Idiosyncratic Volatility and Skewness: Time Series Relations and the Cross-Section of Expected Returns
Investors with a preference for skewness may pay a premium for stocks with high idiosyncratic volatility because such stocks also offer high skewness. We find that lagged skewness alone is a weak predictor of expected skewness, and thus investors may rely on additional variables to forecast skewness. We estimate a model to forecast skewness and find that a number of variables suggested in the literature, especially idiosyncratic volatility, allow us to construct superior estimates of expected skewness. We find that controlling for expected skewness greatly reduces, both economically and statistically, the magnitude of the negative relationship between idiosyncratic volatility and expected returns.
Brian Boyer Todd Mitton Keith Vorkink
Marriott School, Brigham Young University, Provo, UT 84602 Marriott School, Brigham Young University, Provo, UT, 84602
国际会议
成都
英文
1-26
2007-07-09（万方平台首次上网日期，不代表论文的发表时间）