英文标题：
《Dead Alphas as Risk Factors》
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作者：
Zura Kakushadze and Willie Yu
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最新提交年份：
2017
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英文摘要：
We give an explicit algorithm and source code for extracting equity risk factors from dead (a.k.a. \"flatlined\" or \"hockey-stick\") alphas and using them to improve performance characteristics of good (tradable) alphas. In a nutshell, we use dead alphas to extract directions in the space of stock returns along which there is no money to be made (and/or those bets are too volatile). In practice the number of dead alphas can be large compared with the number of underlying stocks and care is required in identifying the aforesaid directions.
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中文摘要：
我们给出了一个明确的算法和源代码，用于从死亡（又称“扁平”或“曲棍球棒”）Alpha中提取股票风险因素，并使用它们改善良好（可交易）Alpha的性能特征。简言之，我们使用死字母来提取股票回报空间中的方向，沿着这些方向没有钱可以赚（和/或那些赌注太不稳定）。实际上，与基础股票的数量相比，死亡Alpha的数量可能很大，在确定上述方向时需要谨慎。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Portfolio Management 项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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一级分类：Quantitative Finance 数量金融学
二级分类：Risk Management 风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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