The price of complexity in financial networks

Abstract

Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.financial contagion | financial networks | complexity | default probability | systemic risk

Reconstruction methods for networks: The case of economic and financial systems

“…Although the knowledge of the whole network structure could help regulators to take immediate countermeasures to stop the propagation of financial distress, this information is seldom available (the knowledge of the whole network of investments would pose immense problems of privacy), thus hindering the possibility of providing a realistic estimate of the extent of the contagion. As confirmed by the analysis of the various papers reported in this review, the incompleteness of network instances seems to be unavoidable [60,61]: since addressing the problem of estimating the resilience of financial networks cannot be addressed without knowing the structural details of national and cross-countries interbank networks, information theory seems indeed to provide the right framework to tackle this kind of problems.Finance is not the only domain affected by limitedness of information about nodes interdependencies: biological and ecological systems also exist (e.g., cell metabolic networks and ecological webs) whose interaction network is often only partially accessible due either to experimental limitations or observational constraints 2 .Approaching network reconstruction. In order to deal with the problem of missing information, many different approaches have been attempted so far.…”

“…This issue received a lot of attention especially after the global financial crisis of 2007/2008. Since then, it was realized that the complex pattern of interconnections between financial institutions makes the system as a whole inherently fragile: those connections constitute the channels through which financial distress can spread which, eventually, lead to amplification effects like default cascades [60,138,139,140,141,142,143,144].…”

The interconnected wealth of nations: Shock propagation on global trade-investment multiplex networks

“…Within the framework of the spreading of economic crisis, it has been proved that networks effects can be substantial [15,16]. Conversely, network tools have been increasingly employed to estimate systemic risk among financial institutions [17][18][19][20][21][22], e.g. by adopting threshold models to assess financial contagion over networks of banks [23][24][25].…”

Explicit size distributions of failure cascades redefine systemic risk on finite networks

“…The ED mechanism has not only attracted theoretical interest [24][25][26][27][28] , it is also used to explain opinion formation 29 and financial contagion 2,30,31 , where random thresholds correspond to fluctuating exposures between banks and changing capital buffers. The randomness can also be interpreted as model uncertainty in such complex systems 32 .…”