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

Richard Bookstaber, Paul Glasserman, Garud Iyengar, Yu Luo, Venkat Venkatasubramanian and Zhizun Zhang
The Journal of Investing Summer 2015, 24 (2) 147-162; DOI: https://doi.org/10.3905/joi.2015.24.2.147
Richard Bookstaber
is a research principal at the Office of Financial Research, U.S. Department of the Treasury, in Washington, DC.
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  • For correspondence: richard.bookstaber@treasury.gov
Paul Glasserman
is Jack R. Anderson Professor of Business at Columbia Business School, Columbia University, in New York, NY.
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  • For correspondence: pg20@columbia.edu
Garud Iyengar
is Chair of the Department of Industrial Engineering and Operations Research at Columbia University in New York, NY.
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  • For correspondence: garud@ieor.columbia.edu
Yu Luo
is a PhD candidate in the Department of Chemical Engineering at Columbia University in New York, NY.
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  • For correspondence: yl2750@columbia.edu
Venkat Venkatasubramanian
is Samuel Ruben-Peter G. Viele Professor of Engineering at Columbia University in New York, NY.
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  • For correspondence: venkat@columbia.edu
Zhizun Zhang
is a PhD candidate in the Department of Chemical Engineering at Columbia University in New York, NY.
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  • For correspondence: zz2216@columbia.edu
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Abstract

The recent financial crisis and the ensuing sovereign debt crisis once again highlighted that understanding the potential instabilities in the financial system is of great societal value. Financial instability typically 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 that is 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 an appropriate 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 the edges in a network in terms of the direction of flows and relationship between the variables associated with the nodes at the two ends of a directed edge, thereby providing a framework for systematically analyzing the potential hazards and instabilities in the system. This article also discusses how the SDG framework can facilitate the automation of the identification and monitoring of potential vulnerabilities. These are illustrated with an example of a bank-dealer case study.

TOPICS: Financial crises and financial market history, quantitative methods

  • © 2015 Pageant Media Ltd
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The Journal of Investing: 24 (2)
The Journal of Investing
Vol. 24, Issue 2
Summer 2015
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Process Systems Engineering as a Modeling Paradigm for Analyzing Systemic Risk in Financial Networks
Richard Bookstaber, Paul Glasserman, Garud Iyengar, Yu Luo, Venkat Venkatasubramanian, Zhizun Zhang
The Journal of Investing May 2015, 24 (2) 147-162; DOI: 10.3905/joi.2015.24.2.147

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Process Systems Engineering as a Modeling Paradigm for Analyzing Systemic Risk in Financial Networks
Richard Bookstaber, Paul Glasserman, Garud Iyengar, Yu Luo, Venkat Venkatasubramanian, Zhizun Zhang
The Journal of Investing May 2015, 24 (2) 147-162; DOI: 10.3905/joi.2015.24.2.147
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  • Article
    • Abstract
    • FINANCIAL NETWORK AS A PROCESS PLANT: A SYSTEMS ENGINEERING FRAMEWORK
    • SDG MODELING FRAMEWORK FOR FINANCIAL NETWORKS
    • BANK/DEALER CASE STUDY
    • FIRE SALES
    • FUNDING RUNS
    • SEMIQUANTITATIVE ANALYSIS
    • CONCLUSION
    • ENDNOTES
    • REFERENCES
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