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Forecasting commodity prices: GARCH, jumps, and mean reversion

Author

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  • Jean-Thomas Bernard

    (Départment d'économique, and GREEN, Université Laval, Quebec City, Quebec, Canada)

  • Lynda Khalaf

    (Economics Department, Carleton University, Ottawa, Ontario, Canada)

  • Maral Kichian

    (Research Department, Bank of Canada, Ottawa, Ontario, Canada)

  • Sebastien Mcmahon

    (Ministry of Finance, and GREEN, Université Laval, Quebec City, Quebec, Canada)

Abstract

In examining stochastic models for commodity prices, central questions often revolve around time-varying trend, stochastic convenience yield and volatility, and mean reversion. This paper seeks to assess and compare alternative approaches to modelling these effects, with focus on forecast performance. Three specifications are considered: (i) random-walk models with GARCH and normal or Student- t innovations; (ii) Poisson-based jump-diffusion models with GARCH and normal or Student- t innovations; and (iii) mean-reverting models that allow for uncertainty in equilibrium price. Our empirical application makes use of aluminium spot and futures price series at daily and weekly frequencies. Results show: (i) models with stochastic convenience yield outperform all other competing models, and for all forecast horizons; (ii) the use of futures prices does not always yield lower forecast error values compared to the use of spot prices; and (iii) within the class of (G)ARCH random-walk models, no model uniformly dominates the other. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian & Sebastien Mcmahon, 2008. "Forecasting commodity prices: GARCH, jumps, and mean reversion," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 279-291.
  • Handle: RePEc:jof:jforec:v:27:y:2008:i:4:p:279-291
    DOI: 10.1002/for.1061
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    References listed on IDEAS

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    Cited by:

    1. Dannenberg, Henry & Ehrenfeld, Wilfried, 2010. "Stochastic Income Statement Planning and Emissions Trading," IWH Discussion Papers 4/2010, Halle Institute for Economic Research (IWH).
    2. Bernard, Jean-Thomas & Khalaf, Lynda & Kichian, Maral & McMahon, Sébastien, 2008. "Oil Prices: Heavy Tails, Mean Reversion and the Convenience Yield," Cahiers de recherche 0801, GREEN.
    3. Shalini, Velappan & Prasanna, Krishna, 2016. "Impact of the financial crisis on Indian commodity markets: Structural breaks and volatility dynamics," Energy Economics, Elsevier, vol. 53(C), pages 40-57.
    4. Wen, Shaobo & An, Haizhong & Chen, Zhihua & Liu, Xueyong, 2017. "Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 299-308.
    5. Sinha, Pankaj & Mathur, Kritika, 2013. "A study on the Price Behavior of Base Metals traded in India," MPRA Paper 47028, University Library of Munich, Germany.
    6. Hegerty, Scott W., 2016. "Commodity-price volatility and macroeconomic spillovers: Evidence from nine emerging markets," The North American Journal of Economics and Finance, Elsevier, vol. 35(C), pages 23-37.
    7. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2010. "The macroeconomic determinants of volatility in precious metals markets," Resources Policy, Elsevier, vol. 35(2), pages 65-71, June.
    8. Jean-Thomas Bernard, Lynda Khalaf, Maral Kichian, and Sebastien McMahon, 2015. "The Convenience Yield and the Informational Content of the Oil Futures Price," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    9. Bouakez, Hafedh & Essid, Badye & Normandin, Michel, 2013. "Stock returns and monetary policy: Are there any ties?," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 33-50.
    10. Na Jin & Sergio Lence & Chad Hart & Dermot Hayes, 2012. "The Long-Term Structure of Commodity Futures," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 94(3), pages 718-735.
    11. repec:eee:ecofin:v:43:y:2018:i:c:p:169-205 is not listed on IDEAS
    12. Heydari, Somayeh & Siddiqui, Afzal, 2010. "Valuing a gas-fired power plant: A comparison of ordinary linear models, regime-switching approaches, and models with stochastic volatility," Energy Economics, Elsevier, vol. 32(3), pages 709-725, May.
    13. Alon Dourban & Liron Yedidsion, 2017. "Optimal Purchasing Policy For Mean-Reverting Items in a Finite Horizon," Papers 1711.03188, arXiv.org.
    14. repec:ebl:ecbull:eb-16-00459 is not listed on IDEAS
    15. Chevallier, Julien & Ielpo, Florian, 2017. "Investigating the leverage effect in commodity markets with a recursive estimation approach," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 763-778.

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    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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