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Volatility forecasting for crude oil futures

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  • L. Lambertini

Abstract

This paper studies the forecasting properties of linear GARCH models for closing-day futures prices on crude oil, first position, traded in the New York Mercantile Exchange from January 1995 to November 2005. In order to account for fat tails in the empirical distribution of the series, we compare models based on the normal, Student’s t and Generalized Exponential distribution. We focus on out-of-sample predictability by ranking the models according to a large array of statistical loss functions. The results from the tests for predictive ability show that the GARCH-G model fares best for short horizons from one to three days ahead. For horizons from one week ahead, no superior model can be identified. We also consider out-ofsample loss functions based on Value-at-Risk that mimic portfolio managers and regulators’ preferences. EGARCH models display the best performance in this case.

Suggested Citation

  • L. Lambertini, 2007. "Volatility forecasting for crude oil futures," Working Papers 598, Dipartimento Scienze Economiche, Universita' di Bologna.
  • Handle: RePEc:bol:bodewp:598
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    References listed on IDEAS

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    1. Fershtman, Chaim & Kamien, Morton I, 1990. "Turnpike Properties in a Finite-Horizon Differential Game: Dynamic Duopoly with Sticky Prices," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 31(1), pages 49-60, February.
    2. Tsutsui, Shunichi & Mino, Kazuo, 1990. "Nonlinear strategies in dynamic duopolistic competition with sticky prices," Journal of Economic Theory, Elsevier, vol. 52(1), pages 136-161, October.
    3. Caputo, Michael R., 2007. "The envelope theorem for locally differentiable Nash equilibria of finite horizon differential games," Games and Economic Behavior, Elsevier, vol. 61(2), pages 198-224, November.
    4. Fershtman, Chaim & Kamien, Morton I, 1987. "Dynamic Duopolistic Competition with Sticky Prices," Econometrica, Econometric Society, vol. 55(5), pages 1151-1164, September.
    5. Dixit, Avinash K, 1986. "Comparative Statics for Oligopoly," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 27(1), pages 107-122, February.
    6. R. Cellini & L. Lambertini, 2000. "Dynamic Oligopoly with Sticky Prices: Closed-Loop,Feedback and Open-Loop Solutions," Working Papers 393, Dipartimento Scienze Economiche, Universita' di Bologna.
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    Cited by:

    1. Halkos, George & Papageorgiou, George, 2012. "Simple taxation schemes on non–renewable resources extraction," MPRA Paper 40945, University Library of Munich, Germany.
    2. Halkos, George, 2009. "A Differential game approach in the case of a polluting oligopoly," MPRA Paper 23742, University Library of Munich, Germany.
    3. L. Lambertini, 2009. "Oligopoly with Hyperbolic Demand and Capital Accumulation," Working Papers 672, Dipartimento Scienze Economiche, Universita' di Bologna.
    4. Halkos, George, 2010. "Dynamic regulations in non –renewable resources oligopolistic markets," MPRA Paper 24774, University Library of Munich, Germany.

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