Optimization in volatility estimation for imperfect financial markets: a GARCH modeling analysis

This study aims to enhance the accuracy of volatility estimation in imperfect financial markets, particularly during the COVID-19 pandemic and non-pandemic periods. It also examines the dynamic behavior of volatility, focusing on how market imperfections influence volatility, particularly during periods of crisis like COVID-19. The study investigates the extent to which COVID-19 triggers changes in information content, which, in turn, affects volatility. The research proposes a GARCH-X framework that incorporates various market imperfections as exogenous variables (Model 1), the interaction between COVID-19 and asymmetric information (Model 2), and the degree of imperfection as an exogenous variable (Model 3). A refined contribution of this study is the use of entropy to measure market imperfections and the degree of imperfection. All models yield significant results, signifying that market imperfections influence volatility behavior. An empirical finding nominating that the proposed model is superior to conventional GARCH models in both in-sample and out-of-sample periods.