Stochastic programming approach for portfolio selection with risk control of WCVaR

We focus on the multi-period optimal investment allocation in the sense of minimizing the worst-case conditional value-at-risk function. In order to control the downside risk during the whole journey of investment, we develop the optimal dynamic portfolio strategy model suited to the current situation in China with stochastic programming approach, in which the future scenarios of financial market are illustrated via applying the vector autoregressive method. Furthermore, we present the concrete Monte Carlo simulation steps for solving the model and then obtain the simulate solution of the optimal strategies combining the history data. Finally, we analyse the sensitivity of the parameter to the optimal portfolio strategies.