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Hedging Petroleum Futures with Multivariate GARCH Models

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  • Tanattrin Bunnag

    (Faculty of Science and Social Sciences, Burapha University, Thailand.)

Abstract

This paper examined the petroleum futures volatility comovements and spillovers for crude oil, gasoline, heat oil and natural gas. The results of volatility analysis were used to calculate the optimal two-petroleum portfolio weights and hedging ratios. The data used in this study was the daily data from 2009 to 2014. The three Multivariate GARCH models, namely the VAR (1)-diagonal VECH, the VAR (1)-diagonal BEKK and the VAR (1)-CCC, were employed. The empirical results overall showed that the estimates of the multivariate GARCH parameters were statistically significant in almost all cases except in the case of RGASOLINE with RNG. This indicates that the short run persistence of shocks on the dynamic conditional correlations was greatest for RCRUDE with RHEATOIL, while the largest long run persistence of shocks to the conditional correlations for RCRUDE with RGASOLINE. Finally, the results from these optimal portfolio weights base on the VAR (1)-diagonal VECH estimates suggested that investors should had more heat oil than crude oil and other petroleum in their portfolio to minimize risk without lowering the expected return.

Suggested Citation

  • Tanattrin Bunnag, 2015. "Hedging Petroleum Futures with Multivariate GARCH Models," International Journal of Energy Economics and Policy, Econjournals, vol. 5(1), pages 105-120.
    • Handle: RePEc:eco:journ2:2015-01-09
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    1. Moschini, GianCarlo & Myers, Robert J., 2002. "Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 589-603, December.
    2. Kuper, Gerard H. & Lestano, 2007. "Dynamic conditional correlation analysis of financial market interdependence: An application to Thailand and Indonesia," Journal of Asian Economics, Elsevier, vol. 18(4), pages 670-684, August.
    3. Bauwens, L. & Hafner, C.M. & Rombouts, J.V.K., 2007. "Multivariate mixed normal conditional heteroskedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3551-3566, April.
    4. Christodoulakis, George A., 2007. "Common volatility and correlation clustering in asset returns," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1263-1284, November.
    5. Sercan Demiralay & Hatice Gaye Gencer, 2014. "Volatility Transmissions between Oil Prices and Emerging Market Sectors: Implications for Portfolio Management and Hedging Strategies," International Journal of Energy Economics and Policy, Econjournals, vol. 4(3), pages 442-447.
    6. William J. Crowder & Anas Hamed, 1993. "A cointegration test for oil futures market efficiency," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 13(8), pages 933-941, December.
    7. Malik, Ali Khalil, 2005. "European exchange rate volatility dynamics: an empirical investigation," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 187-215, January.
    8. Nadhem Selmi & Nejib Hachicha, 2014. "Were Oil Price Markets the Source of Credit Crisis in European Countries? Evidence Using a VAR-MGARCH-DCC Model," International Journal of Energy Economics and Policy, Econjournals, vol. 4(2), pages 169-177.
    9. Emese Lazar & Carol Alexander, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336.
    10. Bradley Ewing & Cynthia Lay Harter, 2000. "Co-movements of Alaska North Slope and UK Brent crude oil prices," Applied Economics Letters, Taylor & Francis Journals, vol. 7(8), pages 553-558.
    11. Yen-Hsien Lee & Ya-Ling Huang & Chun-Yu Wu, 2014. "Dynamic Correlations and Volatility Spillovers between Crude Oil and Stock Index Returns: The Implications for Optimal Portfolio Construction," International Journal of Energy Economics and Policy, Econjournals, vol. 4(3), pages 327-336.
    12. Elisa Scarpa & Matteo Manera, 2008. "Pricing and hedging illiquid energy derivatives: An application to the JCC index," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(5), pages 464-487, May.
    13. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    14. Michael S. Haigh & Matthew T. Holt, 2002. "Hedging foreign currency, freight, and commodity futures portfolios—A note," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 22(12), pages 1205-1221, December.
    15. Kent D. Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 2001. "Overconfidence, Arbitrage, and Equilibrium Asset Pricing," Journal of Finance, American Finance Association, vol. 56(3), pages 921-965, June.
    16. Tse, Y. K., 2000. "A test for constant correlations in a multivariate GARCH model," Journal of Econometrics, Elsevier, vol. 98(1), pages 107-127, September.
    17. Param Silvapulle & Imad A. Moosa, 1999. "The relationship between spot and futures prices: Evidence from the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(2), pages 175-193, April.
    18. Plourde, André & Watkins, G. C., 1998. "Crude oil prices between 1985 and 1994: how volatile in relation to other commodities?," Resource and Energy Economics, Elsevier, vol. 20(3), pages 245-262, September.
    19. Emilio Peroni & Robert McNown, 1998. "Noninformative and informative tests of efficiency in three energy futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 18(8), pages 939-964, December.
    20. Alizadeh, Amir H. & Nomikos, Nikos K. & Pouliasis, Panos K., 2008. "A Markov regime switching approach for hedging energy commodities," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1970-1983, September.
    21. Lee, Hsiu-Yun & Chen, Show-Lin, 2006. "Why use Markov-switching models in exchange rate prediction?," Economic Modelling, Elsevier, vol. 23(4), pages 662-668, July.
    22. Hammoudeh, Shawkat & Yuan, Yuan, 2008. "Metal volatility in presence of oil and interest rate shocks," Energy Economics, Elsevier, vol. 30(2), pages 606-620, March.
    23. Amir Alizadeh & Nikos Nomikos, 2004. "A Markov regime switching approach for hedging stock indices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(7), pages 649-674, July.
    24. April Knill & Kristina Minnick & Ali Nejadmalayeri, 2006. "Selective Hedging, Information Asymmetry, and Futures Prices," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1475-1502, May.
    25. Imad A. Moosa & Nabeel E. Al‐Loughani, 1995. "The effectiveness of arbitrage and speculation in the crude oil futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 15(2), pages 167-186, April.
    26. Lin, Sharon Xiaowen & Tamvakis, Michael N., 2001. "Spillover effects in energy futures markets," Energy Economics, Elsevier, vol. 23(1), pages 43-56, January.
    27. 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.
    28. Sebastian Edwards & Raul Susmel, 2003. "Interest-Rate Volatility in Emerging Markets," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 328-348, May.
    29. Kearney, Colm & Patton, Andrew J, 2000. "Multivariate GARCH Modeling of Exchange Rate Volatility Transmission in the European Monetary System," The Financial Review, Eastern Finance Association, vol. 35(1), pages 29-48, February.
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    Cited by:

    1. Lebotsa Daniel Metsileng & Ntebogang Dinah Moroke & Johannes Tshepiso Tsoku, 2020. "The Application of the Multivariate GARCH Models on the BRICS Exchange Rates," Academic Journal of Interdisciplinary Studies, Richtmann Publishing Ltd, vol. 9, July.
    2. Tanattrin Bunnag, 2015. "Volatility Transmission in Oil Futures Markets and Carbon Emissions Futures," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 647-659.
    3. Tanattrin Bunnag, 2016. "Volatility Transmission in Crude Oil, Gold, Standard and Poor s 500 and US Dollar Index Futures using Vector Autoregressive Multivariate Generalized Autoregressive Conditional Heteroskedasticity Model," International Journal of Energy Economics and Policy, Econjournals, vol. 6(1), pages 39-52.

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    More about this item

    Keywords

    The petroleum futures volatility; comovements and spillovers; multivariate GARCH models; optimal portfolio weights; hedging ratios;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • 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
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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