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Counterparty Credit Limits: The Impact of a Risk-Mitigation Measure on Everyday Trading

Author

Listed:
  • Martin D. Gould
  • Nikolaus Hautsch
  • Sam D. Howison
  • Mason A. Porter
Abstract
A counterparty credit limit (CCL) is a limit that is imposed by a financial institution to cap its maximum possible exposure to a specified counterparty. CCLs help institutions to mitigate counterparty credit risk via selective diversification of their exposures. In this paper, we analyze how CCLs impact the prices that institutions pay for their trades during everyday trading. We study a high-quality data set from a large electronic trading platform in the foreign exchange spot market, which enables institutions to apply CCLs. We find empirically that CCLs had little impact on the vast majority of trades in this data. We also study the impact of CCLs using a new model of trading. By simulating our model with different underlying CCL networks, we highlight that CCLs can have a major impact in some situations.

Suggested Citation

  • Martin D. Gould & Nikolaus Hautsch & Sam D. Howison & Mason A. Porter, 2017. "Counterparty Credit Limits: The Impact of a Risk-Mitigation Measure on Everyday Trading," Papers 1709.08238, arXiv.org, revised Jan 2021.
    • Handle: RePEc:arx:papers:1709.08238
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    References listed on IDEAS

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    1. Craig, Ben & von Peter, Goetz, 2014. "Interbank tiering and money center banks," Journal of Financial Intermediation, Elsevier, vol. 23(3), pages 322-347.
    2. Rehlon, Amandeep & Nixon, Dan, 2013. "Central counterparties: what are they, why do they matter and how does the Bank supervise them?," Bank of England Quarterly Bulletin, Bank of England, vol. 53(2), pages 147-156.
    3. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    4. Robert M. May & Simon A. Levin & George Sugihara, 2008. "Ecology for bankers," Nature, Nature, vol. 451(7181), pages 893-894, February.
    5. Craig Pirrong, 2012. "Clearing and Collateral Mandates: A New Liquidity Trap?," Journal of Applied Corporate Finance, Morgan Stanley, vol. 24(1), pages 67-73, March.
    6. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2013. "Limit order books," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1709-1742, November.
    7. Robert A. Jarrow & Fan Yu, 2008. "Counterparty Risk and the Pricing of Defaultable Securities," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 20, pages 481-515, World Scientific Publishing Co. Pte. Ltd..
    8. Thorsten V. Koeppl, 2013. "The Limits Of Central Counterparty Clearing: Collusive Moral Hazard And Market Liquidity," Working Paper 1312, Economics Department, Queen's University.
    9. Morten Bech, 2012. "FX volume during the financial crisis and now," BIS Quarterly Review, Bank for International Settlements, March.
    10. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
    11. Fricke, Daniel & Lux, Thomas, 2012. "Core-periphery structure in the overnight money market: Evidence from the e-MID trading platform," Kiel Working Papers 1759, Kiel Institute for the World Economy (IfW Kiel).
    12. Roll, Richard, 1984. "A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market," Journal of Finance, American Finance Association, vol. 39(4), pages 1127-1139, September.
    13. William Perraudin & Paolo Vitale, 1996. "Interdealer Trade and Information Flows in a Decentralized Foreign Exchange Market," NBER Chapters, in: The Microstructure of Foreign Exchange Markets, pages 73-106, National Bureau of Economic Research, Inc.
    14. Fricke, Daniel, 2012. "Trading strategies in the overnight money market: Correlations and clustering on the e-MID trading platform," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6528-6542.
    15. Bruno Biais & Florian Heider & Marie Hoerova, 2012. "Clearing, Counterparty Risk, and Aggregate Risk," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 60(2), pages 193-222, July.
    16. Jeffrey A. Frankel & Giampaolo Galli & Alberto Giovannini, 1996. "The Microstructure of Foreign Exchange Markets," NBER Books, National Bureau of Economic Research, Inc, number fran96-1.
    17. Philippe Jorion & Gaiyan Zhang, 2009. "Credit Contagion from Counterparty Risk," Journal of Finance, American Finance Association, vol. 64(5), pages 2053-2087, October.
    18. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    19. Stefan Weber & Kay Giesecke, 2003. "Credit Contagion and Aggregate Losses," Computing in Economics and Finance 2003 246, Society for Computational Economics.
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