IDEAS home Printed from https://ideas.repec.org/a/ris/apltrx/0025.html
   My bibliography  Save this article

Credit Risk Management

Author

Listed:
  • Dean Fantazzini

    (Moscow School of Economics – Moscow State University)

Abstract

The journal continues publishing the consultation of Professor Dean Fantazzini. In this issue econometric analysis of financial data in risk management is discussed. Basic concepts of credit risk management in the context of recent Basel-II agreement recommendations are introduced. One-dimensional models of credit risk for assessing the borrower’s default probability are described.In the second part, which would appear in the first issue of 2009 and would also finish the whole presentation, the author plans to discuss multidimensional models of credit risk management for assessment of the default probability of «the borrowers' portfolio»

Suggested Citation

  • Dean Fantazzini, 2008. "Credit Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 12(4), pages 84-137.
    • Handle: RePEc:ris:apltrx:0025
    as

    Download full text from publisher

    File URL: http://pe.cemi.rssi.ru/pe_2008_4_84-137.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Shleifer, Andrei & Vishny, Robert W, 1992. "Liquidation Values and Debt Capacity: A Market Equilibrium Approach," Journal of Finance, American Finance Association, vol. 47(4), pages 1343-1366, September.
    2. Griep, Clifford & De Stefano, Michael, 2001. "Standard & Poor's official response to the Basel Committee's proposal," Journal of Banking & Finance, Elsevier, vol. 25(1), pages 149-169, January.
    3. Ms. Chikako Oka, 2003. "Anticipating Arrears to the IMF Early Warning Systems," IMF Working Papers 2003/018, International Monetary Fund.
    4. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    5. Acharya, Viral V. & Bharath, Sreedhar T. & Srinivasan, Anand, 2007. "Does industry-wide distress affect defaulted firms? Evidence from creditor recoveries," Journal of Financial Economics, Elsevier, vol. 85(3), pages 787-821, September.
    6. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    7. Fuertes, Ana-Maria & Kalotychou, Elena, 2006. "Early warning systems for sovereign debt crises: The role of heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1420-1441, November.
    8. Granger, Clive W.J. & Terasvirta, Timo & Patton, Andrew J., 2006. "Common factors in conditional distributions for bivariate time series," Journal of Econometrics, Elsevier, vol. 132(1), pages 43-57, May.
    9. Merton, Robert C, 1974. "On the Pricing of Corporate Debt: The Risk Structure of Interest Rates," Journal of Finance, American Finance Association, vol. 29(2), pages 449-470, May.
    10. French, Kenneth R. & Roll, Richard, 1986. "Stock return variances : The arrival of information and the reaction of traders," Journal of Financial Economics, Elsevier, vol. 17(1), pages 5-26, September.
    11. Madhavan, Ananth & Smidt, Seymour, 1991. "A Bayesian model of intraday specialist pricing," Journal of Financial Economics, Elsevier, vol. 30(1), pages 99-134, November.
    12. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    13. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
    14. Treacy, William F. & Carey, Mark, 2000. "Credit risk rating systems at large US banks," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 167-201, January.
    15. Dean Fantazzini & Silvia Figini, 2009. "Random Survival Forests Models for SME Credit Risk Measurement," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 29-45, March.
    16. Sophia Rabe-Hesketh & Anders Skrondal, 2012. "Multilevel and Longitudinal Modeling Using Stata, 3rd Edition," Stata Press books, StataCorp LLC, edition 3, number mimus2.
    17. Merton, Robert C., 1977. "On the pricing of contingent claims and the Modigliani-Miller theorem," Journal of Financial Economics, Elsevier, vol. 5(2), pages 241-249, November.
    18. Zwane, E. N. & van der Heijden, P. G. M., 2003. "Implementing the parametric bootstrap in capture-recapture models with continuous covariates," Statistics & Probability Letters, Elsevier, vol. 65(2), pages 121-125, November.
    19. Hasabrouck, Joel & Sofianos, George, 1993. "The Trades of Market Makers: An Empirical Analysis of NYSE Specialists," Journal of Finance, American Finance Association, vol. 48(5), pages 1565-1593, December.
