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What Do We Know About Exposure At Default On Contingent Credit Lines A Survey Of The Literature Empirical Analysis And Models

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  • Michael Jacobs, Jr.
  • Pinaki Bag

Abstract

Exposure at Default EAD quantification for the large exposures to contingent credit lines CCLs is a critical for models of credit risk amongst financial institutions This includes expected loss calculations for loan provisions economic credit capital as well as regulatory capital under the Basel II advanced Internal Ratings Based IRB framework However banks struggle in quantifying EAD due to limited empirical evidence and industry benchmarks unavailable or inconsistent internal data and paucity of practical models This study contributes to this modeling effort by surveying the existing literature and consolidating the empirical evidence on EAD We consider recent extensions of prior empirical work that considers alternative determinants and measures of EAD risk in addition to the traditional approaches including regression models and actuarial based models of EAD We illustrate these new EAD paradigms through an empirical investigation using a sample of Moody s rated defaulted firms first the construction of a predictive econometric model in the generalized linear model class followed by the calibration of an EAD model similar to basic CreditRisk type using Fast Fourrier transforms to convolute portfolio segments

Suggested Citation

  • Michael Jacobs, Jr. & Pinaki Bag, 2011. "What Do We Know About Exposure At Default On Contingent Credit Lines A Survey Of The Literature Empirical Analysis And Models," Journal of Advanced Studies in Finance, ASERS Publishing, vol. 2(1), pages 26-46.
  • Handle: RePEc:srs:jasf00:v:2:y:2011:i:1:p:26-46
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    Cited by:

    1. Frank Ranganai Matenda & Mabutho Sibanda & Eriyoti Chikodza & Victor Gumbo, 2021. "Determinants of corporate exposure at default under distressed economic and financial conditions in a developing economy: the case of Zimbabwe," Risk Management, Palgrave Macmillan, vol. 23(1), pages 123-149, June.
    2. Shan Luo & Anthony Murphy, 2020. "Understanding the Exposure at Default Risk of Commercial Real Estate Construction and Land Development Loans," Working Papers 2007, Federal Reserve Bank of Dallas.
    3. Jennifer Betz & Maximilian Nagl & Daniel Rösch, 2022. "Credit line exposure at default modelling using Bayesian mixed effect quantile regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2035-2072, October.
    4. Gürtler, Marc & Hibbeln, Martin Thomas & Usselmann, Piet, 2018. "Exposure at default modeling – A theoretical and empirical assessment of estimation approaches and parameter choice," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 176-188.

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