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 ()
Additional contact information
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

No 15-01, Working Papers from Office of Financial Research, US Department of the Treasury

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.

Keywords: Process Systems Engineering; Systemic Risk; Financial Networks (search for similar items in EconPapers)
Pages: 29 pages
Date: 2015-02-11
New Economics Papers: this item is included in nep-ban and nep-net
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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