Presenting a combined econometric model to optimize the stock portfolio in the stock exchange

Purpose: Portfolio optimization is one of the important issues in the field of financial sciences and investment, which has many applications in financial planners and decisions. By choosing a suitable stock portfolio, it is possible to greatly increase the efficiency of investment (in terms of increasing returns and reducing risk).Methodology: In this paper, by presenting a model of liquidity risk, using the concept of diversification in the form of Shannon's entropy and econometric approach, an optimal portfolio of investment with the lowest risk and the highest return has been presented in the form of a portfolio. To calculate the liquidity risk, using multivariable methods, the variance-covariance matrix of price index returns and price gap was calculated and used in the presented model, and finally, the optimal weight was used using the optimization method and meta-heuristic algorithm of non-dominant ranking of the second version., calculated for selected industries.Findings: The output results of the model show that the optimal weight of the groups that have less variance in the optimal portfolio is higher.Originality/Value: Besides, the effect of removing the concept of liquidity from the model leads to an increase in the weight of industries that have less liquidity, and along with the increase in risk, the return of the optimal portfolio also increases in this case.Purpose: Portfolio optimization is one of the important issues in the field of financial sciences and investment, which has many applications in financial planners and decisions. By choosing a suitable stock portfolio, it is possible to greatly increase the efficiency of investment (in terms of increasing returns and reducing risk). Methodology: In this paper, by presenting a model of liquidity risk, using the concept of diversification in the form of Shannon's entropy and econometric approach, an optimal portfolio of investment with the lowest risk and the highest return has been presented in the form of a portfolio. To calculate the liquidity risk, using multivariable methods, the variance-covariance matrix of price index returns and price gap was calculated and used in the presented model, and finally, the optimal weight was used using the optimization method and meta-heuristic algorithm of non-dominant ranking of the second version., calculated for selected industries. Findings: The output results of the model show that the optimal weight of the groups that have less variance in the optimal portfolio is higher. Originality/Value: Besides, the effect of removing the concept of liquidity from the model leads to an increase in the weight of industries that have less liquidity, and along with the increase in risk, the return of the optimal portfolio also increases in this case.