Abstract:
Purpose: This research aims to empirically evaluate the effectiveness of an
augmented Fama and French (2015) Five-Factor Model in explaining the variation of
stock returns on the Colombo Stock Exchange (CSE) in Sri Lanka.
Design/Methodology/Approach: The study uses monthly data from April 2012 to
March 2022, focusing on non-financial firms. The Newey-West heteroscedasticity
and autocorrelation consistent estimator is employed to predict the applicability of
the model. The empirical model tests the validity of seven factors including market
factor (Rm-Rf), size factor (SMB), value factor (HML), profitability factor (RMW),
investment factor (CMA), momentum factor (WML), and liquidity factor (IML).
Factor mimicking portfolios for the Sri Lankan market are constructed following
methods from Fama and French (2015) and Carhart (1997), with liquidity factor
construction inspired by Chai, Faff, and Gharghori (2013).
Findings: The augmented five factor model is found to be applicable in Sri Lanka as
the regression models are significant in almost all the cases. Yet, there is no significant
improvement in the augmented model noticed in many regression portfolios with the
addition of momentum and liquidity. The market premium found to be positive and
significant in explaining the stock return variation in Sri Lanka and the influence of
market premium on the cross-sectional variation of stock returns are very robust.
Practical Implications: The findings suggest that investors and financial analysts in
emerging markets, such as Sri Lanka, can achieve better asset pricing predictions by
incorporating liquidity and momentum factors into their models. This enhanced
model could improve investment strategies, portfolio management, and risk
assessment in such markets.
Originality value: This study contributes to the asset pricing literature by offering an
empirical assessment of the augmented Fama-French Five-Factor Model in the
context of an emerging market, particularly Sri Lanka. The unique inclusion of
liquidity and momentum factors provides fresh insights into the model's applicability
and performance in markets with distinctive characteristics.
