Networks of Banks

The first plenary speaker at the 13th International Conference on E-Commerce (ICEC 2011) in Liverpool last week was Robert, Lord May, Professor of Ecology at Oxford University, former Chief UK Government Scientific Advisor, and former President of the Royal Society.  His talk was part of the special session on Robustness and Reliability of Electronic Marketplaces (RREM 2011), and it was insightful, provocative and amusing.
May began life as an applied mathematician and theoretical physicist (in the Sydney University Physics department of Harry Messel), then applied his models to food webs in ecology, and now finds the same types of network and lattice models useful for understanding inter-dependencies in networks of banks.  Although, as he said in his talk, these models are very simplified, to the point of being toy models, they still have the power to demonstrate unexpected outcomes:  For example, that actions which are individually rational may not be desirable from the perspective of a system containing those individuals.  (It is one of the profound differences between Computer Science and Economics, that such an outcome would be unlikely to be surprising to most computer scientists, yet seems to be so to mainstream Economists, imbued with a belief in metaphysical carpal entities.)
From the final section of Haldane and May (2011):

The analytic model outlined earlier demonstrates that the topology of the financial sector’s balance sheet has fundamental implications for the state and dynamics of systemic risk. From a public policy perspective, two topological features are key.
First, diversity across the financial system. In the run-up to the crisis, and in the pursuit of diversification, banks’ balance sheets and risk management systems became increasingly homogenous. For example, banks became increasingly reliant on wholesale funding on the liabilities side of the balance sheet; in structured credit on the assets side of their balance sheet; and managed the resulting risks using the same value-at-risk models. This desire for diversification was individually rational from a risk perspective. But it came at the expense of lower diversity across the system as whole, thereby increasing systemic risk. Homogeneity bred fragility (N. Beale and colleagues, manuscript in preparation).
In regulating the financial system, little effort has as yet been put into assessing the system-wide characteristics of the network, such as the diversity of its aggregate balance sheet and risk management models. Even less effort has been put into providing regulatory incentives to promote diversity of balance sheet structures, business models and risk management systems. In rebuilding and maintaining the financial system, this systemic diversity objective should probably be given much greater prominence by the regulatory community.
Second, modularity within the financial system. The structure of many non-financial networks is explicitly and intentionally modular.  This includes the design of personal computers and the world wide web and the management of forests and utility grids. Modular configurations prevent contagion infecting the whole network in the event of nodal failure. By limiting the potential for cascades, modularity protects the systemic resilience of both natural and constructed networks.
The same principles apply in banking. That is why there is an ongoing debate on the merits of splitting banks, either to limit their size (to curtail the strength of cascades following failure) or to limit their activities (to curtail the potential for cross-contamination within firms). The recently proposed Volcker rule in the United States, quarantining risky hedge fund, private equity and proprietary trading activity from other areas of banking business, is one example of modularity in practice. In the United Kingdom, the new government have recently set up a Royal Commission to investigate the case for encouraging modularity and diversity in banking ecosystems, as a means of buttressing systemic resilience.
It took a generation for ecological models to adapt. The same is likely to be true of banking and finance.”

It would be interesting to consider network models which are more realistic than these toy versions, for instance, with nodes representing banks with goals, preferences and beliefs.
F. Caccioli, M. Marsili and P. Vivo [2009]: Eroding market stability by proliferation of financial instruments. The European Physical Journal B, 71: 467–479.
Andrew Haldane and Robert May [2011]: Systemic risk in banking ecosystems. Nature, 469:  351-355.
Robert May, Simon Levin and George Sugihara [2008]: Complex systems: ecology for bankers. Nature, 451, 893–895.
Also, the UK Government’s 2011 Foresight Programme on the Future of Computer Trading in Financial Markets has published its background and working papers, here.

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