A robust portfolio selection model with probability constraints is established under the assumptions that
parameters of model vary in a joint ellipsoidal uncertainty set. Then the proposed problem is converted into a convex
programming problem with LMI constraints that can be solved by using interior point algorithms. The empirical analysis
and comparisons from the real market data indicate that the proposed model can obtain a portfolio strategy with the better
wealth growth rate and diversify the risk of the optimal portfolio efficiently.