IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v80y2023ics0301420722005906.html
   My bibliography  Save this article

Futures hedging in crude oil markets: A trade-off between risk and return

Author

Listed:
  • Yu, Xing
  • Li, Yanyan
  • Lu, Junli
  • Shen, Xilin

Abstract

Risk and return are two fundamentals that have an impact on an investor’s or hedger’s investing choices. Based on the proposed synchronous movement intensity index, this paper aims to improve the hedging performance by adjusting the model-driven hedge ratio and realize the trade-off between return and risk in futures hedging. First, without loss of generality, we forecast crude oil spot and futures volatility using 10 GARCH-type models, including three linear models and seven nonlinear models, to obtain the ex-ante hedging ratio under the minimum variance framework. Then, we develop a novel and tractable method to identify the market state based on the index of consistency intensity, in which the index portrays the synchronous degree of stock price movements in the energy sector. Last but not least, we propose the hedge ratio adjustment criteria based on the identified state, and adjust the ratio driven by GARCH-type models of futures in accordance with the market state. Empirical results of crude oil futures markets indicate that the proposed state-dependent hedging model is superior to the commonly used models in terms of three criteria including mean of returns, variance, and ratio of mean to variance of returns for measuring hedging effect. We apply the DM test to make a statistical inference and discover that while the mean and the ratio of mean to variance of returns are increasing, the variance and hedging effectiveness of the hedged portfolio based on the modified methods are not significantly affected. Furthermore, the superiority of the proposed method is robust to different market conditions, including significant rising or falling trends, large basis, and COVID-19 pandemic. We also test the robustness of the proposed method with respect to the baseline model, quantile, and evaluation window. Overall, this paper provides a more realistic approach for crude oil risk managers to hedge crude oil price risk, some corresponding implications are also concluded.

Suggested Citation

  • Yu, Xing & Li, Yanyan & Lu, Junli & Shen, Xilin, 2023. "Futures hedging in crude oil markets: A trade-off between risk and return," Resources Policy, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:jrpoli:v:80:y:2023:i:c:s0301420722005906
    DOI: 10.1016/j.resourpol.2022.103147
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420722005906
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2022.103147?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. Peter Nystrup & Henrik Madsen & Erik Lindstr�m, 2015. "Stylised facts of financial time series and hidden Markov models in continuous time," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1531-1541, September.
    2. Tiwari, Aviral Kumar & Jena, Sangram Keshari & Mitra, Amarnath & Yoon, Seong-Min, 2018. "Impact of oil price risk on sectoral equity markets: Implications on portfolio management," Energy Economics, Elsevier, vol. 72(C), pages 120-134.
    3. Robert J. Myers & Stanley R. Thompson, 1989. "Generalized Optimal Hedge Ratio Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 71(4), pages 858-868.
    4. Cecchetti, Stephen G & Cumby, Robert E & Figlewski, Stephen, 1988. "Estimation of the Optimal Futures Hedge," The Review of Economics and Statistics, MIT Press, vol. 70(4), pages 623-630, November.
    5. Wei-Han Liu, 2014. "Optimal hedge ratio estimation and hedge effectiveness with multivariate skew distributions," Applied Economics, Taylor & Francis Journals, vol. 46(12), pages 1420-1435, April.
    6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    7. Mark G. Castelino, 1992. "Hedge effectiveness: Basis risk and minimum‐variance hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 12(2), pages 187-201, April.
    8. Fong, Wai Mun & See, Kim Hock, 2002. "A Markov switching model of the conditional volatility of crude oil futures prices," Energy Economics, Elsevier, vol. 24(1), pages 71-95, January.
    9. Chao‐Chun Chen & Wen‐Jen Tsay, 2011. "A Markov regime‐switching ARMA approach for hedging stock indices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(2), pages 165-191, February.
    10. Mensi, Walid & Hammoudeh, Shawkat & Vinh Vo, Xuan & Hoon Kang, Sang, 2021. "Volatility spillovers between oil and equity markets and portfolio risk implications in the US and vulnerable EU countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    11. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 535-551, December.
    12. Baillie, Richard T & Myers, Robert J, 1991. "Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(2), pages 109-124, April-Jun.
    13. Philip, Dennis & Shi, Yukun, 2016. "Optimal hedging in carbon emission markets using Markov regime switching models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 1-15.
    14. 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.
    15. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2018. "Markov switching GARCH models for Bayesian hedging on energy futures markets," Energy Economics, Elsevier, vol. 70(C), pages 545-562.
    16. Lu‐Tao Zhao & Ya Meng & Yue‐Jun Zhang & Yun‐Tao Li, 2019. "The optimal hedge strategy of crude oil spot and futures markets: Evidence from a novel method," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 186-203, January.
    17. Scarcioffolo, Alexandre R. & Etienne, Xiaoli L., 2021. "Regime-switching energy price volatility: The role of economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 336-356.
    18. Wang, Hu & Li, Shouwei, 2021. "Asymmetric volatility spillovers between crude oil and China's financial markets," Energy, Elsevier, vol. 233(C).
    19. Trucíos, Carlos, 2019. "Forecasting Bitcoin risk measures: A robust approach," International Journal of Forecasting, Elsevier, vol. 35(3), pages 836-847.
    20. Stephen Figlewski, 1985. "Hedging with stock index futures: Theory and application in a new market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 5(2), pages 183-199, June.
    21. Liu, Yue & Sun, Huaping & Zhang, Jijian & Taghizadeh-Hesary, Farhad, 2020. "Detection of volatility regime-switching for crude oil price modeling and forecasting," Resources Policy, Elsevier, vol. 69(C).
    22. 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.
    23. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    24. Shiferaw, Yegnanew A., 2019. "Time-varying correlation between agricultural commodity and energy price dynamics with Bayesian multivariate DCC-GARCH models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    25. Chen, Ren-Raw & Leistikow, Dean & Wang, Andrew, 2020. "Futures minimum variance hedge ratio determination: An ex-ante analysis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    26. Hung, Jui-Cheng & Yi-Hsien Wang, & Chang, Matthew C. & Shih, Kuang-Hsun & Hsiu-Hsueh Kao,, 2011. "Minimum variance hedging with bivariate regime-switching model for WTI crude oil," Energy, Elsevier, vol. 36(5), pages 3050-3057.
    27. Swanson, Norman R. & Elliott, Graham & Ghysels, Eric & Gonzalo, Jesus, 2006. "Predictive methodology and application in economics and finance: Volume in honor of the accomplishments of Clive W.J. Granger," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 1-9.
    28. Campani, Carlos Heitor & Garcia, René & Lewin, Marcelo, 2021. "Optimal portfolio strategies in the presence of regimes in asset returns," Journal of Banking & Finance, Elsevier, vol. 123(C).
    29. Donald Lien, 2012. "A note on the performance of regime switching hedge strategy," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(4), pages 389-396, April.
    30. Leland L. Johnson, 1976. "The Theory of Hedging and Speculation in Commodity Futures," Palgrave Macmillan Books, in: The Economics of Futures Trading, chapter 3, pages 83-99, Palgrave Macmillan.
    31. Robert J. Myers, 1991. "Estimating time‐varying optimal hedge ratios on futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 11(1), pages 39-53, February.
    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. Yu, Xing & Shen, Xilin & Li, Yanyan & Gong, Xue, 2023. "Selective hedging strategies for crude oil futures based on market state expectations," Global Finance Journal, Elsevier, vol. 57(C).
    2. Xianling Ren & Xinping Yu, 2024. "Hedging performance analysis of energy markets: Evidence from copula quantile regression," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(3), pages 432-450, March.
    3. Yu, Xing & Li, Yanyan & Zhao, Qian, 2024. "Research on optimization strategy of futures hedging dependent on market state," Applied Energy, Elsevier, vol. 373(C).

