نوع مقاله : مقاله پژوهشی
نویسندگان
1 کارشناسی ارشد مالی- مهندسی مالی و مدیریت ریسک، گروه مالی و بانکداری، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران
2 دانشیار گروه مالی و بانکداری، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران.
3 استادیار گروه مالی و بانکداری، دانشکده مدیریت و حسابداری، دانشگاه علامه طباطبائی، تهران، ایران.
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Purpose: Several studies have been conducted on the impact of unique fundamental factors of companies on their stock returns. The capital asset pricing model (CAPM) developed by Sharpe (1964) and Lintner (1965) and the three-factor model of Fama and French (1993) are the most famous models resulting from these studies. These two models have been widely accepted by academics and used in numerous types of research since its presentation. Significant studies such as those of Fama and French (2012 and 2017) and Hou et al. (2015) show the validity of some global factor models. Nevertheless, Findanza and Morsi (2015) believe that, despite numerous studies on the efficiency of factor models in non-financial companies, few pieces of research have been conducted on the explanatory capability of these models in financial companies. At the same time, a more recent stream of studies in the finance field, including the research of Baker and Wergler (2007) and Sime et al. (2013), show that the performance of traditional factor models may be improved by adding various behavioral factors such as investors' sentiment factor. The paradox of the efficiency of markets depends on the efforts of investors to find opportunities to earn abnormal returns by discovering anomalies. By trying to discover these opportunities, many researchers have focused on the investor sentiment factor and studied its effect on the stock price. The current research seeks to investigate the effectiveness of Fama and French's three-factor model and CAPM in the banking and credit institutions industry, as well as the role of investors' sentiment in this industry to increase the explanatory power of the aforementioned factor models.
Methodology: The current research is applied in terms of purpose. In terms of method, the research uses regression analysis along with the generalized least squares (GLS) model. The statistical population of the research includes all the listed banks in Tehran Stock Exchange and IRAN FARA BOURSE (IFB). Also, the time domain of the research includes the monthly periods from April 2012 to November 2022. The sampling is based on the methodical elimination of the banks that make up the statistical population. After removing the banks with a shorter acceptance period than the period of the research, 10 banks make up the sample size of the research. The Excel software is used to classify the data and calculate the research variables. Also, the data are analyzed with the Eviews (13 edition) and Stata (17 edition) software programs.
Due to cross-sectional dependence, which causes the efficiency of the ordinary least squares method to reduce, the model used the generalized least squares (GLS) method in the Eviews software. To eliminate the problem of heterogeneity of variance, White’s correction (Period Cluster) has been used.
Results and discussion: According to the cross-sectional dependence identified in the model, the final estimation of the research model has been done using the generalized least squares (GLS) method and White's correction to solve the heterogeneity of variance. The probability of F statistic related to the significance of all the models is equal to 0.0000. As a result, all the research models are significant. The findings show that adding variables related to the investor sentiment to the asset pricing factor models increases the explanatory power of these models. The excess market return factor was found to be significant in all the models, and the value factor was found to have no significant effect on banks' excess return in any model. The factors related to the investor sentiment are significant in both combined models. At the same time, the addition of the investor's sentiment index to the CAPM and Fama and French three-factor model has increased the adjusted coefficient of determining these models.
Conclusions and policy implications: The purpose of this research is to investigate the effectiveness of the CAPM and Fama and French three-factor model in the banking industry and the role of investor sentiment in strengthening the explanatory power of these models. The findings of the research show the significant and positive effect of excess market returns on the risk-adjusted performance of the studied banks. The size factor also has a significant and positive effect on the excess return of the investigated banks, which shows that there is a direct relationship between the excess return of banks and the performance of the size portfolio or the performance superiority of large market companies. Market performance has had the strongest effect on the excess returns of banks. However, the positive effect of the value portfolio performance on the excess return of banks is not statistically significant. This indicates that, although the expectations of investors incited by future developments, regarding the growth of stock returns with a high ratio of book value to market value, increase the return of this type of stock in the medium term, the factors influencing the stock returns are not counted in the long term. Therefore, the factor of market value to book value does not have a significant relationship with the risk-adjusted performance of banks. The findings of the research also show the significant and positive impact of the investor's sentiment index on the excess returns of banks. The sentiment of investors, thus, has a direct relationship with the excess returns, and the increase of the sentiment of investors and the strengthening of their optimism towards the banking industry cause an increase in the excess returns.
کلیدواژه‌ها [English]
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