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Regime switching fractional cointegration and futures hedging

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  • Hsiang-Tai Lee

Abstract

The article applies a Regime Switching Fractionally Integrated Error Correction Generalized Orthogonal (RSFIEC-GO) Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model for optimal futures hedging. RSFIEC-GO captures both the relationships of fractional cointegration and regime shifts between spot and futures returns. Empirical investigation in agricultural commodity markets reveals that RSFIEC-GO provides superior hedging effectiveness compared to its nested models in terms of variance reductions. Results of Diebold, Mariano and West (DMW) test with adjusted McCracken's critical values also show the statistical superiority of RSFIEC-GO. This illustrates the importance of simultaneously modelling the fractional cointegration and regime shifts for dynamic futures hedging.

Suggested Citation

  • Hsiang-Tai Lee, 2011. "Regime switching fractional cointegration and futures hedging," Applied Financial Economics, Taylor & Francis Journals, vol. 21(15), pages 1145-1157.
    • Handle: RePEc:taf:apfiec:v:21:y:2011:i:15:p:1145-1157
    DOI: 10.1080/09603107.2011.564133
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    Cited by:

    1. 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.
    2. 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.
    3. 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.

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