IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v66y2017icp493-507.html
   My bibliography  Save this article

Hedging downside risk of oil refineries: A vine copula approach

Author

Listed:
  • Sukcharoen, Kunlapath
  • Leatham, David J.

Abstract

The financial health of an oil refinery greatly depends on its refining margin or the difference between the prices of its refined products (typically, gasoline and heating oil) and the cost of crude oil. The refinery may hedge against the downside risk of unfavorable price movements using crude oil, gasoline, and heating oil futures. This paper examines the use of a vine copula approach to estimate multiproduct hedge ratios that minimize the downside risk of the refinery. The advantage of the vine copula approach is that it allows us to capture important characteristics of petroleum price changes, including skewness and fat-tailedness in the marginal distributions of individual price change series as well as heterogeneous (tail) dependence patterns between different pairs of price changes. The out-of-sample hedging effectiveness of two popular classes of vine copula models – canonical (C-) and drawable (D-) vine copula models – are evaluated and compared with that of the widely used nonparametric method and three standard multivariate copula models. The empirical results reveal that the D-vine copula model is a good and safe choice in managing the downside risk of the refinery.

Suggested Citation

  • Sukcharoen, Kunlapath & Leatham, David J., 2017. "Hedging downside risk of oil refineries: A vine copula approach," Energy Economics, Elsevier, vol. 66(C), pages 493-507.
    • Handle: RePEc:eee:eneeco:v:66:y:2017:i:c:p:493-507
    DOI: 10.1016/j.eneco.2017.07.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988317302499
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2017.07.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Donald Lien & Yiu Kuen Tse, 2000. "Hedging downside risk with futures contracts," Applied Financial Economics, Taylor & Francis Journals, vol. 10(2), pages 163-170.
    2. David E. Allen & Mohammad A. Ashraf & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2013. "Financial dependence analysis: applications of vine copulas," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(4), pages 403-435, November.
    3. Unser, Matthias, 2000. "Lower partial moments as measures of perceived risk: An experimental study," Journal of Economic Psychology, Elsevier, vol. 21(3), pages 253-280, June.
    4. Demirer, Riza & Lien, Donald, 2003. "Downside risk for short and long hedgers," International Review of Economics & Finance, Elsevier, vol. 12(1), pages 25-44.
    5. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    6. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    7. Chang, C-L. & McAleer, M.J. & Tansuchat, R., 2010. "Analyzing and Forecasting Volatility Spillovers and Asymmetries in Major Crude Oil Spot, Forward and Futures Markets," Econometric Institute Research Papers EI 2010-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Serra, Teresa & Gil, José M., 2012. "Biodiesel as a motor fuel price stabilization mechanism," Energy Policy, Elsevier, vol. 50(C), pages 689-698.
    9. Óscar Carchano & Ángel Pardo, 2009. "Rolling over stock index futures contracts," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 29(7), pages 684-694, July.
    10. Thomas Conlon & John Cotter, 2012. "An empirical analysis of dynamic multiscale hedging using wavelet decomposition," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(3), pages 272-299, March.
    11. Veld, Chris & Veld-Merkoulova, Yulia V., 2008. "The risk perceptions of individual investors," Journal of Economic Psychology, Elsevier, vol. 29(2), pages 226-252, April.
    12. Fishburn, Peter C, 1977. "Mean-Risk Analysis with Risk Associated with Below-Target Returns," American Economic Review, American Economic Association, vol. 67(2), pages 116-126, March.
    13. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2010. "Analyzing and forecasting volatility spillovers, asymmetries and hedging in major oil markets," Energy Economics, Elsevier, vol. 32(6), pages 1445-1455, November.
    14. 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.
    15. Alexander, Carol & Prokopczuk, Marcel & Sumawong, Anannit, 2013. "The (de)merits of minimum-variance hedging: Application to the crack spread," Energy Economics, Elsevier, vol. 36(C), pages 698-707.
    16. Eric Bouye & Mark Salmon, 2009. "Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 721-750.
    17. Brechmann, Eike Christian & Schepsmeier, Ulf, 2013. "Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i03).
