Does Risk Seeking Drive Stock Prices? A Stochastic Dominance Analysis of Aggregate Investor Preferences and Beliefs

Abstract

We use various stochastic dominance criteria that account for (local) risk seeking to analyze market portfolio efficiency relative to benchmark portfolios formed on market capitalization, book-to-market equity ratio and price momentum. Our results suggest that reverse S-shaped utility functions with risk aversion for losses and risk seeking for gains can explain stock returns. The results are also consistent with a reverse S-shaped pattern of subjective probability transformation. The low average yield on big caps, growth stocks, and past losers may reflect investors` twin desire for downside protection in bear markets and upside potential in bull markets.

Keywords: time optimal control problems, Neumann parabolic equations with an infinite number of variables, Dubovitskii-Milyutin theorem, conical approximations, optimality conditions, Weierstrass theorem