Maxing Out: Stocks as Lotteries and the Cross-Section of Expected Returns

Motivated by existing evidence of a preference among investors for assets with lottery-like payoffs and that many investors are poorly diversified, we investigate the significance of extreme positive returns in the cross-sectional pricing of stocks. Portfolio-level analyses and firm-level cross-sectional regressions indicate a negative and significant relation between the maximum daily return over the past one month(MAX) and expected stock returns. Average raw and risk-adjusted return differences between stocks in the lowest and highest MAX deciles exceed 1% per month. These results are robust to controls for size, book-to-market, momentum, short-term reversals, liquidity, and skewness. Of particular interest, including MAX generally subsumes or reverses the puzzling negative relation between returns and idiosyncratic volatility recently documented in Ang et al. (2006, 2008)

Hybrid Tail Risk and Expected Stock Returns: When Does the Tail Wag the Dog?

This paper introduces a new, hybrid measure of covariance risk in the lower tail of the stock return distribution, motivated by the under-diversified portfolio holdings of individual investors, and investigates its performance in predicting the cross-sectional variation in stock returns over the sample period July 1963-December 2009. Our key innovation is that the covariance is measured across the states of the world in which the individual stock return is in its left tail, not across the corresponding tail states for the market return as in standard systematic risk measures. The results indicate a positive and significant relation between what we label hybrid tail covariance risk (H-TCR) and expected stock returns, in contrast to the insignificant or negative results for purely stock-specific or standard systematic tail risk measures. A trading strategy that goes long stocks in the highest H-TCR decile and shorts stocks in the lowest H-TCR decile produces average raw and risk-adjusted returns of 6% to 8% per annum, consistent with results from a cross-sectional regression analysis that controls for a battery of known predictors

Maxing Out: Stocks as Lotteries and the Cross-Section of Expected Returns

Motivated by existing evidence of a preference among investors for assets with lottery-like payoffs and that many investors are poorly diversified, we investigate the significance of extreme positive returns in the cross-sectional pricing of stocks. Portfolio-level analyses and firm-level cross-sectional regressions indicate a negative and significant relation between the maximum daily return over the past one month (MAX) and expected stock returns. Average raw and risk-adjusted return differences between stocks in the lowest and highest MAX deciles exceed 1% per month. These results are robust to controls for size, book-to-market, momentum, short-term reversals, liquidity, and skewness. Of particular interest, including MAX reverses the puzzling negative relation between returns and idiosyncratic volatility recently documented in Ang et al. (2006, 2008).

Maxing Out: Stocks as Lotteries and the Cross-Section of Expected Returns

Motivated by existing evidence of a preference among investors for assets with lottery-like payoffs and that many investors are poorly diversified, we investigate the significance of extreme positive returns in the cross-sectional pricing of stocks. Portfolio-level analyses and firm-level cross-sectional regressions indicate a negative and significant relation between the maximum daily return over the past one month(MAX) and expected stock returns. Average raw and risk-adjusted return differences between stocks in the lowest and highest MAX deciles exceed 1% per month. These results are robust to controls for size, book-to-market, momentum, short-term reversals, liquidity, and skewness. Of particular interest, including MAX generally subsumes or reverses the puzzling negative relation between returns and idiosyncratic volatility recently documented in Ang et al. (2006, 2008)