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.Keywords: Forecasting, COVID-19 pandemic, Crude oil prices, Pandemic, Generalised Autoregressive Conditional Heteroscedasticity modelJEL Classifications: C5, C53, C58, Q4, Q47DOI: https://doi.org/10.32479/ijeep.10578
Highlights
Today’s global economy is facing the worst circumstances as COVID-19 continues to spread
The COVID-19 pandemic has had the worst impact on crude oil, which plummeted and reached its first negative price
As the pandemic spread around the globe, it decreased gradually until approximately the 80th data
Summary
Today’s global economy is facing the worst circumstances as COVID-19 continues to spread. This pandemic has been affecting economic conditions such as trading, global supply chains and pressured asset pricing, and it forces multinational businesses to make difficult decisions due to limited information (Ayittey et al, 2020). The pandemic affects people’s consumption levels, which are decreasing, forcing markets to be more wary in their budgets. While production is still ongoing, there is lesser demand, causing a high uncertainty in prices, such as that in the oil industry. The COVID-19 pandemic has had the worst impact on crude oil, which plummeted and reached its first negative price. It becomes a necessity to forecast uncertain daily prices of crude oil with error level reduction. In economic statistics, forecasting a financial timeseries data with high accuracy is one way to make better decisions
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