    20. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
    21. Cameron,A. Colin & Trivedi,Pravin K., 2005. "Microeconometrics," Cambridge Books, Cambridge University Press, number 9780521848053, Enero-Abr.
    22. Bo Cai & David B. Dunson, 2006. "Bayesian Covariance Selection in Generalized Linear Mixed Models," Biometrics, The International Biometric Society, vol. 62(2), pages 446-457, June.
    23. Merton H. Miller & Franco Modigliani, 1961. "Dividend Policy, Growth, and the Valuation of Shares," The Journal of Business, University of Chicago Press, vol. 34, pages 411-411.
    24. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2002. "Reliable estimation of generalized linear mixed models using adaptive quadrature," Stata Journal, StataCorp LLC, vol. 2(1), pages 1-21, February.
    25. Hasbrouck, Joel, 1988. "Trades, quotes, inventories, and information," Journal of Financial Economics, Elsevier, vol. 22(2), pages 229-252, December.
    26. Maria Giuli & Dean Fantazzini & Mario Maggi, 2008. "A New Approach for Firm Value and Default Probability Estimation beyond Merton Models," Computational Economics, Springer;Society for Computational Economics, vol. 31(2), pages 161-180, March.
    27. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    28. repec:bla:jfinan:v:59:y:2004:i:2:p:831-868 is not listed on IDEAS
    29. Libby, R, 1975. "Accounting Ratios And Prediction Of Failure - Some Behavioral Evidence," Journal of Accounting Research, Wiley Blackwell, vol. 13(1), pages 150-161.
    30. Allan C. Eberhart & Lawrence A. Weiss, 1998. "The Importance of Deviations from the Absolute Priority Rule in Chapter 11 Bankruptcy Proceedings," Financial Management, Financial Management Association, vol. 27(4), Winter.
    31. Sreedhar T. Bharath & Tyler Shumway, 2008. "Forecasting Default with the Merton Distance to Default Model," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1339-1369, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dean Fantazzini, 2022. "Crypto-Coins and Credit Risk: Modelling and Forecasting Their Probability of Death," JRFM, MDPI, vol. 15(7), pages 1-34, July.
    2. Казакова К.А. & Князев А.Г. & Лепёхин О.А., 2015. "Оптимальный размер банковского резерва: прогноз просроченной кредитной задолженности с использованием копулярных моделей. Optimum volume of bank reserve: forecasting of overdue credit indebtedness usi," Мир экономики и управления // Вестник НГУ. Cерия: Cоциально-экономические науки, Socionet;Новосибирский государственный университет, vol. 15(4), pages 59-76.
    3. Sangcheol Song, 2014. "Subsidiary Divestment: The Role of Multinational Flexibility," Management International Review, Springer, vol. 54(1), pages 47-70, February.
    4. Dean Fantazzini & Raffaella Calabrese, 2021. "Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure," JRFM, MDPI, vol. 14(11), pages 1-23, October.
    5. Брагин Антон Игоревич & Кузнецов Евгений Николаевич, 2011. "Анализ Значений Суверенного Кредитного Рейтинга И Его Моделирование," Российский внешнеэкономический вестник, CyberLeninka;Государственное образовательное учреждение Высшего профессионального образования Всероссийская академия внешней торговли Минэкономразвития России, vol. 2011(12), pages 21-36.
    6. Sangcheol Song, 2014. "Entry mode irreversibility, host market uncertainty, and foreign subsidiary exits," Asia Pacific Journal of Management, Springer, vol. 31(2), pages 455-471, June.
    7. Alina Mihaela Dima & Simona Vasilache, 2016. "Credit Risk modeling for Companies Default Prediction using Neural Networks," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 127-143, September.
    8. Silvia FIGINI & Ron S. KENETT & Silvia SALINI, 2010. "Integrating operational and financial risk assessments," Departmental Working Papers 2010-02, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    9. Raffaella Calabrese, 2012. "Improving Classifier Performance Assessment of Credit Scoring Models," Working Papers 201204, Geary Institute, University College Dublin.
    10. Andreeva, Galina & Calabrese, Raffaella & Osmetti, Silvia Angela, 2016. "A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models," European Journal of Operational Research, Elsevier, vol. 249(2), pages 506-516.
