Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach

Ying Fan, Yue Jun Zhang, Hsien Tang Tsai, Yi Ming Wei*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

172 Citations (Scopus)

Abstract

Estimation has been carried out using GARCH-type models, based on the Generalized Error Distribution (GED), for both the extreme downside and upside Value-at-Risks (VaR) of returns in the WTI and Brent crude oil spot markets. Furthermore, according to a new concept of Granger causality in risk, a kernel-based test is proposed to detect extreme risk spillover effect between the two oil markets. Results of an empirical study indicate that the GED-GARCH-based VaR approach appears more effective than the well-recognized HSAF (i.e. historical simulation with ARMA forecasts). Moreover, this approach is also more realistic and comprehensive than the standard normal distribution-based VaR model that is commonly used. Results reveal that there is significant two-way risk spillover effect between WTI and Brent markets. Supplementary study indicates that at the 99% confidence level, when negative market news arises that brings about a slump in oil price return, historical information on risk in the WTI market helps to forecast the Brent market. Conversely, it is not the case when positive news occurs and returns rise. Historical information on risk in the two markets can facilitate forecasts of future extreme market risks for each other. These results are valuable for anyone who needs evaluation and forecasts of the risk situation in international crude oil markets.

Original languageEnglish
Pages (from-to)3156-3171
Number of pages16
JournalEnergy Economics
Volume30
Issue number6
DOIs
Publication statusPublished - Nov 2008
Externally publishedYes

Keywords

  • GED-GARCH models
  • Granger causality in risk
  • International crude oil markets
  • Risk spillover effect
  • Value-at-Risk (VaR)

Fingerprint

Dive into the research topics of 'Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach'. Together they form a unique fingerprint.

Cite this