Modelling and forecasting crude oil prices during covid-19 pandemic

Abstract

Currently, the world suffers from the COVID-19 pandemic, which affects almost every aspect of daily life, giving rise to recession and affecting the world prices of crude oil. The study aims to model the high uncertainty of volatility as well as to forecast the daily prices of crude oil during the pandemic. One econometric model applied in this study is the Generalised Autoregressive Conditional Heteroscedasticity (GARCH) that allows more accurate and appropriate statistical analyses. Particularly, this study also discusses solving economic issues on the condition of any disturbances in the stability of daily crude oil prices. The findings suggest that the AR(1)-GARCH(1,1) model is a well-fitted model to predict relatively small errors. This model can act as a foundation for determining strategies in the future while facing such uncertain circumstances.