Robust CVaR Approach to Portfolio Selection with Uncertain Exit Time

In this paper we explore the portfolio selection problem involving an uncertain time of eventual exit. To deal with this uncertainty, the worst-case CVaR methodology is adopted in the case where no or only partial information on the exit time is available, and the corresponding problems are integrated into linear programs which can be efficiently solved. Moreover, we present a method for specifying the uncertain information on the distribution of the exit time associated with exogenous and endogenous incentives. Numerical experiments with real market data and Monte Carlo simulation show the usefulness of the proposed model.