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Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS

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  • Marco Valerio Geraci
  • Jean-Yves Gnabo

Abstract

In this paper we propose a time-varying parameter framework to estimate the dynamic network of financial spillovers. In a series of simulation exercises, we show that our framework performs better than the classical approach based on Granger causality testing over rolling windows. We apply it to all financial stocks listed in the S&P 500 and uncover a gradual decrease in interconnectedness after the crisis, which is not observable using the rolling window approach. We show that this is because the rolling window results are highly sensitive to crisis observations.

Suggested Citation

  • Marco Valerio Geraci & Jean-Yves Gnabo, 2015. "Measuring Interconnectedness between Financial Institutions with Bayesian Time-Varying VARS," Working Papers ECARES ECARES 2015-51, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:eca:wpaper:2013/249920
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    Cited by:

    1. Rodolfo C. Moura & Márcio P. Laurini, 2021. "Spillovers and jumps in global markets: A comparative analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5997-6013, October.

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    More about this item

    Keywords

    financial interconnectedness; time-varying parameter; granger causality;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • 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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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