IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v40y2020i7p1090-1108.html
   My bibliography  Save this article

Optimal futures hedging for energy commodities: An application of the GAS model

Author

Listed:
  • Yingying Xu
  • Donald Lien

Abstract

This paper applies generalized autoregressive score‐driven (GAS) models to futures hedging of crude oil and natural gas. For both commodities, the GAS framework captures the marginal distributions of spot and futures returns and corresponding dynamic copula correlations. We compare within‐sample and out‐of‐sample hedging effectiveness of GAS models against constant ordinary least square (OLS) strategy and time‐varying copula‐based GARCH models in terms of volatility reduction and Value at Risk reduction. We show that the constant OLS hedge ratio is not inherently inferior to the time‐varying alternatives. Nonetheless, GAS models tend to exhibit better hedging effectiveness than other strategies, particularly for natural gas.

Suggested Citation

  • Yingying Xu & Donald Lien, 2020. "Optimal futures hedging for energy commodities: An application of the GAS model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1090-1108, July.
    • Handle: RePEc:wly:jfutmk:v:40:y:2020:i:7:p:1090-1108
    DOI: 10.1002/fut.22118
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/fut.22118
    Download Restriction: no
    File URL: https://libkey.io/10.1002/fut.22118?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
    ---><---

    References listed on IDEAS

    as
    1. Donald Lien & Keshab Shrestha, 2007. "An empirical analysis of the relationship between hedge ratio and hedging horizon using wavelet analysis," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(2), pages 127-150, February.
    2. Manabu Asai & Michael McAleer & Jun Yu, 2006. "Multivariate Stochastic Volatility: A Review," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 145-175.
    3. Shrestha, Keshab & Subramaniam, Ravichandran & Rassiah, Puspavathy, 2017. "Pure martingale and joint normality tests for energy futures contracts," Energy Economics, Elsevier, vol. 63(C), pages 174-184.
    4. Donald Lien & Y. K. Tse & Albert Tsui, 2002. "Evaluating the hedging performance of the constant-correlation GARCH model," Applied Financial Economics, Taylor & Francis Journals, vol. 12(11), pages 791-798.
    5. Yu‐Sheng Lai, 2018. "Estimation of the optimal futures hedge ratio for equity index portfolios using a realized beta generalized autoregressive conditional heteroskedasticity model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1370-1390, November.
    6. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    7. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    8. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    9. 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.
    10. 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.
    11. Mr. James Daniel, 2001. "Hedging Government Oil Price Risk," IMF Working Papers 2001/185, International Monetary Fund.
    12. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    13. Zhou, Jian, 2016. "Hedging performance of REIT index futures: A comparison of alternative hedge ratio estimation methods," Economic Modelling, Elsevier, vol. 52(PB), pages 690-698.
    14. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
    15. Donald Lien & Hsiang‐Tai Lee & Her‐Jiun Sheu, 2018. "Hedging systematic risk in the commodity market with a regime‐switching multivariate rotated generalized autoregressive conditional heteroskedasticity model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(12), pages 1514-1532, December.
    16. Lien, Donald, 2009. "A note on the hedging effectiveness of GARCH models," International Review of Economics & Finance, Elsevier, vol. 18(1), pages 110-112, January.
    17. Manabu Asai & Michael McAleer & Jun Yu, 2006. "Multivariate Stochastic Volatility," Microeconomics Working Papers 22058, East Asian Bureau of Economic Research.
    18. 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.
    19. Chen, Rongda & Xu, Jianjun, 2019. "Forecasting volatility and correlation between oil and gold prices using a novel multivariate GAS model," Energy Economics, Elsevier, vol. 78(C), pages 379-391.
    20. Drew Creal & Siem Jan Koopman & André Lucas, 2013. "Generalized Autoregressive Score Models With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 777-795, August.
    21. Sheng‐Syan Chen & Cheng‐Few Lee & Keshab Shrestha, 2004. "An empirical analysis of the relationship between the hedge ratio and hedging horizon: A simultaneous estimation of the short‐ and long‐run hedge ratios," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(4), pages 359-386, April.
    22. Donald Lien, 2005. "A note on the superiority of the OLS hedge ratio," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 25(11), pages 1121-1126, November.
    23. Sari, Ramazan & Hammoudeh, Shawkat & Soytas, Ugur, 2010. "Dynamics of oil price, precious metal prices, and exchange rate," Energy Economics, Elsevier, vol. 32(2), pages 351-362, March.
    24. Jain, Anshul & Biswal, P.C., 2016. "Dynamic linkages among oil price, gold price, exchange rate, and stock market in India," Resources Policy, Elsevier, vol. 49(C), pages 179-185.
