Modeling the Behavior of Tehran Stock Exchange Firm Returns Using Factor Analysis Method

 
Journal of Accounting Advances (J.A.A)
Vol. 7, No. 1, 2015, Ser. 68/3
 
 
Extended Abstract
 
Modeling the Behavior of Tehran Stock Exchange Firm Returns Using Factor Analysis Method
 
Dr. Gholamreza Mansourfar                       Dr. Parviz Piri                     Reza Ziyaei
Urmia University
 
Introduction
Over the last decades, the behavior of stock return has been one of the most important and widely documented issues on capital markets. Based on Capital Asset Pricing Model (CAPM), the systematic risk was the unique explanatory factor of return differences among firms. However, the weaknesses of CAPM’s forecasting led to the idea that the securities pricing method is the result of an interplay of different variables. These abnormalities were also interpreted as the evidence of capital market inefficiency. In this regards, in the last decade of the twentieth century, studies by Fama and French showed that both the size and the book value to market value ratio of companies could better explain the differences between stock returns. Further researches also showed that other accounting variables have strength impact in explaining stock return volatility and they contain useful financial information. Hence, various models were proposed to assess factors, which affect the firms’ return. In the meantime, consideration of only one financial statement fails to take into account the role of information content of variables of the other financial statements. Thus, taking a comprehensive collection of information, including financial statements data and other external environment characteristics such as growth opportunities and stock turnover, would provide a more realistic perspective on the factors affecting return to decision makers. To this end, considering the overlap degree of variables, this paper aims to investigate the relationship between group and individual financial and accounting variables, and the return of publicly listed firms in Tehran Stock Exchange (TSE). Besides, the study attempts to identify the underlying factors that explain the common covariance of the variables that affect the return.
 
 Research Hypothesis
H1: There is a significant relationship between individual characteristics of listed companies in TSE and their returns volatility.
H2: There is a significant relationship between combined characteristics of listed companies in TSE and their returns volatility.
 
Data and Methods
Using systematic filtering, 113 firms from the period 2001 to 2009 of TSE were selected. Since most of the selected companies belonged to only “automotive” and “non-metal mineral” sectors, the analysis in industry level were performed among the mentioned two industries.
Using univariate and the unbalanced multivariate panel data analysis hypotheses were tested in two levels and in each level, two specific questions were answered. Factor analysis utilized for the sake of multicollinearity problem between explanatory variables. Factor analysis is based on the same key elements that are sensitive to the covariance between the observed variables.
 
Result
The findings show that 14 out of 30 variables were significantly associated with the stock returns. The results of factor analysis indicate that “profit per share”, “current ratio”, “the ratio of sales to price” and “the traded market value to total market value” are the most effective variables, such that  they are able to explain about 60 percent of average changes of the stock returns. Moreover, four econometrics models are proposed for predicting the stock returns of TSE. The results of individual effect of each explanatory variable on stock returns in the automotive industry show that 15 variables out of 30 variables were significantly associated with stock returns. Using factor analysis, four factors were extracted and they could explain about 75 percent alteration of stock returns. Based on the factor loading, the variables “EPS”, “Reten”, “LnMV” and “MVtrade” are the most effective variables in the factor scores. Furthermore, six models were obtained from factor analysis. The results of individual effect of each explanatory variable on stock returns in the non-metal mineral industry show 13 variables out of 30 variables were significantly associated with stock returns. In another stage, using factor analysis, four models obtained from factor analysis and the extracted variable could explain about 70 percent alteration of average stock returns. Based on the factor loading, the variables “EY”, “CFMtP”, “Grow” and “MVtrade” are the most effective variables in the factor scores.
 
Discussion and Conclusion
The main objectives of this study were to investigate the relationship between "firm-specific characteristics" and stock returns as well as identifying the underlined factors, which express the common changes of correlated variables. Based on domestic and international studies, 30 variables as "firm-specific characteristics" were selected. Then the relationship between individual and grouping form of these variables and stock returns of 113 publicly listed firms of TSE during the period 1388-1380 were investigated. Besides, the analysis was repeated in industry level among “automotive” and “non-metal mineral” sectors. According to research results, the following recommendations would be presented to decision makers and especially investors. 1) In order to predict the future volatility of a variable, and for the sake of large sets of data collection, while considering all available information, especial attention should be paid to the underlined factors, which express the common changes of correlated variables. 2) Beside macroeconomic and financial variables, accounting variables should be taken in to consideration while doing analysis on future changes of capital markets and 3) Based on the comparative analysis and due to the instability of the variables that explain the variation of returns, rotation models are recommended to be used in factor analysis.