    18. Liu, Pan & Vedenov, Dmitry & Power, Gabriel J., 2017. "Is hedging the crack spread no longer all it's cracked up to be?," Energy Economics, Elsevier, vol. 63(C), pages 31-40.
    19. Michael S. Haigh & Matthew T. Holt, 2002. "Crack spread hedging: accounting for time-varying volatility spillovers in the energy futures markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(3), pages 269-289.
    20. Dißmann, J. & Brechmann, E.C. & Czado, C. & Kurowicka, D., 2013. "Selecting and estimating regular vine copulae and application to financial returns," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 52-69.
    21. Gabriel J. Power & Dmitry Vedenov, 2010. "Dealing with downside risk in a multi‐commodity setting: A case for a “Texas hedge”?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(3), pages 290-304, March.
    22. Luca Riccetti, 2013. "A copula–GARCH model for macro asset allocation of a portfolio with commodities," Empirical Economics, Springer, vol. 44(3), pages 1315-1336, June.
    23. Zhiguang Cao & Richard D.F. Harris & Jian Shen, 2010. "Hedging and value at risk: A semi‐parametric approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(8), pages 780-794, August.
    24. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Dependence and extreme dependence of crude oil and natural gas prices with applications to risk management," Energy Economics, Elsevier, vol. 42(C), pages 332-342.
    25. McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
    26. Hsiang‐Tai Lee, 2009. "A copula‐based regime‐switching GARCH model for optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 29(10), pages 946-972, October.
    27. Kunlapath Sukcharoen & Hankyeung Choi & David J. Leatham, 2015. "Optimal gasoline hedging strategies using futures contracts and exchange-traded funds," Applied Economics, Taylor & Francis Journals, vol. 47(32), pages 3482-3498, July.
    28. Awudu, Iddrisu & Wilson, William & Dahl, Bruce, 2016. "Hedging strategy for ethanol processing with copula distributions," Energy Economics, Elsevier, vol. 57(C), pages 59-65.
    29. Chih‐Chiang Hsu & Chih‐Ping Tseng & Yaw‐Huei Wang, 2008. "Dynamic hedging with futures: A copula‐based GARCH model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(11), pages 1095-1116, November.
    30. Bekiros, Stelios & Hernandez, Jose Arreola & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2015. "Multivariate dependence risk and portfolio optimization: An application to mining stock portfolios," Resources Policy, Elsevier, vol. 46(P2), pages 1-11.
    31. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
    32. David M. Zimmer, 2015. "Analyzing Comovements In Housing Prices Using Vine Copulas," Economic Inquiry, Western Economic Association International, vol. 53(2), pages 1156-1169, April.
    33. Richard D. F. Harris & Jian Shen, 2006. "Hedging and value at risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(4), pages 369-390, April.
    34. Ji, Qiang & Fan, Ying, 2011. "A dynamic hedging approach for refineries in multiproduct oil markets," Energy, Elsevier, vol. 36(2), pages 881-887.
    35. Zhang, Dalu, 2014. "Vine copulas and applications to the European Union sovereign debt analysis," International Review of Financial Analysis, Elsevier, vol. 36(C), pages 46-56.
    36. Songjiao Chen & William Wilson & Ryan Larsen & Bruce Dahl, 2016. "Risk Management for Grain Processors and “Copulas”," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(2), pages 365-382, June.
    37. Pritsker, Matthew, 2006. "The hidden dangers of historical simulation," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 561-582, February.
    38. Conlon, Thomas & Cotter, John, 2013. "Downside risk and the energy hedger's horizon," Energy Economics, Elsevier, vol. 36(C), pages 371-379.
    39. Brechmann, Eike & Czado, Claudia & Paterlini, Sandra, 2014. "Flexible dependence modeling of operational risk losses and its impact on total capital requirements," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 271-285.
    40. Massimiliano Barbi & Silvia Romagnoli, 2014. "A Copula‐Based Quantile Risk Measure Approach to Estimate the Optimal Hedge Ratio," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(7), pages 658-675, July.
    41. 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.
    42. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
    43. Low, Rand Kwong Yew & Alcock, Jamie & Faff, Robert & Brailsford, Timothy, 2013. "Canonical vine copulas in the context of modern portfolio management: Are they worth it?," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3085-3099.
    44. Donald Lien & Yiu Kuen Tse, 1998. "Hedging time‐varying downside risk," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 18(6), pages 705-722, September.
    Full references (including those not matched with items on IDEAS)

