A Portfolio Selection Strategy Using Genetic Relation Algorithm

This paper proposes a new strategy beta-GRA for portfolio selection in which the return and risk are considered as measures of strength in Genetic Relation Algorithm (GRA). Since the portfolio beta beta efficiently measures the volatility relative to the benchmark index or the capital market, beta is usually employed for portfolio evaluation or prediction, but scarcely for portfolio construction process. The main objective of this paper is to propose an integrated portfolio selection strategy, which selects stocks based on beta using GRA. GRA is a new evolutionary algorithm designed to solve the optimization problem due to its special structure. We illustrate the proposed strategy by experiments and compare the results with those derived from the traditional models.