Fitting the Relationship between Financial Variables and Stock Price through Fuzzy Regression Case study: Iran Khodro Company

Abstract

One of the best ways of investment is investing in stock exchange. For investing in stock, it is a crucial fact to be sure of the reasonable share price in the determined date and also predicting the future changes in stock price. Because some parts of the returns out of this type of investment comes from changes in the stock exchange. Thus, the increasing tendency is observed towards stock price prediction in the capital market. So far many researchers have tried to discover the relationship between the stock price and financial and nonfinancial variables by using the regression method. However, the fuzzy regression is not used thoroughly for finding this relationship. In the present study, the regression method based on the fuzzy sets theory has been used to fit the relationship between the financial variables and stock price of Iran Khodro Company (case study) from 1377 till 1386. The financial variables of this study are: Earning per Share (EPS), Dividends per Share (DPS) and Price to Earnings ratio (P/E). Eventually, the fuzzy linear regression model for examining the relationship between DPS, EPS and P/E variables and stock price of Iran Khordo Company has been presented. The empirical results of this research indicate that there is a positive and significant relationship between Earning per Share (EPS) and stock price of the company. However, there is a negative and significant relationship between Dividends per Share (DPS) and Price to Earnings ratio (P/E) of the said company.