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Stability analysis of financial contagion due to overlapping portfolios

Common asset holdings are widely believed to have been the primary vector of contagion in the recent financial crisis. We develop a network approach to the amplification of financial contagion due to the combination of overlapping portfolios and leverage, and we show how it can be understood in terms of a generalized branching process. By studying a stylized model we estimate the circumstances under which systemic instabilities are likely to occur as a function of parameters such as leverage, market crowding, diversification, and market impact. Although diversification may be good for individual institutions, it can create dangerous systemic effects, and as a result financial contagion gets worse with too much diversification. Under our model there is a critical threshold for leverage; below it financial networks are always stable, and above it the unstable region grows as leverage increases. The financial system exhibits "robust yet fragile" behavior, with regions of the parameter space where contagion is rare but catastrophic whenever it occurs. Our model and methods of analysis can be calibrated to real data and provide simple yet powerful tools for macroprudential stress testing.

 

Stability analysis of financial contagion due to overlapping portfolios

Fabio Caccioli, Munik Shrestha, Cristopher Moore, J. Doyne Farmer

http://arxiv.org/abs/1210.5987


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FuturICT: Exploratory of society: L. E. Cederman, R. Conte, D. Helbing, A. Nowak, F. Schweitzer, A. Vespignani

FuturICT: Exploratory of society: L. E. Cederman, R. Conte, D. Helbing, A. Nowak, F. Schweitzer, A. Vespignani | FuturICT Journal Publications | Scoop.it

FuturICT: Exploratory of Society

L. E. Cederman, R. Conte, D. Helbing, A. Nowak, F. Schweitzer, A. Vespignani

Abstract

A huge flow of quantitative social, demographic and behavioral data is becoming available that traces the activities and interactions of individuals, social patterns, transportation infrastructures and travel fluxes. This has caused, together with innovative computational techniques and methods for modeling social actions in hybrid (natural and artificial) societies, a qualitative change in the ways we model socio-technical systems.

 

For the first time, society can be studied in a comprehensive fashion that addresses social and behavioral complexity. In other words we are in the position to envision the development of large data and computational cyber infrastructure defining an exploratory of society that provides quantitative anticipatory, explanatory and scenario analysis capabilities ranging from emerging infectious disease to conflict and crime surges.

 

The goal of the exploratory of society is to provide the basic infrastructure embedding the framework of tools and knowledge needed for the design of forecast/anticipatory/crisis management approaches to socio technical systems, supporting future decision making procedures by accelerating the scientific cycle that goes from data generation to predictions.

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JOURNAL: THE EUROPEAN PHYSICAL JOURNAL SPECIAL TOPICS  Vol. 214 (November II 2012)"Participatory Science and Computing for Our Complex World".

http://epjst.epj.org/index.php?option=com_toc&url=/articles/epjst/abs/2012/14/contents/contents.html

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