Portfolio optimization including informational entropy

The most important factor in investing is choosing the asset that will bring us the highest expected return. Each investment forms its portfolio by predicting the investment risk and estimating the expected return. Various methods have been used to estimate the expected return on investment in recent decades, the most important of which is the Markowitz mean-variance model. But this model has been faced with flaws, so financial researchers have tried in the following decades to obtain more reliable findings for portfolio optimization by adding higher moments such as skewness and kurtosis and entropy. The statistical population of this research is based on trading data (adjusted price) of the top 35 symbols of the the Iranian capital market during the last ten years from 2013 to 2023 from the software bourseview, tsetmc, and the variables including variance, mean, skewness, kurtosis and entropy after processing. Data were implemented using Matlab version 6.7 software and portfolio optimization was done based on mv, mvs, mvsk models and finally MVSKE model. The findings of this research indicate that informational entropy is a reliable variable in portfolio optimization.