount received from holders exercising their stock options. This item inherently excludes any excess tax benefit, which the entity may have realized and reported separately.
|
|
DataField: fn_op_lease_min_pay_due_in_2y_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 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: fn_comp_options_out_weighted_avg_a
|
|
DataFieldDescription: Weighted average price at which grantees can acquire the shares reserved for issuance under the stock option plan.
|
|
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_sbcpnargmsptawervl
|
|
DataFieldDescription: Amount of accumulated difference between fair value of underlying shares on dates of exercise and exercise price on options exercised (or share units converted) into shares.
|
|
DataField: fn_employee_related_liab_q
|
|
DataFieldDescription: Total of the carrying values as of the balance sheet date of obligations incurred through that date and payable for obligations related to services received from employees, such as accrued salaries and bonuses, payroll taxes and fringe benefits. For classified balance sheets, used to reflect the current portion of the liabilities (due within 1 year or within the normal operating cycle if longer); for unclassified balance sheets, used to reflect the total liabilities (regardless of due date).
|
|
DataField: fnd2_a_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_comp_options_grants_a
|
|
DataFieldDescription: Net number of share options (or share units) granted during the period.
|
|
DataField: fn_oth_comp_forfeitures_fair_value_a
|
|
DataFieldDescription: Annual Share Based Compensation Equity Instruments Other Than Options Forfeitures Weighted Average Grant Date Fair Value
|
|
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: 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: fn_proceeds_from_issuance_of_debt_a
|
|
DataFieldDescription: The cash inflow during the period from additional borrowings in aggregate debt. Includes proceeds from short-term and long-term debt.
|
|
DataField: fn_def_tax_assets_net_q
|
|
DataFieldDescription: Deferred Tax Assets Net Of Valuation Allowance
|
|
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 =======================================
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