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

Hsiang-Tai Lee and Jonathan Yoder ()
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Hsiang-Tai Lee: Washington State University

Econometrics from University Library of Munich, Germany

Abstract: 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.

Keywords: bivariate GARCH; require switching; hedging (search for similar items in EconPapers)
JEL-codes: C53 D81 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2005-06-28
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-fin
Note: Type of Document - pdf; pages: 33
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Citations: View citations in EconPapers (3)

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Related works:
Journal Article: A bivariate Markov regime switching GARCH approach to estimate time varying minimum variance hedge ratios (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0506009

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