Modeling Stock Returns Volatility and Portfolio Risk Through Asset Pricing Model: Empirical Evidence from Pakistan

Abstract

The study aimed to test portfolio returns volatility risk from Pakistan’s perspective. This research aims to evaluate the effectiveness of stock returns and portfolio risk by considering both unexpected market risk and uncertainty elements with the Fama French model and GARCH (1, 1) model. But in this study, the additional factor of liquidity of stocks is implemented in Fama French 3-Factor asset pricing model. This study explored the risk exposure posed by Rm-Rf, SMB, HML and LIQ factors and provided future direction to investors, and stakeholders to understand aggregate portfolio performance to meet risk appetite. The findings were satisfactory to support the challenging models and to deliver widespread empirical shreds of evidence to the most relevant asset pricing model for the Pakistani stock market. The GARCH (1,1) results predict future returns from past returns and developed markets have a comparative volatility link. The value of the likelihood statistics ratio is big, implying that the GARCH (1, 1) model is a profitable depiction of the monthly return array, which successfully and competently depicts the ordered dependency of volatility. The findings showed that the sum of GARCH (1, 1) constants for all equity profits is less than 1, which is a crucial condition for mean reversion.