High Idiosyncratic Volatility and Low Returns: International and Further U.S. Evidence

Abstract

Stocks with high idiosyncratic volatility have low expected returns around the world. This effect is individually significant in each G7 country. Across 23 developed markets, the difference in average returns between the extreme quintile portfolios sorted on idiosyncratic volatility is -1.31% per month, after controlling for world market, size, and value factors. In the U.S., we rule out explanations based on trading frictions, information dissemination, and higher moments. There is strong comovement in the low returns to high idiosyncratic volatility stocks across countries, suggesting that broad, not easily diversifiable factors lie behind this phenomenon.

Dynamic Conditional Beta Is Alive and Well in the Cross-Section of Daily Stock Returns

“…The average slopes on REV are negative and highly significant, implying that the largest 500 and 1,000 stocks exhibit strong short-term reversals. Consistent with the findings of Ang, Hodrick, Xing, and Zhang (2006) and Bali, Cakici, and Whitelaw (2011), the average slopes on IVOL and MAX are negative and significant. Similar to our earlier findings from the S&P 500 stocks, the average slopes on ILLIQ (COSKEW) are positive (negative) for the largest 500 and 1,000 stocks, but they are statistically insignificant.…”

“…short-term reversal (Jegadeesh (1990)), liquidity (Amihud (2002)), co-skewness (Harvey and Siddique (2000)), volatility (Ang, Hodrick, Xing, andZhang (2006, 2009)), and preference for lottery-like assets (Bali, Cakici, and Whitelaw (2011)) generate very similar results.…”

“…Harvey and Siddique (2000), Ang, Hodrick, Xing, and Zhang (2006), and Bali, Cakici, and Whitelaw (2011) show that the stocks with high co-skew, high volatility, and high MAX are expected to generate lower return in the future. However, the stocks in the High DCC-beta decile with higher co-skew, higher volatility, and higher MAX have higher average return than the stocks in the Low DCC-beta decile with lower co-skew, lower volatility, and lower MAX.…”

“…Idiosyncratic Volatility: Following Ang, Hodrick, Xing, and Zhang (2006), the daily idiosyncratic volatility of stock i (IVOL) is computed as the standard deviation of the residuals from the regression using daily returns over the prior 21 trading days:…”

Have We Solved the Idiosyncratic Volatility Puzzle?

“…Most studies in this literature typically 1 Ang, Hodrick, Xing, and Zhang (2009) show that the relation also exists in international markets. 2 The long list of candidate explanations includes those based on expected idiosyncratic skewness (Boyer, Mitton, and Vorkink (2010)), coskewness (Chabi-Yo and Yang (2009)), maximum daily return (Bali, Cakici, and Whitelaw (2011)), retail trading proportion (Han and Kumar (2013)), one-month return reversal (Fu (2009) and Huang, Liu, Rhee, and Zhang (2009)), illiquidity (Bali and Cakici (2008) and Han and Lesmond (2011)), uncertainty (Johnson (2004)), average variance beta (Chen and Petkova (2012)), and earnings surprises (Jiang, Xu, and Yao (2009) and Wong (2011)).…”