Application of Copula and Simulated Returns in the Portfolio Optimization with Conditional Value-at-Risk (CVaR) in Tehran Stock Exchange (TSE)

Several studies have confirmed with using criteria appropriate to the structure and characteristics of the data, the performance of the models significantly improved. The Copula function is one of the models in determining the relationship between variables has attracted a lot of attention. In this study, we investigated the portfolio of TSE industry indexes optimized to minimize the Conditional Value at Risk, simulated data based on Copula function and generalized Pareto distribution as input. The statistical analyzes implies portfolio performance improves significantly. Since the Copula functions are diverse, Compare the impact of any one risk reduction is recommended.