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Conditional risk measures in a bipartite market structure

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  • Oliver Kley
  • Claudia Klüppelberg
  • Gesine Reinert

Abstract

In this paper, we study the effect of network structure between agents and objects on measures for systemic risk. We model the influence of sharing large exogeneous losses to the financial or (re)insurance market by a bipartite graph. Using Pareto-tailed losses and multivariate regular variation, we obtain asymptotic results for conditional risk measures based on the Value-at-Risk and the Conditional Tail Expectation. These results allow us to assess the influence of an individual institution on the systemic or market risk and vice versa through a collection of conditional risk measures. For large markets, Poisson approximations of the relevant constants are provided. Differences of the conditional risk measures for an underlying homogeneous and inhomogeneous random graph are illustrated by simulations.

Suggested Citation

  • Oliver Kley & Claudia Klüppelberg & Gesine Reinert, 2018. "Conditional risk measures in a bipartite market structure," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2018(4), pages 328-355, April.
    • Handle: RePEc:taf:sactxx:v:2018:y:2018:i:4:p:328-355
    DOI: 10.1080/03461238.2017.1350203
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    Cited by:

    1. Wang, Bingjie & Li, Jinzhu, 2024. "Asymptotic results on tail moment for light-tailed risks," Insurance: Mathematics and Economics, Elsevier, vol. 114(C), pages 43-55.
    2. Bikramjit Das & Vicky Fasen-Hartmann, 2023. "Measuring risk contagion in financial networks with CoVaR," Papers 2309.15511, arXiv.org, revised Jun 2024.

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