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A New Range-Based Regime-Switching Dynamic Conditional Correlation Model for Minimum-Variance Hedging

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DOI: 10.4236/jmf.2014.43018    3,737 Downloads   5,416 Views   Citations


This study proposes a new range-based Markov-switching dynamic conditional correlation (MSDCC) model for estimating the minimum-variance hedging ratio and comparing its hedging performance with that of alternative conventional hedging models, including the naive, OLS regression, return-based DCC, range-based DCC and return-based MS-DCC models. The empirical results show that the embedded Markov-switching adjustment in the range-based DCC model can clearly delineate uncertain exogenous shocks and make the estimated correlation process more in line with reality. Overall, in-sample and out-of sample tests indicate that the range-based MS-DCC model outperforms other static and dynamic hedging models.

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The authors declare no conflicts of interest.

Cite this paper

Su, Y. and Wu, C. (2014) A New Range-Based Regime-Switching Dynamic Conditional Correlation Model for Minimum-Variance Hedging. Journal of Mathematical Finance, 4, 207-219. doi: 10.4236/jmf.2014.43018.


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