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Process Systems Engineering as a Modeling Paradigm for Analyzing Systemic Risk in Financial Networks

Author

Listed:
  • Richard Bookstaber

    (Office of Financial Research)

  • Paul Glasserman

    (Office of Financial Research)

  • Garud Iyengar

    (Columbia University)

  • Yu Luo

    (Columbia University)

  • Venkat Venkatasubramanian

    (Columbia University)

  • Zhizun Zhang

    (Columbia University)

Abstract

Financial instability often results from positive feedback loops intrinsic to the operation of the financial system. The challenging task of identifying, modeling, and analyzing the causes and effects of such feedback loops requires a proper systems engineering perspective lacking in the remedies proposed in recent literature. We propose that signed directed graphs (SDG), a modeling methodology extensively used in process systems engineering, is a useful framework to address this challenge. The SDG framework is able to represent and reveal information missed by more traditional network models of financial system. This framework adds crucial information to a network model about the direction of influence and control between nodes, providing a tool for analyzing the potential hazards and instabilities in the system. This paper also discusses how the SDG framework can facilitate the automation of the identification and monitoring of potential vulnerabilities, illustrated with an example of a bank/dealer case study.

Suggested Citation

  • Richard Bookstaber & Paul Glasserman & Garud Iyengar & Yu Luo & Venkat Venkatasubramanian & Zhizun Zhang, 2015. "Process Systems Engineering as a Modeling Paradigm for Analyzing Systemic Risk in Financial Networks," Working Papers 15-01, Office of Financial Research, US Department of the Treasury.
    • Handle: RePEc:ofr:wpaper:15-01
    as

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    File URL: https://financialresearch.gov/working-papers/files/OFRwp-2015-02-11-Process-Systems-Engineering-as-a-Modeling-Paradigm.pdf
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    References listed on IDEAS

    as
    1. Gai, Prasanna & Kapadia, Sujit, 2010. "Contagion in financial networks," Bank of England working papers 383, Bank of England.
    2. Tobias Adrian & Hyun Song Shin, 2014. "Procyclical Leverage and Value-at-Risk," The Review of Financial Studies, Society for Financial Studies, vol. 27(2), pages 373-403.
    3. Douglas W. Diamond & Philip H. Dybvig, 2000. "Bank runs, deposit insurance, and liquidity," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 24(Win), pages 14-23.
    4. Andrei Shleifer & Robert Vishny, 2011. "Fire Sales in Finance and Macroeconomics," Journal of Economic Perspectives, American Economic Association, vol. 25(1), pages 29-48, Winter.
    5. John Geanakoplos & Ana Fostel, 2008. "Leverage Cycles and the Anxious Economy," American Economic Review, American Economic Association, vol. 98(4), pages 1211-1244, September.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Dror Kenett & Shlomo Havlin, 2015. "Network science: a useful tool in economics and finance," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 14(2), pages 155-167, November.
    2. Christian Hugo Hoffmann & Charles Djordjevic, 2020. "Complexity, Power Laws and a Humean Argument in Risk Management: The Fundamental Inadequacy of Probability Theory as a Foundation for Modeling Complex Risk in Banking," Homo Oeconomicus: Journal of Behavioral and Institutional Economics, Springer, vol. 37(3), pages 155-182, December.

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    More about this item

    Keywords

    Process Systems Engineering; Systemic Risk; Financial Networks;
    All these keywords.

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