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Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models

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  • Fengler, Matthias R.
  • Herwartz, Helmut

Abstract

We propose global and disaggregated spillover indices that allow us to assess variance and covariance spillovers, locally in time and conditionally on time-t information. Key to our approach is the vector moving average representation of the half-vectorized `squared' multivariate GARCH process of the popular BEKK model. In an empirical application to a four-dimensional system of broad asset classes (equity, fixed income, foreign exchange and commodities), we illustrate the new spillover indices at various levels of (dis)aggregation. Moreover, we demonstrate that they are informative of the value-at-risk violations of portfolios composed of the considered asset classes.

Suggested Citation

  • Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models," MPRA Paper 72197, University Library of Munich, Germany, revised 10 Jun 2016.
    • Handle: RePEc:pra:mprapa:72197
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    More about this item

    Keywords

    BEKK model; forecast error variance decomposition; multivariate GARCH; spillover index; value-at-risk; variance spillovers;
    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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • F3 - International Economics - - International Finance
    • G1 - Financial Economics - - General Financial Markets

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