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Examining the Value-at-risk Performance of Fractionally Integrated GARCH Models: Evidence from Energy Commodities

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  • Onder Buberkoku

    (Department of Finance, Faculty of Business Administration, Yuzuncu Yil University, Van, Turkey)

Abstract

This study examines the out-of-sample value-at-risk forecasting performance of the GARCH, FIGARCH, HYGARCH and FIAPARCH models for West Texas intermediate crude oil, Europe Brent crude oil, heating oil#2, propane and New York Harbour Conventional Gasoline regular under the standard normal, Student's t and skewed Student's t distribution assumptions. Additionally, the expected shortfall is calculated in all cases. The results clearly show that the HYGARCH model under the normal distribution is the most accurate for short trading positions, whereas the FIGARCH model under the Student's t distribution is preferred for long trading positions. This further implies that it is important to consider downside and upside risk separately to obtain more accurate results.

Suggested Citation

  • Onder Buberkoku, 2018. "Examining the Value-at-risk Performance of Fractionally Integrated GARCH Models: Evidence from Energy Commodities," International Journal of Economics and Financial Issues, Econjournals, vol. 8(3), pages 36-50.
    • Handle: RePEc:eco:journ1:2018-03-6
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    More about this item

    Keywords

    FIGARCH models; value-at-risk; expected shortfall; energy commodities;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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