نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
This research proposes a model for determining an optimal portfolio based on changing risk aversion levels in different investment periods. In conventional portfolio optimization methods, the selection of the portfolio is performed using a static measure of risk aversion. Therefore, in this study, a dynamic multi-period portfolio optimization model is presented to better align the model output with the existing realities. The research first uses the theory of fuzzy credibility to determine fuzzy semi-entropy as a risk measure. Then, by adapting the risk aversion coefficient in each period while considering practical constraints, a multi-period portfolio optimization model is developed. The model is implemented for 30 securities in the Tehran Stock Exchange over five time periods using a genetic algorithm. The model output is compared with the results of 500 random portfolios. The results show that the portfolio created by the proposed model outperforms random portfolios in terms of risk and return.
کلیدواژهها English