Target Return Strategy

Abstract

We study the target return strategy (TRS), which exits the market once the return reaches a preset target. We show that the holding-period return (HPR) cannot mean-variance dominate TRS, but TRS can mean-variance dominate HPR. We theoretically analyze TRS and quantitatively illustrate that training targets by a mean-variance utility optimization algorithm based on recent HPRs and peak returns can improve welfare. By exiting at targets, TRS preempts potential price reversals, manages investment risk, enhances risk-return profiles, and encourages market participation. TRS justifies the use of price-contingent orders, explains the disposition effect, and questions market efficiency.