Abstract
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 Inte-grated 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.
Highlights
Oil, which has been called ‘black gold’ as it is most precious commodity impacts the world economy, is going through unprecedented times
The reported results associated with the forecasting crude oil prices using Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models, show that the GARCH (1, 1) model, which is a symmetric model is a fitted model to forecast crude oil prices
The results report that the asymmetric GARCH models are fit to forecast the crude oil prices, except the EGARCH model
Summary
Oil, which has been called ‘black gold’ as it is most precious commodity impacts the world economy, is going through unprecedented times. The demand for crude oil has fallen drastically like never before because of the suspension of economic activity worldwide because of the spread of the contagious coronavirus. The world population of around three billion has been forced to remain at home to prevent the spread of this highly contagious virus This has taken a toll on the economic activities. The most dominant strategy to prevent the spread to coronavirus was a lockdown as at the end of July the world awaits the vaccine for this disease. The futures market of oil is in ‘super-contango,’ encouraging storing oil with the anticipation of increased prices in the future. This has strained both the storage infrastructure. The choice of these two methods is rationalized as ARIMA is based on mean and GARCH is based on variance
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