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Exposure at Default Model for Contingent Credit Line

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  • Bag, Pinaki

Abstract

In-spite of large volume of Contingent Credit Lines (CCL) in all commercial banks paucity of Exposure at Default (EAD) models, unsuitability of external data and inconsistent internal data with partial draw-down, has been a major challenge for risk managers as well as regulators for managing CCL portfolios. Current paper is an attempt to build an easy to implement, pragmatic and parsimonious yet accurate model to determine exposure distribution of a CCL portfolio. Each of the credit line in a portfolio is modeled as a portfolio of large number of option instrument which can be exercised by the borrower determining the level of usage. Using an algorithm similar to basic CreditRisk+ and Fourier Transforms we arrive at a portfolio level probability distribution of usage.

Suggested Citation

  • Bag, Pinaki, 2010. "Exposure at Default Model for Contingent Credit Line," MPRA Paper 20387, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:20387
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    References listed on IDEAS

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    1. Evan Gatev & Philip E. Strahan, 2006. "Banks' Advantage in Hedging Liquidity Risk: Theory and Evidence from the Commercial Paper Market," Journal of Finance, American Finance Association, vol. 61(2), pages 867-892, April.
    2. Gabriel Jiménez & Jose A. Lopez & Jesus Saurina, 2009. "Empirical Analysis of Corporate Credit Lines," The Review of Financial Studies, Society for Financial Studies, vol. 22(12), pages 5069-5098, December.
    3. Agarwal, Sumit & Ambrose, Brent W. & Liu, Chunlin, 2006. "Credit Lines and Credit Utilization," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(1), pages 1-22, February.
    4. O. Emre Ergungor, 2001. "Theories of loan commitments: a literature review," Economic Review, Federal Reserve Bank of Cleveland, issue Q III, pages 2-19.
    5. Thakor, Anjan V. & Udell, Gregory F., 1987. "An economic rationale for the pricing structure of bank loan commitments," Journal of Banking & Finance, Elsevier, vol. 11(2), pages 271-289, June.
    6. Bernd Engelmann & Robert Rauhmeier (ed.), 2006. "The Basel II Risk Parameters," Springer Books, Springer, number 978-3-540-33087-5, January.
    7. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
    8. Amir Sufi, 2009. "Bank Lines of Credit in Corporate Finance: An Empirical Analysis," The Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1057-1088, March.
    9. Crouhy, Michel & Galai, Dan & Mark, Robert, 2000. "A comparative analysis of current credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 59-117, January.
    10. Maksimovic, Vojislav, 1990. "Product Market Imperfections and Loan Commitments," Journal of Finance, American Finance Association, vol. 45(5), pages 1641-1653, December.
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    Cited by:

    1. Lin Chen & Zongfang Zhou & Yi Peng & Gang Kou, 2011. "Structural Model For Determining Enterprise Group'S Integrated Lines Of Credit," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 269-285.

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    More about this item

    Keywords

    EAD; Basel II; Credit Risk; Contingent credit line (CCL);
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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