Reconstruction of financial network for robust estimation of systemic risk
AbstractIn this paper we estimate the propagation of liquidity shocks through interbank markets when the information about the underlying credit network is incomplete. We show that techniques such as Maximum Entropy currently used to reconstruct credit networks severely underestimate the risk of contagion by assuming a trivial (fully connected) topology, a type of network structure which can be very different from the one empirically observed. We propose an efficient message-passing algorithm to explore the space of possible network structures, and show that a correct estimation of the network degree of connectedness leads to more reliable estimations for systemic risk. Such algorithm is also able to produce maximally fragile structures, providing a practical upper bound for the risk of contagion when the actual network structure is unknown. We test our algorithm on ensembles of synthetic data encoding some features of real financial networks (sparsity and heterogeneity), finding that more accurate estimations of risk can be achieved. Finally we find that this algorithm can be used to control the amount of information regulators need to require from banks in order to sufficiently constrain the reconstruction of financial networks.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1109.6210.
Date of creation: Sep 2011
Date of revision: Feb 2012
Publication status: Published in J. Stat. Mech. (2012) P03011
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-10-09 (All new papers)
- NEP-BAN-2011-10-09 (Banking)
- NEP-CBA-2011-10-09 (Central Banking)
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- Furfine, Craig H, 2003. " Interbank Exposures: Quantifying the Risk of Contagion," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(1), pages 111-28, February.
- Hans Degryse & Grégory Nguyen, 2007.
"Interbank Exposures: An Empirical Examination of Contagion Risk in the Belgian Banking System,"
International Journal of Central Banking,
International Journal of Central Banking, vol. 3(2), pages 123-171, June.
- Degryse, H.A. & Nguyen, G., 2006. "Interbank Exposures: An Empirical Examination of Contagion Risk in the Belgian Banking System," Discussion Paper 2006-016, Tilburg University, Tilburg Law and Economic Center.
- Paolo Emilio Mistrulli, 2007.
"Assessing financial contagion in the interbank market: Maximum entropy versus observed interbank lending patterns,"
Temi di discussione (Economic working papers)
641, Bank of Italy, Economic Research and International Relations Area.
- Mistrulli, Paolo Emilio, 2011. "Assessing financial contagion in the interbank market: Maximum entropy versus observed interbank lending patterns," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1114-1127, May.
- Leonardo Bargigli, 2013. "Statistical Equilibrium Models for Sparse Economic Networks," Working Papers - Economics wp2013_25.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
- Bargigli, Leonardo & Gallegati, Mauro & Riccetti, Luca & Russo, Alberto, 2014. "Network analysis and calibration of the “leveraged network-based financial accelerator”," Journal of Economic Behavior & Organization, Elsevier, vol. 99(C), pages 109-125.
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