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Strategic Payments in Financial Networks

Authors Nils Bertschinger , Martin Hoefer , Daniel Schmand



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Author Details

Nils Bertschinger
  • Systemic Risk Group, Frankfurt Institute of Advanced Studies, Germany
  • Institute for Computer Science, Goethe University Frankfurt, Germany
Martin Hoefer
  • Institute for Computer Science, Goethe University Frankfurt, Germany
Daniel Schmand
  • Institute for Computer Science, Goethe University Frankfurt, Germany

Acknowledgements

We thank Pascal Lenzner and Steffen Schuldenzucker for valuable discussions and feedback on the results of this paper. NB thanks Dr. h. c. Maucher for funding his position.

Cite AsGet BibTex

Nils Bertschinger, Martin Hoefer, and Daniel Schmand. Strategic Payments in Financial Networks. In 11th Innovations in Theoretical Computer Science Conference (ITCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 151, pp. 46:1-46:16, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.ITCS.2020.46

Abstract

In their seminal work on systemic risk in financial markets, Eisenberg and Noe [Larry Eisenberg and Thomas Noe, 2001] proposed and studied a model with n firms embedded into a network of debt relations. We analyze this model from a game-theoretic point of view. Every firm is a rational agent in a directed graph that has an incentive to allocate payments in order to clear as much of its debt as possible. Each edge is weighted and describes a liability between the firms. We consider several variants of the game that differ in the permissible payment strategies. We study the existence and computational complexity of pure Nash and strong equilibria, and we provide bounds on the (strong) prices of anarchy and stability for a natural notion of social welfare. Our results highlight the power of financial regulation - if payments of insolvent firms can be centrally assigned, a socially optimal strong equilibrium can be found in polynomial time. In contrast, worst-case strong equilibria can be a factor of Ω(n) away from optimal, and, in general, computing a best response is an NP-hard problem. For less permissible sets of strategies, we show that pure equilibria might not exist, and deciding their existence as well as computing them if they exist constitute NP-hard problems.

Subject Classification

ACM Subject Classification
  • Theory of computation → Algorithmic game theory and mechanism design
Keywords
  • Nash Equilibrium
  • Financial Network
  • Systemic Risk
  • Price of Anarchy
  • Equilibrium Computation

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