Unique Factors

Yiyu Shen, Yexiao Xu
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引用次数: 1

Abstract

It is well known that 70% of individual stocks' returns are classified as idiosyncratic returns under a conventional asset pricing model. In this study, we raise an important question as to whether majority return variations are truly influenced by idiosyncratic risks that at most affect several stocks from an empirical perspective. In other words, we explore a possible middle ground between common risk factors that influence almost all stocks and idiosyncratic risks by proposing unique factors that may only affect certain groups of stocks. In particular, we present a simple iterative approach both to extract unique factors from individual stock returns and to group stocks simultaneously. Comparing with industry groupings, this approach not only allows for a parsimonious group structure but also ensures that unique factors are indeed unique to individual groups. With the deterioration in the explanatory power of common factors such as the Fama and French factors in recent years, we find that unique factors not only are pervasive within their groups but also have played an increasingly important role in explaining individual stock returns over the past forty years. As an example, a multifactor model with two common factors and two unique factors not only provides a 10% extra explanatory power over other popular models but also outperforms the Fama and French model in out-of-sample tests. Therefore, the simple structure of unique factor model may hold the key to improve the performance of an asset pricing model in general.
独特的因素
众所周知,在传统的资产定价模型下,70%的个股回报被归类为特殊回报。在本研究中,我们提出了一个重要的问题,即从经验的角度来看,大多数回报变化是否真的受到最多影响几只股票的特质风险的影响。换句话说,我们通过提出可能仅影响某些股票组的独特因素,在影响几乎所有股票的共同风险因素和特殊风险之间探索可能的中间地带。特别是,我们提出了一种简单的迭代方法,既可以从个股收益中提取独特的因素,又可以同时对股票进行分组。与行业分组相比,这种方法不仅允许一个简约的组结构,而且还确保独特的因素确实是个别组所独有的。随着Fama因子和French因子等共同因子近年来解释力的减弱,我们发现独特因子不仅在其群体内普遍存在,而且在解释过去40年个股收益方面发挥着越来越重要的作用。作为一个例子,一个包含两个共同因素和两个独特因素的多因素模型不仅比其他流行的模型提供了10%的额外解释能力,而且在样本外检验中优于Fama和French模型。因此,独特因子模型的简单结构可能是提高一般资产定价模型绩效的关键。
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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