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Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?

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  • Wang, Yudong
  • Wu, Chongfeng
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    Abstract

    In this paper, we forecast energy market volatility using both univariate and multivariate GARCH-class models. First, we forecast volatilities of individual assets and find that multivariate models display better performance than univariate models. Second, we forecast crack spread volatility and contrast the performance of multivariate models for two underlyings, with the alternative of univariate ones for crack spreads directly. Our evidence shows that univariate models allowing for asymmetric effects display the greatest accuracy. We also discuss the hedging strategy based on multivariate models and its implications for market participants.

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    Bibliographic Info

    Article provided by Elsevier in its journal Energy Economics.

    Volume (Year): 34 (2012)
    Issue (Month): 6 ()
    Pages: 2167-2181

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    Handle: RePEc:eee:eneeco:v:34:y:2012:i:6:p:2167-2181

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    Web page: http://www.elsevier.com/locate/eneco

    Related research

    Keywords: Energy markets; Volatility; Univariate GARCH; Multivariate GARCH; Crack spread;

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    Cited by:
    1. Liu, Li & Chen, Ching-Cheng & Wan, Jieqiu, 2013. "Is world oil market “one great pool”?: An example from China's and international oil markets," Economic Modelling, Elsevier, vol. 35(C), pages 364-373.
    2. Liu, Li & Wang, Yudong, 2014. "Cross-correlations between spot and futures markets of nonferrous metals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 20-30.
    3. Lv, Xiaodong & Shan, Xian, 2013. "Modeling natural gas market volatility using GARCH with different distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5685-5699.
    4. He, Kaijian & Wang, Lijun & Zou, Yingchao & Lai, Kin Keung, 2014. "Value at risk estimation with entropy-based wavelet analysis in exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 62-71.
    5. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Working Papers hal-00980125, HAL.
    6. Olga Efimova & Apostolos Serletis, 2014. "Energy Markets Volatility Modelling using GARCH," Working Papers 2014-39, Department of Economics, University of Calgary, revised 24 Feb 2014.

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