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An Investigation of Some Hedging Strategies for Crude Oil Market

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  • Andre Assis de Salles

    (Industrial Engineering Department Polytechnic School, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil)

Abstract

This paper examines the performance of bivariate volatility models for the crude oil spot and future returns of the WTI type barrel prices. Besides the volatility of spot and future crude oil barrel returns time series, the hedge ratio strategy is examined through the hedge effectiveness. Thus this study shows hedge strategies built using methodologies applied in the variance modelling of returns of crude oil prices in the spot and future markets, and covariance between these two market returns, which correspond to the inputs of the hedge strategy shown in this work. From the studied models the bivariate GARCH in a Diagonal VECH and BEKK representations was chosen, using three different models for the mean: a bivariate autoregressive, a vector autoregressive and a vector error correction. The methodologies used here take into consideration the denial of assumptions of homoscedasticity and normality for the return distributions making them more realistic.

Suggested Citation

  • Andre Assis de Salles, 2013. "An Investigation of Some Hedging Strategies for Crude Oil Market," International Journal of Energy Economics and Policy, Econjournals, vol. 3(1), pages 51-59.
    • Handle: RePEc:eco:journ2:2013-01-6
    as

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    References listed on IDEAS

    as
    1. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2011. "Crude oil hedging strategies using dynamic multivariate GARCH," Energy Economics, Elsevier, vol. 33(5), pages 912-923, September.
    2. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-170, March.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    5. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    6. 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.
    7. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    8. 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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Volatility Models; Future Markets; Hedge Ratio; Hedge Effectiveness; Crude Oil Market;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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