DOUBLE CASCADE MODEL OF FINANCIAL CRISES

T. R. Hurd (), Davide Cellai (), Sergey Melnik () and Quentin H. Shao ()
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T. R. Hurd: Mathematics and Statistics, McMaster University, 1280 Main St. West Hamilton, Ontario, L8S4L8, Canada
Davide Cellai: #x2020;MACSI, Department of Mathematics and Statistics, University of Limerick, Limerick, V94 T9PX, Ireland
Sergey Melnik: #x2020;MACSI, Department of Mathematics and Statistics, University of Limerick, Limerick, V94 T9PX, Ireland
Quentin H. Shao: Mathematics and Statistics, McMaster University, 1280 Main St. West Hamilton, Ontario, L8S4L8, Canada

International Journal of Theoretical and Applied Finance (IJTAF), 2016, vol. 19, issue 05, 1-27

Abstract: The scope of financial systemic risk research encompasses a wide range of interbank channels and effects, including asset correlation shocks, default contagion, illiquidity contagion, and asset fire sales. This paper introduces a financial network model that combines the default and liquidity stress mechanisms into a “double cascade mapping”. The progress and eventual result of the crisis is obtained by iterating this mapping to its fixed point. Unlike simpler models, this model can therefore quantify how illiquidity or default of one bank influences the overall level of liquidity stress and default in the system. Large-network asymptotic cascade mapping formulas are derived that can be used for efficient network computations of the double cascade. Numerical experiments then demonstrate that these asymptotic formulas agree qualitatively with Monte Carlo results for large finite networks, and quantitatively except when the initial system is placed in an exceptional “knife-edge” configuration. The experiments clearly support the main conclusion that when banks respond to liquidity stress by hoarding liquidity, then in the absence of asset fire sales, the level of defaults in a financial network is negatively related to the strength of bank liquidity hoarding and the eventual level of stress in the network.

Keywords: Systemic risk; banking network; contagion; random graph; default; funding liquidity; liquidity hoarding (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (3)

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DOI: 10.1142/S0219024916500412

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