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Forecasting Volatility and Spillovers in Crude Oil Spot, Forward and Futures Markets

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  • Chia-Lin Chang

    (Department of Applied Economics, National Chung Hsing University)

  • Michael McAleer

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo)

  • Roengchai Tansuchat

    (Faculty of Economics, Maejo University and Faculty of Economics, Chiang Mai University)

Abstract

Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the international oil market, namely West Texas Intermediate (USA), Brent (North Sea), Dubai/Oman (Middle East), and Tapis (Asia-Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover effects across and within the four markets, using three multivariate GARCH models, namely the CCC, VARMA-GARCH and VARMA-AGARCH models. A rolling window approach is used to forecast the 1-day ahead conditional correlations. The paper presents evidence of volatility spillovers and asymmetric effects on the conditional variances for most pairs of series. In addition, the forecasted conditional correlations between pairs of crude oil returns have both positive and negative trends.

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File URL: http://www.carf.e.u-tokyo.ac.jp/pdf/workingpaper/fseries/169.pdf
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Bibliographic Info

Paper provided by Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo in its series CARF F-Series with number CARF-F-163.

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Length: 24 pages
Date of creation: Aug 2009
Date of revision:
Handle: RePEc:cfi:fseres:cf163

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  1. Hammoudeh, Shawkat M. & Yuan, Yuan & McAleer, Michael, 2009. "Shock and volatility spillovers among equity sectors of the Gulf Arab stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 829-842, August.
  2. Martin Sola & Fabio Spagnolo & Nicola Spagnolo, 2002. "A Test for Volatility Spillovers," Economics and Finance Discussion Papers 02-04, Economics and Finance Section, School of Social Sciences, Brunel University.
  3. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
  4. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  5. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(02), pages 280-310, April.
  6. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CIRJE F-Series CIRJE-F-638, CIRJE, Faculty of Economics, University of Tokyo.
  7. Hammoudeh, Shawkat & Li, Huimin & Jeon, Bang, 2003. "Causality and volatility spillovers among petroleum prices of WTI, gasoline and heating oil in different locations," The North American Journal of Economics and Finance, Elsevier, vol. 14(1), pages 89-114, March.
  8. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  9. George Milunovich & Susan Thorp, 2005. "Valuing Volatility Spillovers," Research Papers 0506, Macquarie University, Department of Economics.
  10. da Veiga, Bernardo & Chan, Felix & McAleer, Michael, 2008. "Modelling the volatility transmission and conditional correlations between A and B shares in forecasting value-at-risk," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 155-171.
  11. Lin, Sharon Xiaowen & Tamvakis, Michael N., 2001. "Spillover effects in energy futures markets," Energy Economics, Elsevier, vol. 23(1), pages 43-56, January.
  12. Ewing, Bradley T. & Malik, Farooq & Ozfidan, Ozkan, 2002. "Volatility transmission in the oil and natural gas markets," Energy Economics, Elsevier, vol. 24(6), pages 525-538, November.
  13. McAleer, Michael, 2005. "Automated Inference And Learning In Modeling Financial Volatility," Econometric Theory, Cambridge University Press, vol. 21(01), pages 232-261, February.
  14. Lee, Sang-Won & Hansen, Bruce E., 1994. "Asymptotic Theory for the Garch(1,1) Quasi-Maximum Likelihood Estimator," Econometric Theory, Cambridge University Press, vol. 10(01), pages 29-52, March.
  15. McAleer, Michael & Chan, Felix & Hoti, Suhejla & Lieberman, Offer, 2008. "Generalized Autoregressive Conditional Correlation," Econometric Theory, Cambridge University Press, vol. 24(06), pages 1554-1583, December.
  16. McAleer, Michael & Chan, Felix & Marinova, Dora, 2007. "An econometric analysis of asymmetric volatility: Theory and application to patents," Journal of Econometrics, Elsevier, vol. 139(2), pages 259-284, August.
  17. Michael McAleer & Suhejla Hoti & Felix Chan, 2009. "Structure and Asymptotic Theory for Multivariate Asymmetric Conditional Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 28(5), pages 422-440.
  18. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
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Cited by:
  1. Tansuchat, R. & Chang, C-L. & McAleer, M.J., 2010. "Crude Oil Hedging Strategies Using Dynamic Multivariate GARCH," Econometric Institute Research Papers EI 2010-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  2. Lee, Chien-Chiang & Zeng, Jhih-Hong, 2011. "The impact of oil price shocks on stock market activities: Asymmetric effect with quantile regression," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(9), pages 1910-1920.

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