    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. Arunanondchai, Panit & Sukcharoen, Kunlapath & Leatham, David J., 2020. "Dealing with tail risk in energy commodity markets: Futures contracts versus exchange-traded funds," Journal of Commodity Markets, Elsevier, vol. 20(C).
    2. Vedenov, Dmitry & Power, Gabriel J., 2022. "We don't need no fancy hedges! Or do we?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    3. Ubukata, Masato, 2018. "Dynamic hedging performance and downside risk: Evidence from Nikkei index futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 270-281.
    4. Kjersti Aas, 2016. "Pair-Copula Constructions for Financial Applications: A Review," Econometrics, MDPI, vol. 4(4), pages 1-15, October.
    5. Maziar Sahamkhadam & Andreas Stephan, 2019. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for the financial crisis," Papers 1912.10328, arXiv.org.
    6. Power, Gabriel J. & Vedenov, Dmitry, 2023. "Who's afraid of a Texas hedge?," Energy Economics, Elsevier, vol. 127(PB).
    7. Cao, Min & Conlon, Thomas, 2023. "Composite jet fuel cross-hedging," Journal of Commodity Markets, Elsevier, vol. 30(C).
    8. Wang, Yudong & Geng, Qianjie & Meng, Fanyi, 2019. "Futures hedging in crude oil markets: A comparison between minimum-variance and minimum-risk frameworks," Energy, Elsevier, vol. 181(C), pages 815-826.
    9. Liu, Pan & Vedenov, Dmitry & Power, Gabriel J., 2017. "Is hedging the crack spread no longer all it's cracked up to be?," Energy Economics, Elsevier, vol. 63(C), pages 31-40.
    10. Huang, Wanling & Mollick, André Varella & Nguyen, Khoa Huu, 2016. "U.S. stock markets and the role of real interest rates," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 231-242.
    11. Fei, Chengcheng & Vedenov, Dmitry & Stevens, Reid B. & Anderson, David, 2021. "Single-Commodity vs. Joint Hedging in Cattle Feeding Cycle: Is Joint Hedging Always Essential?," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 46(3), September.
    12. Kunlapath Sukcharoen & Hankyeung Choi & David J. Leatham, 2015. "Optimal gasoline hedging strategies using futures contracts and exchange-traded funds," Applied Economics, Taylor & Francis Journals, vol. 47(32), pages 3482-3498, July.
    13. Wanling Huang & André Varella Mollick & Khoa Huu Nguyen, 2017. "Dynamic responses and tail-dependence among commodities, the US real interest rate and the dollar," Empirical Economics, Springer, vol. 53(3), pages 959-997, November.
    14. Barbi, Massimiliano & Romagnoli, Silvia, 2018. "Skewness, basis risk, and optimal futures demand," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 14-29.
    15. Wenming Shi & Kevin X. Li & Zhongzhi Yang & Ganggang Wang, 2017. "Time-varying copula models in the shipping derivatives market," Empirical Economics, Springer, vol. 53(3), pages 1039-1058, November.
    16. Han, Xuyuan & Liu, Zhenya & Wang, Shixuan, 2022. "An R-vine copula analysis of non-ferrous metal futures with application in Value-at-Risk forecasting," Journal of Commodity Markets, Elsevier, vol. 25(C).
    17. Chai, Shanglei & Zhou, P., 2018. "The Minimum-CVaR strategy with semi-parametric estimation in carbon market hedging problems," Energy Economics, Elsevier, vol. 76(C), pages 64-75.
    18. Qianjie Geng & Yudong Wang, 2021. "Futures Hedging in CSI 300 Markets: A Comparison Between Minimum-Variance and Maximum-Utility Frameworks," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 719-742, February.
    19. Chang, Chia-Lin & McAleer, Michael & Wang, Yanghuiting, 2018. "Testing Co-Volatility spillovers for natural gas spot, futures and ETF spot using dynamic conditional covariances," Energy, Elsevier, vol. 151(C), pages 984-997.
    20. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.

    More about this item

    Keywords

    Downside risk; Energy hedging; Futures hedging; Multiproduct hedging; Vine copula;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

    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:eee:eneeco:v:66:y:2017:i:c:p:493-507. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.