Journal of Financial Economics·Volume 128, Issue 1·April 2018

免除贝塔异象

作者🧬：Jianan Liu（The Wharton School, University of Pennsylvania）

Robert F. Stambaugh（Shanghai Advanced Institute of Finance, Shanghai Jiao Tong University）

Yu Yuan（Shanghai Advanced Institute of Finance, Shanghai Jiao Tong University）

摘要🧩：贝塔异象，即高（低）β值股票有负（正）的α值🦻🏼，这是源自β与特质波动率（IVOL）的正相关关系。特质波动率和阿尔法之间的相关性在低估股票中为正⛲️，但在高估股票中为负数并且更强（Stambaugh🚶‍♀️‍➡️，Yu和Yuan，2015）。这种更强的负向关系与正向的IVOL-β相关性结合产生了β异象。只有在高估股价过高的情况下🤸、以及β-IVOL相关性和价格过高的可能性同时偏高时🙎🏽🧑🏽‍🦳，这种异象才显著🤜。控制特质波动率或简单地排除高特质波动率的价格高估股票，都会使β异象不再显著🪅🎞。

关键词：贝塔，异象，波动率

Absolving beta of volatility’s effects

Jianan Liu（The Wharton School, University of Pennsylvania），Robert F. Stambaugh（Shanghai Advanced Institute of Finance, Shanghai Jiao Tong University）🧑🏿，Yu Yuan（Shanghai Advanced Institute of Finance, Shanghai Jiao Tong University）

ABSTRACT

The beta anomaly, negative (positive) alpha on stocks with high (low) beta, arises from beta’s positive correlation with idiosyncratic volatility (IVOL). The relation between IVOL and alpha is positive among underpriced stocks but negative and stronger among overpriced stocks (Stambaugh, Yu, and Yuan, 2015). That stronger negative relation combines with the positive IVOL-beta correlation to produce the beta anomaly. The anomaly is significant only within overpriced stocks and only in periods when the beta-IVOL correlation and the likelihood of overpricing are simultaneously high. Either controlling for IVOL or simply excluding overpriced stocks with high IVOL renders the beta anomaly insignificant.

Keywords：Beta, Anomaly, Volatility

原文链接🧗‍♂️：https://www.sciencedirect.com/science/article/pii/S0304405X18300163#!

翻译🦹🏼🫃🏻：何杉