Examination of the Predictive Power of Fama-French Five-Factor Model by the Inclusion of Skewness Coefficient: Evidence of Iranian Stock Market

Document Type : Original Article


1 Ph.D. Candidate of Finance Management, Islamic Azad University, Dubai Branch, United Arab Emirates.

2 Professor of Finance, Tarbiat Modares University, Tehran, Iran. (Corresponding author)

3 Professor of Accounting, Tehran University, Tehran, Iran.

4 Associate Professor, Islamic Azad University, South Tehran Branch, Tehran, Iran.


Due to the complexity of financial markets and specialization of investment, the investors in financial markets need tools, methods and models by which they can choose the best investment and the most appropriate portfolios. Fama-French Five-Factor Model (FFFFM) is one of the newest methods among various methods for financial asset pricing and prediction of stock returns. The main aim of this research is to investigate the improved predictability of returns by inclusion ofthe skewness variable to FFFFM. The statistical population of this study consists of all manufacturing companies listed in Tehran Stock Exchange (TSE) during 2003-2014. 75 companies selected by random sampling method. The results of panel data test of FFFFM indicate the positive significant effects of book to market value ratio, size, growth opportunity, and profitability but a negative significant effect of the investment variable. By inclusion of the skewness variable in the FFFFM model, the negative effects of investment variable becomes positive. Also, skewness variable indicates a significant positive impact and that this inclusion improved the predictability of firm returns.


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