Cvar-Based Robust Models For Portfolio Selection - Sun, Y.; Aw, E.L.G.; Li, Bin; Teo, Kok Lay; Sun, Jie (AMER INST MATHEMATICAL SCIENCES-AIMS, 2020)
This study relaxes the distributional assumption of the return of the risky asset, to arrive at the optimal portfolio. Studies of portfolio selection models have typically assumed that stock returns conform to the normal distribution. The application of robust optimization techniques means that only the historical mean and variance of asset returns are required instead of distributional information. We show that the method results in an optimal portfolio that has comparable return and yet equivalent risk, to one that assumes normality of asset returns.