Factor Models for Alpha Streams

Zurab Kakushadze
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引用次数: 5

Abstract

We propose a framework for constructing factor models for alpha streams. Our motivation is threefold. 1) When the number of alphas is large, the sample covariance matrix is singular. 2) Its out-of-sample stability is challenging. 3) Optimization of investment allocation into alpha streams can be tractable for a factor model alpha covariance matrix. We discuss various risk factors for alphas such as: style risk factors; cluster risk factors based on alpha taxonomy; principal components; and also using the underlying tradables (stocks) as alpha risk factors, for which computing the factor loadings and factor covariance matrices does not involve any correlations with alphas, and their number is much larger than that of the relevant principal components. We draw insight from stock factor models, but also point out substantial differences.
Alpha流的因子模型
我们提出了一个构建α流因子模型的框架。我们的动机是三重的。1)当α数较大时,样本协方差矩阵为奇异。2)样品外稳定性具有挑战性。3)用因子模型α协方差矩阵求解α流投资配置优化问题。我们讨论了阿尔法的各种风险因素,如:风格风险因素;基于alpha分类法的风险因素聚类主成分;并将标的可交易证券(股票)作为alpha风险因子,其计算的因子负荷和因子协方差矩阵不涉及与alpha的任何相关性,其数量远远大于相关主成分的数量。我们从股票因素模型中获得了洞察力,但也指出了实质性的差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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