Comparison of explanatory power of linear in models predicts expected stock returns

Introduction
The present study is an applied research in terms of purpose and semi-experimental post-event research in the field of positive accounting research in terms of purpose of data collection, which has been done using multivariate regression method and econometric models.
 
Hypotheses
H1. There is a significant difference between the explanatory power of linear models to explain stock returns.
H2. There is a significant difference between the predictive models of explanatory power of expected stock returns.
 
 Method
The statistical population studied in this research consists of companies listed on the Tehran Stock Exchange during the years 2009 to 1398 and the selected sample of the research are companies. The research method in the present study is systematic elimination or screening according to which 102 companies were selected from the Tehran Stock Exchange companies for the final analysis. In collecting data, new entry software and Cadal system and website related to the stock exchange were used. Hypothesis testing was performed after collecting the required data with the help of Ives software version 10.
 
 Results
The results showed that among the linear models in Karhart model, the coefficients of market variables, size and value were higher than the coefficients of other models used. This finding is consistent with the results of research conducted by Iman and Zamani (1396). The findings also indicate that after the Carhart model, the 5-factor model of Fama and French has a higher explanatory power than other linear models. This finding is also consistent with the research of Salehi et al. (2015), Bozorg Asl and Masjid Mousavi (2015), Rezaei Dolatabadi and Yousefan (2015), Bakhshaish et al. (2015), Mousawa et al. (2018). In general, the results indicate that the use of investment and profitability factors has led to an increase in explanatory power in explaining stock returns.
 
 Discussion and Conclusion
In general, regarding the comparison between linear methods and their compatibility with the economic environment in Iran, the results indicate that among the linear models, Karhart model has a higher power to explain the expected return on stocks and the findings of this study with Imani and Pourzamani (1396) research are consistent.
Thus, among the linear models, the Carhart model has a higher power to explain the expected stock returns. In addition, the results and findings indicate that the addition of two profitability indices and investment index to the Fama and French three-factor model increases the power and strength of the model in explaining and explaining the stock returns of companies.
These results can increase the understanding, awareness and knowledge of investors and capital market researchers to explain the expected return on stocks. Investors are encouraged to consider factors such as liquidity, amount of investment, market factor, company size, and company value when deciding and forecasting expected stock returns.