Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks

  • Tomohiro Ando
    Melbourne Business School, University of Melbourne, Carlton, Victoria 3053, Australia
  • Matthew Greenwood-Nimmo
    Department of Economics, University of Melbourne, Carlton, Victoria 3053, Australia
  • Yongcheol Shin
    Department of Economics and Related Studies, University of York, Heslington, York YO10 5DD, United Kingdom

書誌事項

公開日
2022-04
DOI
  • 10.1287/mnsc.2021.3984
公開者
Institute for Operations Research and the Management Sciences (INFORMS)

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説明

<jats:p> We develop a new technique to estimate vector autoregressions with a common factor error structure by quantile regression. We apply our technique to study credit risk spillovers among a group of 17 sovereigns and their respective financial sectors between January 2006 and December 2017. We show that idiosyncratic credit risk shocks propagate much more strongly in both tails than at the conditional mean or median. Furthermore, we develop a measure of the relative spillover intensity in the right and left tails of the conditional distribution that provides a timely aggregate measure of systemic financial fragility and that can be used for risk management and monitoring purposes. </jats:p><jats:p> This paper was accepted by Gustavo Manso, finance. </jats:p>

収録刊行物

  • Management Science

    Management Science 68 (4), 2401-2431, 2022-04

    Institute for Operations Research and the Management Sciences (INFORMS)

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