Presentation of a model for the active optimization of stock portfolios using value at risk exposure; Application of Convergence Variance Difference Models Approach Based on Algorithm DE Approach

Active management is one of the issues that is important in terms of violating effectiveness of financial markets financial markets. Because inefficient market, there is a potential to generate abnormal returns through active portfolio management. In many studies in this regard the reason for the surplus return compared to the baseline portfolio by minimizing the tracking error variance (TEV) in this regard, the risk of the entire portfolio is not taken into account. In this study, by using the differential evolution algorithm (DE) to optimize the active portfolio, with the goal of maximizing portfolio surplus returns compared to the standard portfolio, considering the risk of the entire portfolio from the calculated conditional risk value criterion (CVaR) based on the GARCH approach is used. The results of the portfolio consist of 14 stocks with a positive average yield from the beginning of 2011 to the end of June of 2017 from the top 50 stock exchanges on a monthly shows that subject to risk portfolio based on CVaR, causes better performance in the active optimization of the portfolio, based on backtesting method.