IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2015-01-09.html
   My bibliography  Save this article

Hedging Petroleum Futures with Multivariate GARCH Models

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.econjournals.com/index.php/ijeep/article/view/1006/572
    Download Restriction: no
    File URL: http://www.econjournals.com/index.php/ijeep/article/download/1006/572
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," The Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. Lin, Sharon Xiaowen & Tamvakis, Michael N., 2001. "Spillover effects in energy futures markets," Energy Economics, Elsevier, vol. 23(1), pages 43-56, January.
    23. Malik, Ali Khalil, 2005. "European exchange rate volatility dynamics: an empirical investigation," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 187-215, January.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohamed Osman, 2015. "Dynamic Asymmetries in the Electric Consumption of the GCC Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 5(2), pages 461-467.
    2. Su, EnDer, 2017. "Stock index hedging using a trend and volatility regime-switching model involving hedging cost," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 233-254.
    3. Kuang-Liang Chang, 2011. "The optimal value-at-risk hedging strategy under bivariate regime switching ARCH framework," Applied Economics, Taylor & Francis Journals, vol. 43(21), pages 2627-2640.
    4. Zouheir Mighri & Faysal Mansouri, 2013. "Dynamic Conditional Correlation Analysis of Stock Market Contagion: Evidence from the 2007-2010 Financial Crises," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 637-661.
    5. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    6. Gannon, Gerard L. & Thuraisamy, Kannan S., 2017. "Sovereign risk and the impact of crisis: Evidence from Latin AmericaAuthor-Name: Batten, Jonathan A," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 328-350.
    7. Su, EnDer, 2013. "Stock index hedge using trend and volatility regime switch model considering hedging cost," MPRA Paper 49190, University Library of Munich, Germany.
    8. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Dynamic frequency relationships and volatility spillovers in natural gas, crude oil, gas oil, gasoline, and heating oil markets: Implications for portfolio management," Resources Policy, Elsevier, vol. 73(C).
    9. Hsiang‐Tai Lee, 2022. "A Markov regime‐switching Cholesky GARCH model for directly estimating the dynamic of optimal hedge ratio," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 389-412, March.
    10. Hao Chen & Zhixin Liu & Yinpeng Zhang & You Wu, 2020. "The Linkages of Carbon Spot-Futures: Evidence from EU-ETS in the Third Phase," Sustainability, MDPI, vol. 12(6), pages 1-18, March.
    11. Kao, Chung-Wei & Wan, Jer-Yuh, 2009. "Information transmission and market interactions across the Atlantic -- an empirical study on the natural gas market," Energy Economics, Elsevier, vol. 31(1), pages 152-161, January.
    12. Ahmed Ghorbel & Wajdi Hamma & Anis Jarboui, 2017. "Dependence between oil and commodities markets using time-varying Archimedean copulas and effectiveness of hedging strategies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(9), pages 1509-1542, July.
    13. Yudong Wang & Chongfeng Wu & Li Yang, 2015. "Hedging with Futures: Does Anything Beat the Naïve Hedging Strategy?," Management Science, INFORMS, vol. 61(12), pages 2870-2889, December.
    14. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    15. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    16. Bubák, Vít & Kocenda, Evzen & Zikes, Filip, 2011. "Volatility transmission in emerging European foreign exchange markets," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2829-2841, November.
    17. Ewing, Bradley T. & Malik, Farooq, 2005. "Re-examining the asymmetric predictability of conditional variances: The role of sudden changes in variance," Journal of Banking & Finance, Elsevier, vol. 29(10), pages 2655-2673, October.
    18. Dimitriou, Dimitrios & Mpitsios, Petros & Simos, Theodore, 2011. "Dynamic linkages and interdependence between Mediterranean region EMU markets during 2007 financial crisis," MPRA Paper 37476, University Library of Munich, Germany.
    19. Ngene, Geoffrey & Post, Jordin A. & Mungai, Ann N., 2018. "Volatility and shock interactions and risk management implications: Evidence from the U.S. and frontier markets," Emerging Markets Review, Elsevier, vol. 37(C), pages 181-198.
    20. El Hedi Arouri, Mohamed & Lahiani, Amine & Nguyen, Duc Khuong, 2015. "World gold prices and stock returns in China: Insights for hedging and diversification strategies," Economic Modelling, Elsevier, vol. 44(C), pages 273-282.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eco:journ2:2015-01-09. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.