Counterparty Risk Subject To ATE

Zhou, Richard (2010): Counterparty Risk Subject To ATE.

Abstract

Rating trigger ATE (Additional Termination Event) is a counterparty risk mitigant that allows banks to terminate and close out bilateral derivative contracts if the credit rating of the counterparty falls below the trigger level. Since credit default is often preceded by rating downgrades, ATE clause effectively reduces the counterparty credit risk by early termination of exposure. However, there is still the risk that counterparty may default without going through severe downgrade. This article presents a practical model for valuating CVA in the presence of ATE.

• Item Type: MPRA Paper
• Language: English
• Keywords: Counterparty Risk, Credit Valuation Adjustment, Rating Transition, Rating Trigger, Additional Termination Event
• Subjects: C - Mathematical and Quantitative Methods > C0 - General > C00 - General

References

Alavian, S., Ding, J., Whitehead, P. and Laudicina, L. (2009) Counterparty Valuation Adjustment (CVA), Working paper.

Brigo, D. and Chourdakis, K. (2009) ‘Counterparty Risk for Credit Default Swaps: Impact of spread volatility and default correlation’, Int. J. Theor. Appl. Finance, Vol. 12.

Brigo, D. and Morini, M. (2010) Dangers of Bilateral Counterparty Risk: The fundamental impact of closeout conventions, Working paper.

Gregory, J. (2009) ‘Being two-faced over counterparty credit risk’, Risk Magazine, February pp. 86-90.

Gregory, J. (2010) ‘Counterparty Credit Risk: The new challenge for global financial markets’, Wiley Finance.

Huge, B. and Lando, D. (1999) ‘Swap Pricing with Two-Side Default Risk in a Rating-Based Model’, Euro. Finance Rev. Vol. 3, pp. 239-268.

Hull, J. (2009) The Credit Crunch of 2007: What Went Wrong? Why? What Lessons Can Be Learned?, Working paper, University of Toronto.

Jarrow, R., Lando, D. and Turnbull, S. (1997) ‘A Markov model for the term structure of credit risk spreads’, Review Financial Studies, Vol. 10 No. 2, pp.481-523.

Kijima, M. and Komoribayashi, K. (1998) ‘A Markov chain model for valuing credit risk derivatives’, J. Derivatives, Vol. 6, No. 1, pp.97-108.

Kreinin, A. and Sidelnikova, M. (2001) ‘Regularization Algorithms for Transition Matrices’, Algo Research Quarterly, Vol. 4, June.24

Lando, D. and Mortensen, A. (2005) ‘On the pricing of step-up bonds in the European telecom sector’, J. Credit Risk, Vol. 1 No. 1, pp. 71-109.

Israel, R., Rosenthal, J. and Wei, J. (2001) ‘Finding generators for Markov Chains via Empirical Transition Matrices, with Applications to Credit Ratings’, Math. Finance, Vol. 11, No. 2, pp 245-265.

Moody’s (2009) Corporate Default and Recovery Rates, 1920-2008, Moody’s Special Comment, February. RiskMetrics (1997) CreditMetrics Technical Document, RiskMetrics Group.

Pykhtin, M. and Zhu, S. (2007) ‘A Guide to Modeling Counterparty Credit Risk’, GARP Risk Review, July/August.

Schonbucher, P. (2003) Credit derivative pricing models, Wiley Finance.

Yi, C. (2010) Dangerous Knowledge: Credit value adjustment with credit trigger, Working paper.

Zeng, B. and Zhang, J. (2001a) Measuring Credit Correlations: Equity Correlations Are Not Enough, KMV.

Zeng, B. and Zhang, J. (2001b) An Empirical Assessment of Asset Correlation Models, KMV report, November.

Zhu, S. and Lomibao, D. (2005) ‘A conditional Valuation Approach for Path-Dependent Instruments’, J. Credit Risk.