Compare Meta-heuristic Algorithms on Optimal Model of Multi Period Portfolio Based on the Value at Risk

The purpose of this study is to provide an optimal selection model for multi-round equity portfolios based on the value of exposed risk periods, with transaction costs. Multi-stock portfolios allow the investor to revise the contents of the basket over time and adjust it to fit new information. For sample, ten portfolios of five shares were randomly selected from companies listed in Tehran Stock Exchange during the years of 1388-1393, which, with an annual risk-free return (20%), average quarterly returns of more than 0.1, were selected. The proposed model is optimized using two continuous and cumulative particle genetic algorithms. In order to measure the efficiency of the results of the two algorithms, a risk-based value criterion has been used and the result of the research suggests higher efficiency of the results of the particle cumulative algorithm compared to the genetic algorithm.