Optimizing Portfolio Weights for the First Degree Stochastic Dominance with Maximum Expected Return

1차 확률적 지배를 하는 최대수익 포트폴리오 가중치의 탐색에 관한 연구

Unlike the mean-variance approach, the stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first degree stochastic dominance with maximum expected return by managing the constraint set and the objective function separately. An algorithm was developed and tested with promising results against Korean stock market data sets.