Optimal Portfolio Diversification Strategy Using WCVaR Risk Criteria and Its Comparison with Monte Carlo Method

Choosing an optimal portfolio is one of the main goals of financial management. The initial strategy is to zero the risk of non-systematic risk by diversification in the optimal portfolio. In this research, WCVaR applied model and linear programming method for stock market risk measurement and selection of a weight optimized portfolio were used. WCVaR is one of the newest risk measurements and covers the defects of the VaR and CVaR models. This research 11-year period information (1387 -1397) was used from actual data of 10 different companies accepted in Tehran Stock Exchange. This research uses data from ten companies accepted in TESM during the period of 1397-1387. The results of model estimation using the linear programming method in Matlab software showed that changing the benchmark optimization would lead to a change in the weight of the basket stock and change the strategy of diversification in the optimal portfolio. The results of estimating the model using the linear programming method showed that changing the optimization criterion will lead to a change in the stock weight of the portfolio and a change in the diversification strategy in the optimal stock portfolio. Among the 44 baskets with different weights, the most optimal