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Counterparty Credit Limits: An Effective Tool for Mitigating Counterparty Risk?

39 Pages Posted: 27 Sep 2017  

Martin David Gould

Imperial College London - Department of Mathematics

Nikolaus Hautsch

University of Vienna - Department of Statistics and Operations Research; Center for Financial Studies (CFS)

Sam Howison

University of Oxford - Nomura Centre for Quantitative Finance, OCIAM

Mason A. Porter

California Institute of Technology

Date Written: September 26, 2017

Abstract

A counterparty credit limit (CCL) is a limit imposed by a financial institution to cap its maximum possible exposure to a specified counterparty. Although CCLs are designed to help institutions mitigate counterparty risk by selective diversification of their exposures, their implementation restricts the liquidity that institutions can access in an otherwise centralized pool. We address the question of how this mechanism impacts trade prices and volatility, both empirically and via a new model of trading with CCLs. We find empirically that CCLs cause little impact on trade. However, our model highlights that in extreme situations, CCLs could serve to destabilize prices and thereby influence systemic risk.

Keywords: Counterparty Credit Limits; Counterparty Risk; Price Formation; Market Design; Systemic Risk

Suggested Citation

Gould, Martin David and Hautsch, Nikolaus and Howison, Sam and Porter, Mason A., Counterparty Credit Limits: An Effective Tool for Mitigating Counterparty Risk? (September 26, 2017). CFS Working Paper, WP No. 581. Available at SSRN: https://ssrn.com/abstract=3043112

Martin David Gould

Imperial College London - Department of Mathematics ( email )

South Kensington Campus
Imperial College
London, SW7 2AZ
United Kingdom

HOME PAGE: http://www.imperial.ac.uk/people/m.gould

Nikolaus Hautsch (Contact Author)

University of Vienna - Department of Statistics and Operations Research ( email )

Oskar-Morgenstern-Platz 1
Vienna, A-1090
Austria

Center for Financial Studies (CFS) ( email )

Grüneburgplatz 1
Frankfurt am Main, 60323
Germany

Sam Howison

University of Oxford - Nomura Centre for Quantitative Finance, OCIAM ( email )

Mathematical Institute
24-29 St Giles
Oxford OX1 3LB
United Kingdom

Mason A. Porter

California Institute of Technology ( email )

Pasadena, CA 91125
United States

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