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Know Your VMS Exposure

机译:了解您的VMS暴露

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摘要

One of the ongoing debates in equity market research is the set of common factors that explains the cross section of individual stock returns. With the influential backing of Fama and French [1993], a three-factor model that includes the market, size, and value factors is frequently cited in academic research and widely used in portfolio management. More recently, momentum has joined the list of accepted factors, resulting in references to a four-factor model. Lately, security volatility has begun to be used, along with the factors just mentioned, in describing portfolio risk.The authors introduce a specific measure of the idiosyncratic volatility factor that mirrors the Fama-French methodology, calling it VMS for volatile-minus-stable stocks. VMS is calculated for the entire span of the CRSP database and found to have strong credentials. VMS seems to be more important than SMB (small-minus-big market capitalization) and HML (high-minus-low book-to-market ratio), and similar to UMD (up-minus-down past return) in explaining the covariance structure of stock returns. The relative importance of VMS holds over the entire history for which it can be measured in the U.S. market (1931-2008) and continues to be an important factor in the covariance structure of stock returns in recent decades (1983-2008). Volatility, however, is not very orthogonal to the more well-known factors, a desirable property for new factors. Specifically,VMS is highly correlated to the general market (e.g., volatile stocks outperform stable stocks when the general equity market goes up) despite the fact that the authors measure security volatility in a market-idiosyncratic setting.VMS is also positively correlated with SMB (e.g., volatile stocks tendrnto outperform when small-cap stocks outperform) despite the Fama-French process of double sorting on market capitalization. Finally,VMS is negatively correlated with HML (e.g., volatile stocks tend to outperform when growth stocks outperform) although this correlation was not pronounced until the last few decades. In contrast to the other Fama-French factors, the average return of the VMS factor has been close to zero over time and negative in recent decades.
机译:股市研究中正在进行的辩论之一是解释单个股票收益的横截面的一组共同因素。在Fama和French [1993]的有力支持下,包括市场,规模和价值因素在内的三因素模型在学术研究中经常被引用并广泛用于投资组合管理。最近,动量加入了公认的因素列表,从而引用了四因素模型。最近,安全波动率以及刚才提到的因素已被用于描述投资组合风险。作者介绍了一种反映Fama-French方法的特质波动率因素的特定度量,称其为VMS,表示波动率-负值稳定股票。 VMS是针对CRSP数据库的整个范围计算得出的,具有强大的凭据。在解释协方差时,VMS似乎比SMB(小市值-大市值)和HML(高市值-低市值比率)更重要,并且类似于UMD(过去收益率上下波动)股票收益的结构。 VMS的相对重要性在美国市场(1931-2008)可以衡量的整个历史上一直存在,并且在最近几十年(1983-2008)中仍然是股票收益的协方差结构的重要因素。但是,波动率与较知名的因素不是很正交,而较众所周知的因素是新因素的理想属性。具体来说,尽管作者在市场特殊情况下衡量证券的波动性,但VMS与普通市场高度相关(例如,当普通股票市场上涨时,波动性股票表现优于稳定股票)。VMS与SMB也呈正相关关系(例如,尽管Fama-French对市值进行了双重分类,但波动性股票往往在小盘股表现优于大盘时表现优于大盘。最后,VMS与HML呈负相关(例如,当成长型股票跑赢大市时,波动性股票往往跑赢大市),尽管这种相关性直到最近几十年才显现出来。与其他Fama-French因素相反,VMS因子的平均回报随着时间的流逝接近于零,近几十年来为负。

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