The Impact of Size and Book-to-Market Ratio on Excess Return Using Fama-French 5-Factor Model: The Case of Egypt

This paper attempts to investigate the relationship between the stock/portfolio excess return and the five factors of Fama-French (market excess return, size, value, operating profitability and investment) using a sample of 24 listed firms in EGX30 of the Egyptian Exchange and its 11 sectors, over the period from the 2015 to 2022. Stock/Portfolio excess return is measured by deducting the risk-free rate from the stock/portfolio rate of return (SPER), Market excess return is measured by subtracting the risk-free rate from the rate or return to the certain market index (MER), size and value factors is measured by market capitalization and book to market ratio as a proxy factor to compute the SMB and HML respectively, while the profitability factor ty is measured by return on equity (ROE) and the investment factor is measured by total assets growth (TAG). Forecasting for stocks and portfolio returns is still a controversial topic to enhance the stock market and help investors identify the factors affecting these returns. According to the previous studies to evaluate the validity of the Fama-French five-factor model, some of these studies provide no evidence to evaluate this model, but the others find their ability to predict the yields with different significant levels and signs, while in this study it is clearly showing that the efficiency of the five-factor approach of Fama-French with explanation power of 48.27% which overcome the three-factor approach of 47.27% to explain the stocks and portfolios returns with differing R2 according to the industry sector under study, as it varies from 15.77% to 79.90%. The results support the significance of each of the market and value factors on stocks and portfolio return in the Egyptian market with higher explanation power for the Fama-French five-factor model than the three-factor approach, without any evidence regarding the effect of other factors in general. Besides, each industry had its own significance and sign of regression coefficient toward the model’s factors.