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GARCH model and predictive performance of volatility forecasting: Evidence from oil market
Mid Sweden University, Faculty of Human Sciences, Department of Social Sciences.
2015 (English)In: World Review of Entrepreneurship, Management and Sustainable Development, ISSN 1746-0573, E-ISSN 1746-0581, Vol. 11, no 4, 345-357 p.Article in journal (Refereed) Published
Abstract [en]

This study investigates the predictive performance of the GARCH (1, 1) model in forecasting the return volatility of the three major items on the oil market, WTI crude, Brent crude and heating oil, for horizons of one, five, twenty and thirty days ahead. The empirical results indicate that the predictive performance of the GARCH model is best for short horizons, from one day ahead for WTI, one to five days ahead for Brent and one to twenty days ahead for heating oil, at the 5% significant level. For horizons from twenty days ahead, no robust forecasting model can be observed for any of these items. Thus, although the results show that the GARCH (1, 1) model has high predictive performance in forecasting the volatility for the short-term horizons, it cannot produce reliable results when the forecast horizon increases. The findings also show how volatility clustering on returns emerges on the oil market, which creates periods of high volatility followed by small movements.

Place, publisher, year, edition, pages
2015. Vol. 11, no 4, 345-357 p.
Keyword [en]
GARCH model, Oil prices, Price shocks, Volatility clustering, Volatility forecasting
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:miun:diva-26735DOI: 10.1504/WREMSD.2015.072040Scopus ID: 2-s2.0-84943423195OAI: oai:DiVA.org:miun-26735DiVA: diva2:888435
Available from: 2015-12-22 Created: 2015-12-22 Last updated: 2016-04-25Bibliographically approved

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Yazdanfar, Darush
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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf