Idiosyncratic skewness;
Good volatility;
Bad volatility;
Cross-sectional stock returns;
Risk factors;
Growth options;
CONDITIONAL SKEWNESS;
GROWTH OPTIONS;
PAST RETURNS;
LOTTERIES;
RISK;
INVESTMENT;
D O I:
10.1016/j.jbankfin.2024.107343
中图分类号:
F8 [财政、金融];
学科分类号:
0202 ;
摘要:
We decompose the idiosyncratic volatility of stock returns into "good"and "bad"volatility components, which are associated with positive and negative returns, respectively. Using firm characteristics, we estimate across- sectional model for the expected idiosyncratic good minus bad volatility (EIGMB). The EIGMB outperforms expected idiosyncratic skewness (EISKEW) and standard time-series models in capturing conditional idiosyncratic return asymmetry. EIGMB is negatively and significantly associated with future stock returns, even after controlling for EIKSEW and exposure to systematic-skewness-related factors. Separating the role each specific characteristic plays in driving the predictive power of EIGMB for returns, we find that return on equity and momentum are two important elements of variation in EIGMB.
机构:
Yale Univ, Sch Management, New Haven, CT 06520 USAYale Univ, Sch Management, New Haven, CT 06520 USA
Barberis, Nicholas
;
Huang, Ming
论文数: 0引用数: 0
h-index: 0
机构:
Cornell Univ, Johnson Sch, Ithaca, NY 14853 USA
Cheung Kong Grad Sch Business, Beijing, Peoples R ChinaYale Univ, Sch Management, New Haven, CT 06520 USA
机构:
Yale Univ, Sch Management, New Haven, CT 06520 USAYale Univ, Sch Management, New Haven, CT 06520 USA
Barberis, Nicholas
;
Huang, Ming
论文数: 0引用数: 0
h-index: 0
机构:
Cornell Univ, Johnson Sch, Ithaca, NY 14853 USA
Cheung Kong Grad Sch Business, Beijing, Peoples R ChinaYale Univ, Sch Management, New Haven, CT 06520 USA