Compare the Three and Four and Five Factor Models of Pricing of Fama and French Capital Assets to Predict Stock Returns of Companies Listed in Tehran Stock Exchange

Authors

  • Mohammad Ali Afzali Damghan Branch, Islamic Azad University
  • Mostafa Vaezi Monfared Damghan Branch, Islamic Azad University

DOI:

https://doi.org/10.24200/jmas.vol4iss04pp65-69

Abstract

One of the basic criteria for decisions on the exchange is stock returns. Stock returns, alone, are having informational content and more actual and potential investors use it in financial analysis and forecasts. Many studies have been done on the relationship between risk and return. Fama and French purpose of the experiment was to know the relative importance of future stock returns, which at present, is different than the market value to their book value. Methodology: Fama and French, to predict stock returns were to work as a model became known three-factor model. In this model, the stock return was affected by three factors: beta, firm size and the ratio of book value to market value. In recent years, were presented and were studied three and four-factor model of Fama and French for evaluation pricing of capital assets and most recently, Fama and French also have provided their five-factor new model. The aim of this study was to compare the results of forecast three factor model and four-factor model and the five-factor model of Fama and French in Tehran Stock Exchange. Results: The results show that the five-factor model of Fama and French is a significant in Tehran Stock Exchange and in comparison the explanatory power of three and four and five factors models, the five-factor model was better than the three factor model and four factor model was better than the five factor model. Conclusion: So, using four factor models in financial analysis in Tehran stock exchange will result in the highest performance.

References

Chen, C., Hung, W., & Cheng, H. 2011. Applying linguistic PROMETHEE method in investment portfolio decision-making, International Journal of Electronic Business Management, 9 (2): 139-148.

Eslam Bigdeli, G., & Shahsavani, D. 2012. Assess the ability of model based on features stock compared with Fama and French three-factor model in explaining the difference between stock returns of companies listed on the Tehran Stock Exchange, Journal of Accounting and Audit, 4 (13): 55-67.

Eslam Bigdeli, G., & Honardoust, A. 2012. Fama and French three-factor model and liquidity risk: evidence of Tehran Stock Exchange, investment knowledge quarterly, 1 (2): 71-93.

Izadinia, N. 2014. Compare the original model of Fama and French with Carhart four factor model in explaining stock companies listed on the Tehran Stock Exchange, Quarterly research Journal of asset management and financing, 2 (3): 17-28.

Jafari, M., Misaghi Faruji, J., Ahmadvand, Ali. 2013. Comparison pricing models, capital assets of three-factor Fama and French and artificial neural networks to predict the stock market, Journal of Economics and Business, 4 (5): 53-63.

Shams, N., & Parsaeian, S. 2012. Compare the performance of Fama and French model and artificial neural networks in predicting stock returns in Tehran Stock Exchange, Financial Engineering and manage portfolios magazine, 1: 14-21.

Artmann, S., Filter, P., & Kempf, A. 2012. Determinants of Expected Stock Returns: Large ample Evidence from the German Market. Journal of Business Finance & Accounting, 39 (5-6): 758-784.

Carhart, M. 1997. On Persistence in Mutual Fund Performance. The Journal of finance, 52 (1): 57-82.

Fama, E., & French, K. 2012 .Size, Value, and Momentum in International Stock Returns. Journal of Financial Economics, 105 (3): 457-4721.

Fama, E., & French, K. 1993. "Common risk factors in the returns on stocks and bonds". Journal of Financial Economics. 1: 33: 3–56.

Fan, S., & Yu, L. 2013. Does the Alternative Three-Factor Model Explain Momentum Anomaly Better in G12 countries? .Journal Of Finance & Accountancy, 12: 81-96.

Narasimhan, J., & Titman, S. 1993. Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency, Journal of Finance, 1: 48-91.

Downloads

Published

2019-07-21

Issue

Section

Articles