    25. Singhal, Shelly & Ghosh, Sajal, 2016. "Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models," Resources Policy, Elsevier, vol. 50(C), pages 276-288.
    26. Ding, Liang & Vo, Minh, 2012. "Exchange rates and oil prices: A multivariate stochastic volatility analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(1), pages 15-37.
    27. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
    28. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
    29. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2006. "Analysis of high dimensional multivariate stochastic volatility models," Journal of Econometrics, Elsevier, vol. 134(2), pages 341-371, October.
    30. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Yoon, Seong-Min, 2014. "Dynamic spillovers among major energy and cereal commodity prices," Energy Economics, Elsevier, vol. 43(C), pages 225-243.
    31. Chris Brooks & Olan T. Henry & Gita Persand, 2002. "The Effect of Asymmetries on Optimal Hedge Ratios," The Journal of Business, University of Chicago Press, vol. 75(2), pages 333-352, April.
    32. Gourieroux, C. & Jasiak, J. & Sufana, R., 2009. "The Wishart Autoregressive process of multivariate stochastic volatility," Journal of Econometrics, Elsevier, vol. 150(2), pages 167-181, June.
    33. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    34. Shrestha, Keshab & Subramaniam, Ravichandran & Peranginangin, Yessy & Philip, Sheena Sara Suresh, 2018. "Quantile hedge ratio for energy markets," Energy Economics, Elsevier, vol. 71(C), pages 253-272.
    35. Maghyereh, Aktham I. & Awartani, Basel & Tziogkidis, Panagiotis, 2017. "Volatility spillovers and cross-hedging between gold, oil and equities: Evidence from the Gulf Cooperation Council countries," Energy Economics, Elsevier, vol. 68(C), pages 440-453.
    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. Chang, Kuang-Liang, 2023. "The low-magnitude and high-magnitude asymmetries in tail dependence structures in international equity markets and the role of bilateral exchange rate," Journal of International Money and Finance, Elsevier, vol. 133(C).
    2. Haiying Wang & Ying Yuan & Tianyang Wang, 2021. "The dynamics of cross‐boundary fire—Financial contagion between the oil and stock markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(10), pages 1655-1673, October.
    3. Sharma, Udayan & Karmakar, Madhusudan, 2023. "Measuring minimum variance hedging effectiveness: Traditional vs. sophisticated models," International Review of Financial Analysis, Elsevier, vol. 87(C).
    4. Markus Arlindo Monteiro & Bennie Grové & Nicolette Matthews, 2022. "Developing a Moving Average Crossover Strategy as an Alternative Hedging Strategy for the South Africa Maize Market," Agriculture, MDPI, vol. 12(8), pages 1-14, August.
    5. Pan, Zhiyuan & Xiao, Dongli & Dong, Qingma & Liu, Li, 2022. "Structural breaks, macroeconomic fundamentals and cross hedge ratio," Finance Research Letters, Elsevier, vol. 47(PA).
    6. Xu Gong & Yujing Jin & Chuanwang Sun, 2022. "Time‐varying pure contagion effect between energy and nonenergy commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1960-1986, October.
    7. Long Hai Vo & Duc Hong Vo, 2020. "Modelling Australian Dollar Volatility at Multiple Horizons with High-Frequency Data," Risks, MDPI, vol. 8(3), pages 1-16, August.
    8. Ning Zhang & Yujing Gong & Xiaohan Xue, 2023. "Less disagreement, better forecasts: Adjusted risk measures in the energy futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(10), pages 1332-1372, October.
    9. Yu‐Sheng Lai, 2021. "Generalized autoregressive score model with high‐frequency data for optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 2023-2045, December.
    10. Lee, Hsiang-Tai & Lee, Chien-Chiang, 2022. "A regime-switching real-time copula GARCH model for optimal futures hedging," International Review of Financial Analysis, Elsevier, vol. 84(C).
    11. Pablo Urtubia & Alfonso Novales & Andrés Mora-Valencia, 2021. "Cross-Hedging Portfolios in Emerging Stock Markets: Evidence for the LATIBEX Index," Mathematics, MDPI, vol. 9(21), pages 1-19, October.
    12. You‐How Go & Jia‐Jun Teo & Kam Fong Chan, 2023. "The effectiveness of crude oil futures hedging during infectious disease outbreaks in the 21st century," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(11), pages 1559-1575, November.
    13. Yingying Xu & Donald Lien, 2022. "Forecasting volatilities of oil and gas assets: A comparison of GAS, GARCH, and EGARCH models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 259-278, March.
    14. Xu, Yingying, 2021. "Risk spillover from energy market uncertainties to the Chinese carbon market," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    15. Pan, Zhiyuan & Fu, Ziqian & Wang, Yudong & Dong, Qingma, 2024. "Exploiting the sentiments: A simple approach for improving cross hedging effectiveness," Energy Economics, Elsevier, vol. 134(C).
    16. Hsiang‐Tai Lee, 2024. "Riemannian‐geometric regime‐switching covariance hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(6), pages 1003-1054, June.
    17. Wang Haoyu & Junpeng Di & Qing Han, 2023. "Adaptive hedging horizon and hedging performance estimation," Papers 2302.00251, arXiv.org.
    18. 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.

