Valuation Ratios and Shape Predictability in the Distribution of Stock Returns
60 Pages Posted: 19 Dec 2016 Last revised: 22 Dec 2019
Date Written: December 20, 2019
While a large literature on return predictability has shown a link between valuation levels and expected rates of aggregate returns in-sample, we document a link between valuation levels and the shape of the distribution of cumulative (for example, over 12 and 24 months) total returns. Return distributions become more asymmetric and negatively skewed when valuation levels are high. In contrast, they are roughly symmetric when valuation levels are low. These results turn out to be very robust to alternative (a) measures of valuation levels, (b) model specifications and (c) equity markets (international and industry-level). Importantly, these findings shed light on how equity prices regress back to their means conditional on valuation levels, have important practical implications for risk measurement and asset management, and refine the well-known finding of negative skewness in aggregate returns. The model with conditional skewness also outperforms benchmark models assuming a symmetric or constant-skewness distribution in an out-of-sample setup. Our empirical results support theoretical asset pricing models that have asymmetric responses to shocks, such as stochastic bubbles, liquidity spirals or models with time-varying risk aversion.
Keywords: return predictability, valuation ratios, skewness
JEL Classification: G12, G17, C22
Suggested Citation: Suggested Citation