A Lagrange Multiplier Test for Testing the Adequacy of the Constant Conditional Correlation GARCH Model

Paul Catani, Timo Teräsvirta and Meiqun Yin ()
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Meiqun Yin: Beijing International Studies University, Postal: 100024, Beijing, China

CREATES Research Papers from Department of Economics and Business Economics, Aarhus University

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 misspeci?cation. A simulation study shows that the test has good ?nite sample properties. We compare the test with other tests for misspeci?cation of multivariate GARCH models. The test has high power against alternatives where the misspeci?cation is in the GARCH parameters and is superior to other tests. The test is not greatly affected by misspeci?cation in the conditional correlations and is therefore well suited for considering misspeci?cation of GARCH equations. JEL Codes: C32, C52, C58

Keywords: constant conditional correlation; LM test; misspeci?cation testing; modelling volatility; multivariate GARCH (search for similar items in EconPapers)
Pages: 24
Date: 2014-01-28
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-sog
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