IAEE Members and subscribers to The Energy Journal: Please log in to access the full text article or receive discounted pricing for this article.

Long Memory in Oil and Refined Products Markets

Abstract:
We test for the presence of long memory in daily oil and refined products prices absolute return, squared return and conditional volatility, using several parametric and semiparametric methods. This study finds strong evidence of long memory (LM) in the daily absolute and squared spot and futures returns for crude oil, gasoline and heating oil but at different degrees. The FIGARCH model also demonstrates strong evidence of LM for volatility for most of oil and products prices returns, with also different resilience levels. Structural breaks have only the partial effects of slightly reducing persistence for just absolute and squared returns. Examining the forecasting behavior of two competing models, the less parsimonious ARFIMA which satisfies the LM property, and the parsimonious ARMA with short-term processes, the ARFIMA model provides significantly better out-of-sample forecasts at all forecasting horizons for all three petroleum types.

Purchase ( $25 )

Energy Specializations: Petroleum – Refining and Products; Petroleum – Markets and Prices for Crude Oil and Products; Energy Modeling – Forecasting and Market Analysis

JEL Codes: Q35: Hydrocarbon Resources, L71: Mining, Extraction, and Refining: Hydrocarbon Fuels, Q41: Energy: Demand and Supply; Prices, C58: Financial Econometrics, Q40: Energy: General, Q02: Commodity Markets, C53: Forecasting Models; Simulation Methods, G13: Contingent Pricing; Futures Pricing; option pricing

Keywords: Oil, Refined products, Long memory, Structural breaks, Forecasting

DOI: 10.5547/ISSN0195-6574-EJ-Vol30-No2-5

Published in Volume 30, Number 2 of the bi-monthly journal of the IAEE's Energy Economics Education Foundation.

 

© 2024 International Association for Energy Economics | Privacy Policy | Return Policy