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A Bivariate Markov Regime Switching GARCH Approach to Estimate Time Varying Minimum Variance Hedge Ratios


  • Hsiang-Tai Lee

    (Washington State University)

  • Jonathan Yoder

    (Washington State University)


This paper develops a new bivariate Markov regime switching BEKK-GARCH (RS-BEKK-GARCH) model. The model is a state-dependent bivariate BEKK- GARCH model, and an extension of Gray’s univariate generalized regime- switching (GRS) model to the bivariate case. To solve the path- dependency problem inherent in the bivariate regime switching BEKK-GARCH model, we propose a recombining method for the covariance term in the conditional variance-covariance matrix. The model is applied to estimate time-varying minimum variance hedge ratios for corn and nickel spot and futures prices. Out-of-sample point estimates of hedging portfolio variance show that compared to the state-independent BEKK-GARCH model, the RS-BEKK-GARCH model improves out-of-sample hedging effectiveness for both corn and nickel data. We perform White’s (2000) data-snooping reality check to test for predictive superiority of RS-BEKK-GARCH over the benchmark model, and find that the difference in variance reduction between BEKK-GARCH and RS-BEKK-GARCH is not statistically significant for either data set at conventional confidence levels.

Suggested Citation

  • Hsiang-Tai Lee & Jonathan Yoder, 2005. "A Bivariate Markov Regime Switching GARCH Approach to Estimate Time Varying Minimum Variance Hedge Ratios," Econometrics 0506009, EconWPA.
  • Handle: RePEc:wpa:wuwpem:0506009
    Note: Type of Document - pdf; pages: 33

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    References listed on IDEAS

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    Cited by:

    1. Beatriz Martínez Martínez & Hipolit Torro Enguix, 2017. "Hedging spark spread risk with futures," Working Papers. Serie EC 2017-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    2. 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.
    3. Martínez, Beatriz & Torró, Hipòlit, 2015. "European natural gas seasonal effects on futures hedging," Energy Economics, Elsevier, vol. 50(C), pages 154-168.
    4. Wagner Oliveira Monteiro & Rodrigo De Losso da Silveira Bueno, 2011. "Dynamic Hedging inMarkov Regimes Switching," Anais do XXXVII Encontro Nacional de Economia [Proceedings of the 37th Brazilian Economics Meeting] 136, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].
    5. Aboura Sofiane & Chevallier Julien & Jammazi Rania & Tiwari Aviral Kumar, 2016. "The place of gold in the cross-market dependencies," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(5), pages 567-586, December.
    6. Jammazi, Rania, 2012. "Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach," Energy, Elsevier, vol. 37(1), pages 430-454.
    7. Dark, Jonathan, 2015. "Futures hedging with Markov switching vector error correction FIEGARCH and FIAPARCH," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 269-285.
    8. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    9. Zhu, Hui-Ming & Li, Rong & Li, Sufang, 2014. "Modelling dynamic dependence between crude oil prices and Asia-Pacific stock market returns," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 208-223.
    10. 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.
    11. 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.
    12. 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.
    13. Marta Giampietro & Massimo Guidolin & Manuela Pedio, 2017. "Estimating Stochastic Discount Factor Models with Hidden Regimes: Applications to Commodity Pricing," Working Papers 614, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    14. Marta Giampietro & Massimo Guidolin & Manuela Pedio, 2015. "Can No-Arbitrage SDF Models with Regime Shifts Explain the Correlations Between Commodity, Stock, and Bond Returns?," BAFFI CAREFIN Working Papers 1619, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    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. Rozaimah Zainudin & Roselee Shah Shaharudin, 2011. "Multi Mean Garch Approach to Evaluating Hedging Performance in the Crude Palm Oil Futures Market," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 7(1), pages 111-130.
    17. Akram Hasanov & Ahmad Baharumshah, 2014. "Exchange-Rate Risk and Exports," Problems of Economic Transition, Taylor & Francis Journals, vol. 57(1), pages 80-101.
    18. 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.
    19. Monica Billio & Massimiliano Caporin & Lorenzo Frattarolo & Loriana Pelizzon, 2016. "Networks in risk spillovers: a multivariate GARCH perspective," Working Papers 2016:03, Department of Economics, University of Venice "Ca' Foscari".
    20. repec:eee:enepol:v:113:y:2018:i:c:p:731-746 is not listed on IDEAS
    21. 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.
    22. Seth J. Kopchak, 2016. "The regime-switching risk premium in the gold futures market," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 40(3), pages 472-491, July.
    23. Hongfeng Peng & Xiaoyu Tan & Yi Chen, 2016. "Discretion of Dynamic Position Adjustment in Hedging Strategy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 86-101, June.
    24. Lee, Hsiang-Tai, 2010. "Regime switching correlation hedging," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2728-2741, November.
    25. Pujiang Chen & Zirong Zhuo & Jixiang Liu, 2016. "Estimation and Comparative of Dynamic Optimal Hedge Ratios of China Gold Futures Based on ECM-GARCH," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(3), pages 236-243, March.

    More about this item


    bivariate GARCH; require switching; hedging;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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