Title: Forecasting the energy commodities: an evidence of ARIMA and intervention analysis

Authors: Miklesh Prasad Yadav; Vandana Sehgal; Deepali Ratra; Abdul Wajid

Addresses: Department of Finance, Indian Institute of Foreign Trade, Kakinada, 533001, India ' Department of Management, Jaypee Institute of Information Technology, 201301, India ' JIMS, Rohini, 110085, India ' Galgotias University, 201301, India

Abstract: The objective of this study is to forecast energy commodity and check the intervention effect on energy commodity. Crude oil and natural gas are the proxies of energy commodities. We apply autoregressive integrated moving average (ARIMA) to forecast the daily prices and intervention analysis to check the effect of lockdown on these two commodities. An ARIMA (5,0,5) and ARIMA (5,0,4) are suitable models for forecasting the crude oil and natural gas prices. The result reveals that these commodities are forecastable, and investors can generate returns investing in these commodities. In addition, intervention analysis indicates that first lockdown in India has affected crude oil significantly but not the natural gas. This study provides an insight to the investors and policy makers while forecasting the energy commodity.

Keywords: energy prices; crude oil; natural gas; ARIMA; autoregressive integrated moving average; intervention effect; COVID-19.

DOI: 10.1504/IJMEF.2023.136086

International Journal of Monetary Economics and Finance, 2023 Vol.16 No.6, pp.443 - 457

Received: 06 Feb 2022
Accepted: 20 Nov 2022

Published online: 16 Jan 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article