Abstract

Today, investment by purchasing stock-share constitutes the greater part of economic exchanges of countries and a considerable amount of capital is exchanged through stock markets in the whole world. National economies are strongly influenced by the operation of stock markets; in addition, stock market as an available means for investment is of special importance for both investor and the receiver of investment. The most important part of this business is to obtain more profits through estimating future stock prices. This research with a probe in a sample of the whole population of the study involves the data and financial record of SAIPA auto-making company which is a member of Iranian stock, aims at the prediction of stock price. The prediction was done by the two linear and nonlinear models for one ahead and multi ahead in stock price by using exogenous variable of stock market cash index, and the results show the preference of nonlinear neural-fuzzy model to classic linear model and verify the capabilities of fuzzy-neural networks in this prediction. JEL Classification: C32-C45-C53.

Key words: One-ahead forecast, multi-ahead forecast, ARIMA linear model, neural networks, fuzzy-neural model.