We derive empirical tests for the mean-variance efficiency of a given portfolio. The tests can be computed using straightforward linear programming, and they give substantial flexibility in modeling the investment possibilities. Using this test, we can reject the hypothesis that the S&P 500...

We derive empirical tests for the mean-variance efficiency of a given portfolio. The tests can be computed using straightforward linear programming, and they give substantial flexibility in modeling the investment possibilities. Using this test, we can reject the hypothesis that the S&P 500...

In this paper, we present a recurrent neural network for solving mixed linear complementarity problems (MLCPs) with positive semi-definite matrices. The proposed neural network is derived based on an NCP function and has a low complexity respect to the other existing models. In theoretical and...