A Parsimonious Test of Constancy of a Positive Definite Correlation Matrix in a Multivariate Time-Varying GARCH Model

Jian Kang, Johan Stax Jakobsen, Annastiina Silvennoinen, Timo Teräsvirta and Glen Wade
Additional contact information
Jian Kang: School of Finance, Dongbei University of Finance and Economics, Dalian 116025, China
Johan Stax Jakobsen: Department of Finance, Copenhagen Business School, DK-2000 Frederiksberg, Denmark
Glen Wade: National Centre for Econometric Research (NCER), Queensland University of Technology, Brisbane, QLD 4000, Australia

Econometrics, 2022, vol. 10, issue 3, 1-41

Abstract: We construct a parsimonious test of constancy of the correlation matrix in the multivariate conditional correlation GARCH model, where the GARCH equations are time-varying. The alternative to constancy is that the correlations change deterministically as a function of time. The alternative is a covariance matrix, not a correlation matrix, so the test may be viewed as a general test of stability of a constant correlation matrix. The size of the test in finite samples is studied by simulation. An empirical example involving daily returns of 26 stocks included in the Dow Jones stock index is given.

Keywords: deterministically varying correlation; multiplicative time-varying GARCH; multivariate GARCH; nonstationary volatility; smooth transition GARCH (search for similar items in EconPapers)
JEL-codes: B23 C C00 C01 C1 C2 C3 C4 C5 C8 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Working Paper: A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model (2022)
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