Right tail information and asset pricing

Abstract

Abstract The right tail of the distribution of financial variables provides important information to investors and decision-makers. In this paper, we study the role of the right tail distributional information in finance. First, we propose semiparametric estimators for the right tail mean (RTM) and right tail variance (RTV). The proposed estimators use parsimonious parametric models to capture the dynamics of the data, and also allow for nonparametric flexibility in the distribution. These estimators can be estimated at the rate of root-T and are asymptotically normal. We then conduct a comparative study on the dynamics and empirical feature of the RTM and RTV in two international equity markets: The US and The Chinese stock markets. Third, we study the effect of right tail measures in the cross-sectional pricing of stock returns. Our empirical investigation indicates that the right tail information plays a significant role in explaining the cross-section pricing of stock returns. In addition, the RTV and left tail variance (LTV) have opposite impacts on asset prices. Finally, we use simulation based analysis to examine the impact of RTM on the optimal investment strategy. Our results have important implications for portfolio management in financial market.