Second-Order Stochastic Dominance, Reward-Risk Portfolio Selection, and the CAPM
从收益风险投资组合选择模型出发，推导出与经典均值方差资本资产定价模型类似的收益风险资本资产定价模型，并证明在完全市场中该模型可简化为代表性投资者模型，实证显示其比均值方差模型更好地解释美国股票收益的截面差异。
Abstract Starting from the reward-risk model for portfolio selection introduced in De Giorgi (2005), we derive the reward-risk Capital Asset Pricing Model (CAPM) analogously to the classical mean-variance CAPM. In contrast to the mean-variance model, reward-risk portfolio selection arises from an axiomatic definition of reward and risk measures based on a few basic principles, including consistency with second-order stochastic dominance. With complete markets, we show that at any financial market equilibrium, reward-risk investors' optimal allocations are comonotonic and, therefore, our model reduces to a representative investor model. Moreover, the pricing kernel is an explicitly given, non-increasing function of the market portfolio return, reflecting the representative investor's risk attitude. Finally, an empirical application shows that the reward-risk CAPM captures the cross section of U.S. stock returns better than the mean-variance CAPM does.