Predicting crude oil prices during a pandemic: A comparison of arima and garch models

The unprecedented global turn of events primarily due to the spread of highly contagious corona pandemic has led to a substantial fall in crude oil prices. A forecast for crude oil prices is important as oil is required for all major economic activity, particularly production and transportation. This study aims to apply two commonly used methods of Autoregressive Integrated Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) to predict the WTI crude oil prices for the period February 10, 2020, to April 27, 2020. Such a comparative analysis of these methods in unprecedented times is missing in the existing literature. ARIMA suggests ARIMA (4,1,4) model while GARCH (1,1) as the best among their own respective family of models. And between ARIMA and GARCH ARIMA model is recommended for forecasting as it has a lower root mean squared error (RMSE) and mean absolute error (MAE). The study recommends using a mean based ARIMA approach for predicting future values in extreme situations.