Economics at your fingertips  

Double Cascade Model of Financial Crises

Thomas R. Hurd, Davide Cellai, Sergey Melnik and Quentin Shao

Papers from

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.

New Economics Papers: this item is included in nep-ban, nep-cba and nep-net
Date: 2013-10, Revised 2016-09
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Published in International Journal of Theoretical and Applied Finance 19, 1650041 (2016)

Downloads: (external link) Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Papers from
Series data maintained by arXiv administrators ().

Page updated 2017-09-29
Handle: RePEc:arx:papers:1310.6873