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Greg M. Gupton

Personal Details

First Name:Greg
Middle Name:M.
Last Name:Gupton
RePEc Short-ID:pgu139
[This author has chosen not to make the email address public]


Federal Reserve Bank of New York

New York City, New York (United States)

33 Liberty Street, New York, NY 10045-0001
RePEc:edi:frbnyus (more details at EDIRC)

Research output

Jump to: Articles


  1. Greg M. Gupton, 2012. "Stochastic Analysis with Financial Applications, by Arturo Kohatsu-Higa, Nicolas Privault and Shuenn-Jyi Sheu (Eds.)," Quantitative Finance, Taylor & Francis Journals, vol. 12(5), pages 691-692, May.
  2. Greg M. Gupton, 2005. "Advancing Loss Given Default Prediction Models: How the Quiet Have Quickened," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 34(2), pages 185-230, July.


Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.


  1. Greg M. Gupton, 2005. "Advancing Loss Given Default Prediction Models: How the Quiet Have Quickened," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 34(2), pages 185-230, July.

    Cited by:

    1. Jiří Witzany & Michal Rychnovský & Pavel Charamza, 2010. "Survival Analysis in LGD Modeling," Working Papers IES 2010/02, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2010.
    2. Rumyantseva, Ekaterina & Furmanov, Kirill, 2017. "Realisation of mortgage property: Survival analysis," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 48, pages 22-43.
    3. Filippo Curti & Marco Migueis, 2016. "Predicting Operational Loss Exposure Using Past Losses," Finance and Economics Discussion Series 2016-2, Board of Governors of the Federal Reserve System (U.S.), revised 12 Oct 2016.
    4. Thamayanthi Chellathurai, 2017. "Probability Density Of Recovery Rate Given Default Of A Firm’S Debt And Its Constituent Tranches," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(04), pages 1-34, June.
    5. Dannenberg, Henry, 2006. "Die Verlustverteilung des unternehmerischen Forderungsausfallrisikos – Eine simulationsbasierte Modellierung," IWH Discussion Papers 10/2006, Halle Institute for Economic Research (IWH).
    6. Mustapha Ammari & Ghizlane Lakhnati, 2017. "Loss Given Default Estimating by the Conditional Minimum Value," International Journal of Economics and Financial Issues, Econjournals, vol. 7(3), pages 779-785.
    7. Yashkir, Olga & Yashkir, Yuriy, 2013. "Loss Given Default Modelling: Comparative Analysis," MPRA Paper 46147, University Library of Munich, Germany.
    8. Krüger, Steffen & Oehme, Toni & Rösch, Daniel & Scheule, Harald, 2018. "A copula sample selection model for predicting multi-year LGDs and Lifetime Expected Losses," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 246-262.
    9. Jiří Witzany, 2009. "Unexpected Recovery Risk and LGD Discount Rate Determination," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2009(1), pages 61-84.
    10. Stefan Hlawatsch, 2009. "A Framework for LGD Validation of Retail Portfolios," FEMM Working Papers 09025, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.

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