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ABSTRACT
A Lagrange multiplier test for testing the parametric structure of a constant conditional correlation-generalized autoregressive conditional heteroskedasticity (CCC-GARCH) model is proposed. The test is based on decomposing the CCC-GARCH model multiplicatively into two components, one of which represents the null model, whereas the other one describes the misspecification. A simulation study shows that the test has good finite sample properties. We compare the test with other tests for misspecification of multivariate GARCH models. The test has high power against alternatives where the misspecification is in the GARCH parameters and is superior to other tests. The test is not greatly affected by misspecification in the conditional correlations and is therefore well suited for considering misspecification of GARCH equations.
Acknowledgment
The first author acknowledges financial support from The Society of Swedish Literature in Finland. The research of the second author has been supported by CREATES - Center for Research in Econometric Analysis of Time Series (DNRF78), funded by the Danish National Research Foundation. The third author has received support from the China National Social Science Fund, Project No. 13BGL042. Material from this paper has been presented at the seventh International Conference on Computational and Financial Econometrics (CFE 2013), 14–16 December 2013, London. We wish to thank Christian Conrad and James Davidson for useful remarks. Special thanks go to the referee for careful reading of the paper. Errors and shortcomings in this work remain our own responsibility.