Finding Better Securities while Holding Portfolios:Is Stochastic Dominance the Answer?
研究提出边际条件随机占优（MCSD）方法，帮助投资经理在持有特定组合时筛选能改善业绩的证券，并与均值方差模型和CAPM比较。
Investment managers always look for securities to improve their portfolio performance and a common mechanism is the mean-variance (MV) model. As an alternative, Shalit proposes using marginal conditional stochastic dominance (MCSD), which ensures that all risk-averse investors benefit from the selection process by establishing the relative preference among stocks conditional on holding a specific portfolio. He describes the basic MCSD rules and applies them to large portfolios. The resulting preferred stocks are compared to the selection obtained using the mean-variance criterion and the CAPM. <b>TOPICS:</b>Portfolio construction, portfolio theory, risk management