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Energy Markets Volatility Modelling using GARCH

  • Olga Efimova
  • Apostolos Serletis

    (University of Calgary)

This paper investigates the empirical properties of oil, natural gas, and electricity price volatilities using a range of univariate and multivariate GARCH models and daily data from wholesale markets in the United States for the period from 2001 to 2013. The key contribution to the literature is the estimation of trivariate BEKK and DCC models that allow us to observe spillovers and interactions among energy markets. We evaluate and compare the performance of univariate and multivariate models with a range of diagnostic and forecast performance tests, and assess forecasting performance and conditional correlation dynamics.

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Paper provided by Department of Economics, University of Calgary in its series Working Papers with number 2014-39.

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Date of creation: 24 Feb 2014
Date of revision: 24 Feb 2014
Handle: RePEc:clg:wpaper:2014-39
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  17. Buhlmann, Peter & McNeil, Alexander J., 2002. "An algorithm for nonparametric GARCH modelling," Computational Statistics & Data Analysis, Elsevier, vol. 40(4), pages 665-683, October.
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  26. Jin, Xiaoye & Xiaowen Lin, Sharon & Tamvakis, Michael, 2012. "Volatility transmission and volatility impulse response functions in crude oil markets," Energy Economics, Elsevier, vol. 34(6), pages 2125-2134.
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  28. Goto, Mika & Karolyi, G. Andrew, 2004. "Understanding Electricity Price Volatility within and across Markets," Working Paper Series 2004-12, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
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