Designing a Model to for Selection of Effective Variables of Forecasting Future Dividend of the Firms Member Tehran Stock Exchange

Decision making is on the most important roles of a manager. Meanwhile, selection of effective input variables on decision making or forecasting problems, is one of the most important dilemmas in forecasting and decision making field. Due to research and problem constraints, we can not use all of known variables for forecasting or decision making in real world applications. Thus, in decision making problems or system simulations, we are trying to select important and effective variables as good data.In this paper we proposed a hybrid model of Genetic Algorithm (GA) and Artificial Neural Network (ANN) to determine and select effective variables on forecasting and decision making process. In this model, genetic algorithm has been used to code the combination of effective variables and neural network as a fitness function of genetic algorithm. The introduced model is applied in a case study to determine effective variables on forecasting future dividend of the firms that are members of Tehran stock exchange.