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Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks

Author

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  • Anthony D. Hall

    (National Centre for Econometric Research (NCER), Queensland University of Technology, Brisbane, QLD 4000, Australia)

  • Annastiina Silvennoinen

    (National Centre for Econometric Research (NCER), Queensland University of Technology, Brisbane, QLD 4000, Australia)

  • Timo Teräsvirta

    (Aarhus BSS, Aarhus University, DK-8210 Aarhus V, Denmark
    Center for Applied Statistics and Economics (C.A.S.E.), Humboldt-Universität zu Berlin, DE-10178 Berlin, Germany)

Abstract

This paper proposes a methodology for building Multivariate Time-Varying STCC–GARCH models. The novel contributions in this area are the specification tests related to the correlation component, the extension of the general model to allow for additional correlation regimes, and a detailed exposition of the systematic, improved modelling cycle required for such nonlinear models. There is an R-package that includes the steps in the modelling cycle. Simulations demonstrate the robustness of the recommended model building approach. The modelling cycle is illustrated using daily return series for Australia’s four largest banks.

Suggested Citation

  • Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2023. "Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks," Econometrics, MDPI, vol. 11(1), pages 1-37, February.
    • Handle: RePEc:gam:jecnmx:v:11:y:2023:i:1:p:5-:d:1059591
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    References listed on IDEAS

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