股票预期收益的横截面与特质波动率的组成

Seyed Reza Tabatabaei Poudeh, Chengbo Fu
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引用次数: 3

摘要

本文的目的是通过研究股票收益与组合和公司层面上股票收益方差分解所得成分之间的关系,为现有的股票收益可预测性和特质风险文献做出贡献。设计/方法/方法:采用有条件的Fama-French三因素模型,利用理论模型将股票收益的方差分解为两个波动项和两个协方差项。本研究采用投资组合分析和Fama-MacBeth横断面回归来检验特质风险成分与股票预期收益之间的关系。研究结果表明,波动性项与股票预期收益呈负相关,alpha风险与股票收益的关系最为显著。相反,在投资组合水平上,协方差项与预期股票收益呈正相关。此外,Fama-MacBeth横截面回归的结果表明,只有α风险可以解释股票收益在公司层面的变化。另一个发现是,当波动率和协方差项被排除在特质波动率之外时,特质波动率与股票收益之间的关系在投资组合水平上变得微弱,在公司水平上消失。原创性/价值这是第一个在等加权和价值加权投资组合中检验特质风险的所有组成部分与预期股票回报之间关系的研究。本研究还提出协方差项的特质波动率作为新的预测股票收益在投资组合水平。此外,本文通过检验所有四个附加成分是否都解释了无条件特质风险中包含的所有系统模式,为特质风险文献做出了贡献。
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The Cross-section of Expected Stock Returns and Components of Idiosyncratic Volatility
PurposeThe purpose of this paper is to contribute to the existing stock return predictability and idiosyncratic risk literature by examining the relationship between stock returns and components derived from the decomposition of stock returns variance at the portfolio and firm levels.Design/methodology/approachA theoretical model is used to decompose the variance of stock returns into two volatility and two covariance terms by using a conditional Fama-French three-factor model. This study adopts portfolio analysis and Fama-MacBeth cross-sectional regression to examine the relationship between components of idiosyncratic risk and expected stock returns.FindingsThe portfolio analysis results show that volatility terms are negatively related to expected stock returns, and alpha risk has the most significant relationship with stock returns. On the contrary, covariance terms have positive relationships with expected stock returns at the portfolio level. Furthermore, the results of the Fama-MacBeth cross-sectional regression show that only alpha risk can explain variations in stock returns at the firm level. Another finding is that when volatility and covariance terms are excluded from idiosyncratic volatility, the relation between idiosyncratic volatility and stock returns becomes weak at the portfolio level and disappears at the firm level.Originality/valueThis is the first study that examines the relations between all the components of idiosyncratic risk and expected stock returns in equal-weighted and value-weighted portfolios. This research also suggests covariance terms of idiosyncratic volatility as new predictors of stock returns at the portfolio level. Moreover, this paper contributes to the idiosyncratic risk literature by examining whether all the four additional components explain all the systematic patterns included in the unconditional idiosyncratic risk.
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