Optimal Portfolio Selection of Shares of Food Industry Companies in Tehran Stock Exchange Using Combined Forecasting Method: An Application of Mean-Variance-Skewness Model

The food industry companies' growth considered among the factors in the growth and development of the agricultural sector. One of the places for the principled allocation of financial resources to strengthen the food industry is the stock exchange. With proper investment in this market, in addition to financing the industrial and agricultural sector growth and country economic growth, investors also can gain appropriate benefits from this investment. To achieve the above goals, we need a way to through it identify the companies' shares profitable and to buy it and make optimal portfolio equity. The purpose of this study was to develop a procedure for the selection of the optimal portfolio of shares of companies in the food industry Tehran Stock Exchange using the mean-variance-skewness model with six objective functions. The statistical society of this study included 14 companies in the food and beverage except sugar sector and the data also includes the final price is the company's shares leading up to February 2016. For this purpose, three different methods to estimate the expected stock price was used in the food industry companies, and according to the forecast error, to each method is given weighted according to its estimation. To ensure the optimal weights obtained, the price obtained from the combination method with the prices obtained from each of the predicted methods by criteria of measurement error was compared. The results show the superiority of the combination is in the forecast price. The following weights obtained based on six criteria mean, variance and skewness related to returns and forecast error combination is achieved. Mean-variance- skewness model made by Goal Programming is solved. Finally, portfolio obtained from Mean-variance-skewness model with portfolio obtained from mean-variance model were compared. The results show the high performance of mean-variance- skewness model in creating an optimum portfolio with a high efficiency than that the mean-variance model. So that average daily returns during month for mean-variance-skewness model 0.52 percent and 0.32 percent for the mean-variance model.