Abstract
The recent worldwide economic crisis of 2007–09 has focused attention on the need to analyze systemic risk in complex financial networks. We investigate the problem of robustness of such systems in the context of the general theory of dynamical stability in complex networks and, in particular, how the topology of connections influence the risk of the failure of a single institution triggering a cascade of successive collapses propagating through the network. We use data on bilateral liabilities (or exposure) in the derivatives market between 202 financial intermediaries based in USA and Europe in the last quarter of 2009 to empirically investigate the network structure of the over-the-counter (OTC) derivatives market. We observe that the network exhibits both heterogeneity in node properties and the existence of communities. It also has a prominent core-periphery organization and can resist large-scale collapse when subjected to individual bank defaults (however, failure of any bank in the core may result in localized collapse of the innermost core with substantial loss of capital) but is vulnerable to system-wide breakdown as a result of an accompanying liquidity crisis.
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Notes
- 1.
The degree of a node is the number of links it possesses.
- 2.
A financial intermediary is an institution, such as a bank, a credit union or a mortgage loan company, that transfers funds from investors (lenders) to those requiring capital (borrowers). For instance, a bank uses its deposits to provide loans or mortgages thereby mediating transactions between surplus and deficit agents [30].
- 3.
Strength of a node is the sum of weights of all links belonging to it.
- 4.
Bilateral netting, whose primary purpose is to reduce exposure to credit risk, is an arrangement between two parties to exchange only the net difference in their obligations to each other [36].
- 5.
Except for the D L Evans Bank, for which the GNFV exactly equals the GNPV so that the total netted exposure is zero, all the other banks have no bilateral exposure at all with respect to any other bank in the network.
References
Francis J (1850) Mammon and the money market. In: The church of England quarterly review, vol XXVII. W. E. Painter, Strand, London, p 142
Mackay C (1848) Extraordinary popular delusions and the madness of crowds. National Illustrated Library, London
Cassidy J (1998) Annals of finance: pricking the bubble. New Yorker. Aug 17, 1998. http://www.newyorker.com/archive/1998/08/17/
Sinha S, Chatterjee A, Chakraborti A, Chakrabarti BK (2011) Econophysics: an introduction. Wiley-VCH, Weinheim
Chancellor E (2000) Devil take the hindmost: a history of financial speculation. Papermac, London
Ormerod P (2005) Why most things fail: evolution, extinction and economics. Faber and Faber, London
Allen F, Gale D (2000) Financial contagion. J Polit Econ 108:1–33
Schweitzer F, Fagiolo G, Sornette D, Vega-Redondo F, Vespignani A, White DR (2009) Economic networks: the new challenges. Science 325:422–425
Tainter JA (1988) The collapse of complex societies. Cambridge University Press, Cambridge
McCann KS (2000) The diversity-stability debate. Nature 405:228–233
May RM (1973) Stability and complexity in model ecosystems. Princeton University Press, Princeton
Sinha S, Sinha S (2005) Evidence of universality for the May–Wigner stability theorem for random networks with local dynamics. Phys Rev E 71:020902
Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393:440–442
de Solla Price DJ (1976) A general theory of bibliometric and other cumulative advantage processes. J Am Soc Inf Sci 27:292–306
Barabasi A-L, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512
Sinha S (2005) Complexity vs stability in small-world networks. Physica A 346:147–153
Brede M, Sinha S (2005) Assortative mixing by degree makes a network more unstable. http://arxiv.org/abs/cond-mat/0507710
Sinha S (2010) Are large complex economic systems unstable? Sci Cult 76:454–458
May RM, Levin A, Sugihara G (2008) Ecology for bankers. Nature 451:893–895
Haldane AG, May RM (2011) Systemic risk in banking ecosystems. Nature 469:351–355
Soramäki K, Bech Arnold J ML, Glass RJ, Beyeler WE (2007) The topology of interbank payment flows. Physica A 379:317–333
Chatterjee N, Sinha S (2008) Understanding the mind of a worm: hierarchical network structure underlying nervous system function in C. elegans. Prog Brain Res 168:145–153
Ashraf I, Sinha S (2012) Core-periphery organization of graphemes in written sequences: decreasing positional rigidity with increasing core order. In: Gelbukh A (ed) CICLing 2012 part I. Springer lecture notes in computer science, vol 7181. pp 142–153
Boss M, Elsinger H, Summer M, Thurner S (2004) Network topology of the interbank market. Quant Finance 4:677–684
Sui P (2009) Financial contagion in the coreperiphery network. http://www2.warwick.ac.uk/fac/soc/economics/
Inaoka H, Takayasu H, Shimizu T, Ninomiya T, Taniguchi K (2004) Self-similarity of banking network. Physica A 339:621–634
Iori G, De Masi G, Precup OV, Gabbi G, Caldarelli G (2008) A network analysis of the Italian overnight money market. J Econ Dyn Control 32:259–278
Fujiwara Y, Aoyama H, Ikeda Y, Iyetomi H, Souma W (2009) Structure and temporal change of credit network between banks and large firms in Japan. Econ E-J 3:2009-7
De Masi G, Fujiwara Y, Gallegati M, Greenwald B, Stiglitz JE (2010) An analysis of the Japanese credit network. Evol Inst Econ Rev 7:209–232
Furfine CH (2003) Interbank exposure: quantifying the risk of contagion. J Money Credit Bank 35:111–128
Gai P, Kapadia S (2010) Contagion in financial networks. Proc R Soc Lond A 466:2401–2423
Jiang L (2005) Mathematical modeling and methods of option pricing. World Scientific, Singapore
Quarterly OCC Report on bank trading and derivatives fourth quarter 2009. Comptroller of the currency administrator of national banks. Washington DC. http://www.occ.treas.gov/topics/capital-markets/financial-markets/trading/derivatives/dq409.pdf
Markose S, Giansante S, Gatkowski M, Shaghaghi AR (2010) Too interconnected to fail: financial contagion and systemic risk in network model of CDS and other credit enhancement obligations of US banks. University of Essex Discussion Paper 683. http://www.essex.ac.uk/economics/discussion-papers/papers-text/dp683.pdf
Newman MEJ (2010) Networks: an introduction. Oxford University Press, Oxford
Golub GH, Greif C (2006) An Arnoldi-type algorithm for computing page rank. BIT Numer Math 46:759–771
Gleich D (2006) Pagerank package for MATLAB. http://www.mathworks.com/matlabcentral/fileexchange/11613-pagerank
Leicht EA, Newman MEJ (2008) Community structure in directed networks. Phys Rev Lett 100:118703
Markose S, Giansante S, Shaghaghi AR (2010) ‘Too interconnected to fail’ financial network of US CDS market: Topological fragility and systemic risk. J Econ Behav Organ, in press.
Acknowledgements
We would like to thank S Raghavendra for earlier discussions on this topic and F Abergel, N Ganguly and S S Manna for useful comments on the work during presentations at meetings in Kolkata and Bangalore. We are grateful to E Schöll for stimulating discussions and hospitality at TU-Berlin where part of the work was done.
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Sinha, S., Thess, M., Markose, S. (2013). How Unstable Are Complex Financial Systems? Analyzing an Inter-bank Network of Credit Relations. In: Abergel, F., Chakrabarti, B., Chakraborti, A., Ghosh, A. (eds) Econophysics of Systemic Risk and Network Dynamics. New Economic Windows. Springer, Milano. https://doi.org/10.1007/978-88-470-2553-0_5
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