Application of Polynomial Goal Programming in Optimal Portfolio Determination of Food Industry Stocks

In this study, a polynomial goal programming approach based on the mean-variance-skewness-kurtosis model is used to select the optimal portfolio based on different investor preferences structure. Then systematic risk is considered as a constraint in the model because of its importance in decision making. Extreme Downside Hedge is considered as the measurement of systematic risk. The data used in this study include daily stock price of selected food industry companies and market index for 2015-2019. The results showed that investor preferences influence portfolio selection and allocation of capital, so individuals can choose their portfolio based on their preferences. The risk entry into the model also indicated that given this limitation, portfolio selection would shift to the stocks of companies that are less affected by market volatility. Based on results, it is suggested that in future studies the model be developed based on other limitations such as different degree of risk aversion in decision making. The model can also be designed based on fuzzy logic and its performance be investigated under such conditions. Also, results of each estimation can be considered as an investment patern for individuals.