Papers by Author: Yue Lin Gao

Abstract: This paper proposes the portfolio risk of tracking error based on CVaR, and gives the multi-stages index tracking model considering some real-world constraints. We use the observed historical data and econometric methods to estimate the parameters in our model, rather than assume the returns of risk asset follow some distributions, and use filtered historical simulation method to calculate the CVaR risk of the downside tracking error. We use PSO-DE hybrid algorithm for solving our model by using Shanghai security 50 index and stocks included by the index.

Abstract: A multi-objective particle swarm optimization with dynamic crowding entropy-based diversity measure is proposed in this paper. Firstly, the elitist strategy is used in external archive in order to improve the convergence of this algorithm. Then the new diversity strategy called dynamic crowding entropy strategy and the global optimization update strategy are used to ensure sufficient diversity and uniform distribution amongst the solution of the non-dominated fronts. The results show that the proposed algorithm is able to find better spread of solutions with the better convergence to the Pareto front and preserve diversity of Pareto optimal solutions the more efficiently.

Abstract: This paper presents an improve particle swarm optimization algorithm for solving the mixed nonlinear integer programming problems. In this algorithm, the mixed nonlinear integer programming problems is converted into unconstrained bi-objective optimization problem by the dynamic bi-objective constraint handling methods and improved the velocity equation of PSO. Introduction of migration operator in order to overcome the premature phenomenon, retention to the better performance of infeasible particles according to the constraint violation in each iteration, it is effectively maintain the swarm diversity. Numerical experiments show that the proposed algorithm has faster convergence speed and better ability of global optimization.