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Hedging systematic risk in the commodity market with a regime‐switching multivariate rotated generalized autoregressive conditional heteroskedasticity model
Author(s) -
Lien Donald,
Lee HsiangTai,
Sheu HerJiun
Publication year - 2018
Publication title -
journal of futures markets
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.88
H-Index - 55
eISSN - 1096-9934
pISSN - 0270-7314
DOI - 10.1002/fut.21959
Subject(s) - futures contract , econometrics , autoregressive conditional heteroskedasticity , autoregressive model , multivariate statistics , economics , markov chain , heteroscedasticity , covariance , commodity , mathematics , financial economics , statistics , volatility (finance) , finance
In this paper, a regime‐switching multivariate rotated BEKK generalized autoregressive conditional heteroskedasticity (GARCH; RS‐MRBEKK) model for optimal futures hedging is proposed. The basic structure of the RS‐MRBEKK model is to rotate returns with spectral decomposition and fit the rotated returns with a Markov regime‐switching BEKK covariance structure that is computationally attractive for modeling higher‐dimensional regime‐switching GARCH dynamics. The empirical results reveal that adding additional commodity index futures to capture the commodity price comovement under regime switching improves hedging performance. The more parsimonious RS‐MRBEKK is statistically no worse than the conventional nonrotated regime‐switching BEKK, illustrating the usefulness of RS‐MRBEKK in higher‐dimensional hedging applications.