Time series analysis for forecasting crude oil prices

Abstract

Many analysts, policymakers, and researchers have grown increasingly concerned about the fluctuation of international crude oil prices. That is because oil prices reflect many macroeconomic and financial indicators (GDP, unemployment, inflation, S&P 500 Index, Nasdaq Composite Index), and conditions in a variety of financial and goods markets. This paper highlights the most appropriate model for estimating and forecasting West Texas Intermediate (WTI) crude oil monthly prices by comparing three hybrid models – ARMA-GARCH, ARMAEGARCH, and ARMA-FIGARCH. Finally, among these models, the paper considers that the ARMA-EGARCH(1,20) model emerges as the most efficacious model for the prediction of West Texas Intermediate (WTI) crude oil monthly price returns.