    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. Chen, Rongda & Xu, Jianjun, 2019. "Forecasting volatility and correlation between oil and gold prices using a novel multivariate GAS model," Energy Economics, Elsevier, vol. 78(C), pages 379-391.
    2. Čech, František & Zítek, Michal, 2022. "Marine fuel hedging under the sulfur cap regulations," Energy Economics, Elsevier, vol. 113(C).
    3. Sharma, Udayan & Karmakar, Madhusudan, 2023. "Measuring minimum variance hedging effectiveness: Traditional vs. sophisticated models," International Review of Financial Analysis, Elsevier, vol. 87(C).
    4. Corbet, Shaen & Hou, Yang (Greg) & Hu, Yang & Oxley, Les, 2022. "The influence of the COVID-19 pandemic on the hedging functionality of Chinese financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
    5. Yu‐Sheng Lai, 2018. "Estimation of the optimal futures hedge ratio for equity index portfolios using a realized beta generalized autoregressive conditional heteroskedasticity model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1370-1390, November.
    6. Yu‐Sheng Lai, 2021. "Generalized autoregressive score model with high‐frequency data for optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 2023-2045, December.
    7. 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.
    8. Yu-Sheng Lai, 2018. "Dynamic hedging with futures: a copula-based GARCH model with high-frequency data," Review of Derivatives Research, Springer, vol. 21(3), pages 307-329, October.
    9. David Happersberger & Harald Lohre & Ingmar Nolte, 2020. "Estimating portfolio risk for tail risk protection strategies," European Financial Management, European Financial Management Association, vol. 26(4), pages 1107-1146, September.
    10. 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.
    11. Andrea BUCCI, 2017. "Forecasting Realized Volatility A Review," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 8(2), pages 94-138.
    12. Xu, Yingying & Lien, Donald, 2020. "Dynamic exchange rate dependences: The effect of the U.S.-China trade war," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 68(C).
    13. Yu‐Sheng Lai, 2022. "Use of high‐frequency data to evaluate the performance of dynamic hedging strategies," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(1), pages 104-124, January.
    14. Olson, Eric & Vivian, Andrew & Wohar, Mark E., 2019. "What is a better cross-hedge for energy: Equities or other commodities?," Global Finance Journal, Elsevier, vol. 42(C).
    15. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2017. "Can energy commodity futures add to the value of carbon assets?," Economic Modelling, Elsevier, vol. 62(C), pages 194-206.
    16. Yang (Greg) Hou & Mark Holmes, 2020. "Do higher order moments of return distribution provide better decisions in minimum-variance hedging? Evidence from US stock index futures," Australian Journal of Management, Australian School of Business, vol. 45(2), pages 240-265, May.
    17. Chang, Chia-Lin & González-Serrano, Lydia & Jimenez-Martin, Juan-Angel, 2013. "Currency hedging strategies using dynamic multivariate GARCH," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 164-182.
    18. Lucas, André & Zhang, Xin, 2016. "Score-driven exponentially weighted moving averages and Value-at-Risk forecasting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 293-302.
    19. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
    20. Vincenzo Candila & Giampiero M. Gallo & Lea Petrella, 2020. "Mixed--frequency quantile regressions to forecast Value--at--Risk and Expected Shortfall," Papers 2011.00552, arXiv.org, revised Mar 2023.

    More about this item

    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:wly:jfutmk:v:40:y:2020:i:7:p:1090-1108. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0270-7314/ .

    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.