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

Author

Listed:
  • Paul Catani

    (Hanken School of Economics)

  • Timo Teräsvirta

    (Aarhus University and CREATES)

  • Meiqun Yin

    (Beijing International Studies 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

Suggested Citation

  • Paul Catani & Timo Teräsvirta & Meiqun Yin, 2014. "A Lagrange Multiplier Test for Testing the Adequacy of the Constant Conditional Correlation GARCH Model," CREATES Research Papers 2014-03, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2014-03
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    Cited by:

    1. Lee, Taewook, 2016. "Wild bootstrap Ljung–Box test for cross correlations of multivariate time series," Economics Letters, Elsevier, vol. 147(C), pages 59-62.
    2. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2019. "Tests for conditional heteroscedasticity with functional data and goodness-of-fit tests for FGARCH models," MPRA Paper 93048, University Library of Munich, Germany.
    3. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A Parsimonious Test of Constancy of a Positive Definite Correlation Matrix in a Multivariate Time-Varying GARCH Model," Econometrics, MDPI, vol. 10(3), pages 1-41, August.
    4. Cristina Amado & Annastiina Silvennoinen & Timo Ter¨asvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," NIPE Working Papers 07/2018, NIPE - Universidade do Minho.
    5. Gregory Rice & Tony Wirjanto & Yuqian Zhao, 2020. "Tests for conditional heteroscedasticity of functional data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(6), pages 733-758, November.
    6. Keqiang Dong & Liao Guo, 2021. "Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis," Sustainability, MDPI, vol. 13(21), pages 1-16, October.

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    More about this item

    Keywords

    constant conditional correlation; LM test; misspeci?cation testing; modelling volatility; multivariate GARCH;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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