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Estimating Recovery Rates on Bank’s Historical Loan Loss Data

Author

Listed:
  • Bandyopadhyay, Arindam
  • Singh, Pratima

Abstract

The main objective of this paper is to estimate a statistical model that incorporates information at different levels: collateral, facility, industry, zone and the macro economy to predict the Recovery Rates which will enable the bank to arrive at the Loss Given Default figure that would help to better price and manage credit risk. This estimated LGD can also play a critical role in meeting the Basel II requirements on advanced Internal Rating Based Approach (AIRB).

Suggested Citation

  • Bandyopadhyay, Arindam & Singh, Pratima, 2007. "Estimating Recovery Rates on Bank’s Historical Loan Loss Data," MPRA Paper 9525, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:9525
    as

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    File URL: https://mpra.ub.uni-muenchen.de/9525/1/MPRA_paper_9525.pdf
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    References listed on IDEAS

    as
    1. Yawitz, Jess B., 1977. "An Analytical Model of Interest Rate Differentials and Different Default Recoveries," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 12(3), pages 481-490, September.
    2. Ivailo Izvorski, 1997. "Recovery Ratios and Survival Times for Corporate Bonds," IMF Working Papers 1997/084, International Monetary Fund.
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    Cited by:

    1. Júdice, Pedro & Zhu, Qiji Jim, 2021. "Bank balance sheet risk allocation," Journal of Banking & Finance, Elsevier, vol. 133(C).

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    More about this item

    Keywords

    Loss Estimation; Credit Risk; Modeling; Bank;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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