    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. Stavros Degiannakis & Christos Floros & Enrique Salvador & Dimitrios Vougas, 2022. "On the stationarity of futures hedge ratios," Operational Research, Springer, vol. 22(3), pages 2281-2303, July.
    2. Čech, František & Zítek, Michal, 2022. "Marine fuel hedging under the sulfur cap regulations," Energy Economics, Elsevier, vol. 113(C).
    3. Zhipeng, Yan & Shenghong, Li, 2018. "Hedge ratio on Markov regime-switching diagonal Bekk–Garch model," Finance Research Letters, Elsevier, vol. 24(C), pages 49-55.
    4. 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.
    5. Goswami, Alankrita & Karali, Berna & Adjemian, Michael K., 2023. "Hedging with futures during nonconvergence in commodity markets," Journal of Commodity Markets, Elsevier, vol. 32(C).
    6. 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.
    7. Shashi Gupta & Himanshu Choudhary & D.R. Agarwal, 2017. "Hedging Efficiency of Indian Commodity Futures," Paradigm, , vol. 21(1), pages 1-20, June.
    8. Chun, Dohyun & Cho, Hoon & Kim, Jihun, 2019. "Crude oil price shocks and hedging performance: A comparison of volatility models," Energy Economics, Elsevier, vol. 81(C), pages 1132-1147.
    9. Yu, Xing & Li, Yanyan & Zhao, Qian, 2024. "Research on optimization strategy of futures hedging dependent on market state," Applied Energy, Elsevier, vol. 373(C).
    10. Michael S. Haigh & Matthew T. Holt, 2002. "Combining time-varying and dynamic multi-period optimal hedging models," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 29(4), pages 471-500, December.
    11. Martínez, Beatriz & Torró, Hipòlit, 2015. "European natural gas seasonal effects on futures hedging," Energy Economics, Elsevier, vol. 50(C), pages 154-168.
    12. Bessler, Wolfgang & Leonhardt, Alexander & Wolff, Dominik, 2016. "Analyzing hedging strategies for fixed income portfolios: A Bayesian approach for model selection," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 239-256.
    13. Dinica, Mihai Cristian & Armeanu, Daniel, 2014. "The Optimal Hedging Ratio for Non-Ferrous Metals," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 105-122, March.
    14. Alizadeh, Amir H. & Huang, Chih-Yueh & van Dellen, Stefan, 2015. "A regime switching approach for hedging tanker shipping freight rates," Energy Economics, Elsevier, vol. 49(C), pages 44-59.
    15. Yu, Xing & Shen, Xilin & Li, Yanyan & Gong, Xue, 2023. "Selective hedging strategies for crude oil futures based on market state expectations," Global Finance Journal, Elsevier, vol. 57(C).
    16. 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.
    17. Chen, Xiangyu & Tongurai, Jittima, 2021. "Cross-commodity hedging for illiquid futures: Evidence from China's base metal futures market," Global Finance Journal, Elsevier, vol. 49(C).
    18. 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.
    19. Cifarelli, Giulio & Paladino, Giovanna, 2011. "Hedging vs. speculative pressures on commodity futures returns," MPRA Paper 28229, University Library of Munich, Germany.
    20. Aragó, Vicent & Salvador, Enrique, 2011. "Sudden changes in variance and time varying hedge ratios," European Journal of Operational Research, Elsevier, vol. 215(2), pages 393-403, December.

    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:jrpoli:v:80:y:2023:i:c:s0301420722005906. 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/inca/30467 .

    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.