Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-08T08:22:23.667Z Has data issue: false hasContentIssue false

16 - Diversification in Financial Networks may Increase Systemic Risk

from PART V - SYSTEMIC RISK ANDMATHEMATICAL FINANCE

Published online by Cambridge University Press:  05 June 2013

By
Josselin Garnier ,
George Papanicolaou  and
Tzu-Wei Yang
Edited by
Jean-Pierre Fouque  and
Joseph A. Langsam
Josselin Garnier
Affiliation:
Université Paris VII
George Papanicolaou
Affiliation:
Stanford University
Tzu-Wei Yang
Affiliation:
Stanford University
Jean-Pierre Fouque
Affiliation:
University of California, Santa Barbara
Joseph A. Langsam
Affiliation:
University of Maryland, College Park
Get access

Summary

Abstract It has been pointed out in the macroeconomics and financial risk literature that risk-sharing by diversification in a financial network may increase the systemic risk. This means roughly that while individual agents in the network, for example banks, perceive their risk of default or insolvency decrease as a result of cooperation, the overall risk, that is, the risk that several agents may default simultaneously, or nearly so, may in fact increase. We present the results of a recent mathematical study that addresses this issue, relying on a mean-field model of interacting diffusions and its large deviations behavior. We also review briefly some recent literature that addresses similar issues.

Keywords systemic risk, mean field, large deviations, dynamic phase transitions; MSC Codes: 60F10, 60K35, 91B30, 82C26

Introduction

Systemic risk is the risk that a large number of components of an interconnected financial system fail within a short time thus leading to the overall failure of the financial system. What is particularly interesting is that the onset of this overall failure can occur even when the individual agents in the system perceive that their own individual risk of failure is diminished by diversification through cooperation. This phenomenon is described and put into a broader perspective in Haldane's recent presentation (Haldane, 2009), which was the starting point of our own work (Garnier et al., 2012). In this review we first introduce and describe our model for the role of cooperation in determining systemic risk.

Type
Chapter
Information
Handbook on Systemic Risk , pp. 432 - 443
Publisher: Cambridge University Press
Print publication year: 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

S., Battiston, D. D., Gatti, M., Gallegati, B. C., Greenwald, and J. E., Stiglitz (2009). Liaisons dangereuses: increasing connectivity, risk sharing, and systemic risk. Working Paper 15611, National Bureau of Economic Research.CrossRef
N., Beale, D., Rand, H., Battey, K., Croxson, R., May, and M., Nowak (2011). Individual versus systemic risk and the Regulator's Dilemma. Proceedings of the National Academy of Sciences 108 12647.Google Scholar
D. A., Dawson (1983) Critical dynamics and fluctuations for a mean-field model of cooperative behavior. J. Statist. Phys. 31 29-85.Google Scholar
D. A., Dawson and J., Gartner (1987). Large deviations from the McKean-Vlasov limit for weakly interacting diffusions. Stochastics 20 247-308.Google Scholar
D. A., Dawson and J., Gartner, (1989). Large Deviations, Free Energy Functional and Quasi- potential for a Mean Field Model of Interacting Diffusions. Mem. Amer. Math. Soc. 78.Google Scholar
A., Dembo and O., Zeitouni (2010). Large Deviations Techniques and Applications. Corrected reprint of the second (1998) edition. Springer-Verlag, Berlin.Google Scholar
J., Garnier, G., Papanicolaou, and T.-W., Yang (2012). Large deviations for a mean field model of systemic risk. In Preparation.
A., Haldane (2009). Rethinking the financial network. Speech delivered at the Financial Student Association, Amsterdam.
A. G., Haldane and R. M., May, (2011). Systemic risk in banking ecosystems. Nature 469 351-355.Google Scholar
R., May and N., Arinaminpathy (2010). Systemic risk: the dynamics of model banking systems. Journal of the Royal Society Interface 7 823-838.Google Scholar
E., Nier, J., Yang, T., Yorulmazer, and A., Alentorn (2007). Network models and financial stability. Journal of Economic Dynamics and Control 31 2033-2060.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×