risk reduction of portfolio based on generalized autoregressive conditional heteroscedasticity model in tehran stock exchange

return maximization or risk minimization is goal in portfolio optimization based on mean variance theory. the structure of correlation matrices and individual variance of each asset are two main factors in optimization with risk minimization object. it’s necessary to use appropriate variance and correlation coefficient for time series with clustering volatilities feature, too. in this research, it has been approved optimization based on conditional variance and standardized residuals correlation in constant correlation generalized autoregressive conditional heteroscedasticity model leads to less portfolio risk and improvement the portfolio manager performance.