Estimation of value-at-risk for energy commodities via fat-tailed GARCH models

• Published in: Energy economics Vol. 30; no. 3; pp. 1173 - 1191
• Main Authors: Hung, Jui-Cheng, Lee, Ming-Chih, Liu, Hung-Chun
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.05.2008; Elsevier Science; Elsevier; Elsevier Science Ltd
• Series: Energy Economics
• Subjects: Applied sciences; Commodities; Comparative analysis; Crude oil; Econometric models; Economic data; Energy; Energy commodities; Energy economics; Energy market; Estimating techniques; Estimation; Exact sciences and technology; Fat tails; Fossil fuels and derived products; GARCH models; GARCH-HT; General, economic and professional studies; Innovations; Methodology. Modelling; MRSB; Oil; Stochastic models; Studies; VaR; Vector-autoregressive models; USA, New York, New York, New York Harbor; C53; MRSB; C52; Energy commodities; VaR; G15; Fat tails; GARCH-HT; Performance evaluation; Volatility; Econometric model; C52; C53; G15; Fuel oil; Petroleum; Return on investment; GARCH modele; VaR; GARCH-HT; Energy commodities; MRSB; Fat tails; Gasoline; Distribution function; Profit; Spot price; Risk management; Portfolio management; Propane

The choice of an appropriate distribution for return innovations is important in VaR applications owing to its ability to directly affect the estimation quality of the required quantiles. This study investigates the influence of fat-tailed innovation process on the performance of one-day-ahead VaR e...