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

Onder Buberkoku
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Onder Buberkoku: Department of Finance, Faculty of Business Administration, Yuzuncu Yil University, Van, Turkey

International Journal of Economics and Financial Issues, 2018, vol. 8, issue 3, 36-50

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.

Keywords: FIGARCH models; value-at-risk; expected shortfall; energy commodities (search for similar items in EconPapers)
JEL-codes: C53 C58 G31 Q40 (search for similar items in EconPapers)
Date: 2018
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