Sensitivity and computational complexity in financial networks

Brett Hemenway () and Sanjeev Khanna ()
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Brett Hemenway: Department of Computer Science, University of Pennsylvania, Postal: Philadelphia, PA, USA
Sanjeev Khanna: Department of Computer Science, University of Pennsylvania, Postal: Philadelphia, PA, USA

Algorithmic Finance, 2016, vol. 5, issue 3-4, 95-110

Abstract: Determining the causes of instability and contagion in financial networks is necessary to inform policy and avoid future financial collapse. In the American Economic Review, Elliott, Golub and Jackson proposed a simple model for capturing the dynamics of complex financial networks. In Elliott, Golub and Jackson’s model, the institutions in the network are connected by linear dependencies (cross-holdings) and if any institution’s value drops below a critical threshold, its value suffers an additional failure cost. This work shows that even in this simple model there are fundamental barriers to understanding the risks that are inherent in a network. First, if institutions are not required to maintain a minimum amount of self-holdings, any change in investments by a single institution can have an arbitrarily magnified influence on the net worth of the institutions in the system. This implies that if institutions have small self-holdings, then estimating the market value of an institution requires almost perfect information about every cross-holding in the system . Second, even if a regulator has complete information about all cross-holdings in the system, it may be computationally intractable to estimate the number of failures that could be caused by a small shock to the system.

Keywords: Financial contagion; computational complexity; network analysis; network stability; sensitivity (search for similar items in EconPapers)
JEL-codes: C00 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (4)

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