    11. Lore Dirick & Gerda Claeskens & Bart Baesens, 2017. "Time to default in credit scoring using survival analysis: a benchmark study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 652-665, June.
    12. Dean Fantazzini, 2009. "Credit Risk Management (Cont.)," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 13(1), pages 105-138.
    13. Raffaella Calabrese, 2011. "Cost-sensitive classification for rare events: an application to the credit rating model validation for SMEs," Working Papers 201134, Geary Institute, University College Dublin.
    14. Ana Paula Matias Gama & Helena Susana Amaral Geraldes, 2012. "Credit risk assessment and the impact of the New Basel Capital Accord on small and medium‐sized enterprises," Management Research Review, Emerald Group Publishing Limited, vol. 35(8), pages 727-749, July.
    15. Yaroslav Bologov, 2013. "A copula-based approach to portfolio credit risk modeling," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 29(1), pages 45-66.
    16. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Zhipeng, 2009. "Recovery Rates and Macroeconomic Conditions: The Role of Loan Covenants," MPRA Paper 17521, University Library of Munich, Germany.
    2. Dalla Valle, Luciana & De Giuli, Maria Elena & Tarantola, Claudia & Manelli, Claudio, 2016. "Default probability estimation via pair copula constructions," European Journal of Operational Research, Elsevier, vol. 249(1), pages 298-311.
    3. Mili, Medhi & Sahut, Jean-Michel & Teulon, Frédéric, 2018. "Modeling recovery rates of corporate defaulted bonds in developed and developing countries," Emerging Markets Review, Elsevier, vol. 36(C), pages 28-44.
    4. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    5. Han-Hsing Lee, 2020. "Distress risk, product market competition, and corporate bond yield spreads," Review of Quantitative Finance and Accounting, Springer, vol. 55(3), pages 1093-1135, October.
    6. Giesecke, Kay & Longstaff, Francis A. & Schaefer, Stephen & Strebulaev, Ilya, 2011. "Corporate bond default risk: A 150-year perspective," Journal of Financial Economics, Elsevier, vol. 102(2), pages 233-250.
    7. Mora, Nada, 2015. "Creditor recovery: The macroeconomic dependence of industry equilibrium," Journal of Financial Stability, Elsevier, vol. 18(C), pages 172-186.
    8. Gabriel Jiménez & Steven Ongena & José‐Luis Peydró & Jesús Saurina, 2014. "Hazardous Times for Monetary Policy: What Do Twenty‐Three Million Bank Loans Say About the Effects of Monetary Policy on Credit Risk‐Taking?," Econometrica, Econometric Society, vol. 82(2), pages 463-505, March.
    9. Jean-David Fermanian, 2020. "On the Dependence between Default Risk and Recovery Rates in Structural Models," Annals of Economics and Statistics, GENES, issue 140, pages 45-82.
    10. Maria Stefanova, 2012. "Recovery Risiko in der Kreditportfoliomodellierung," Springer Books, Springer, number 978-3-8349-4226-5, July.
    11. Benjamin Bade & Daniel Rösch & Harald Scheule, 2011. "Default and Recovery Risk Dependencies in a Simple Credit Risk Model," European Financial Management, European Financial Management Association, vol. 17(1), pages 120-144, January.
    12. Gopalakrishnan, Balagopal & Mohapatra, Sanket, 2020. "Insolvency regimes and firms' default risk under economic uncertainty and shocks," Economic Modelling, Elsevier, vol. 91(C), pages 180-197.
    13. 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.
    14. Cangemi, Robert R. & Mason, Joseph R. & Pagano, Michael S., 2012. "Options-based structural model estimation of bond recovery rates," Journal of Financial Intermediation, Elsevier, vol. 21(3), pages 473-506.
    15. Maria Giuli & Dean Fantazzini & Mario Maggi, 2008. "A New Approach for Firm Value and Default Probability Estimation beyond Merton Models," Computational Economics, Springer;Society for Computational Economics, vol. 31(2), pages 161-180, March.
    16. Sudheer Chava & Catalina Stefanescu & Stuart Turnbull, 2011. "Modeling the Loss Distribution," Management Science, INFORMS, vol. 57(7), pages 1267-1287, July.
    17. Stephen Zamore & Kwame Ohene Djan & Ilan Alon & Bersant Hobdari, 2018. "Credit Risk Research: Review and Agenda," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(4), pages 811-835, March.
    18. Kim, Joon Ho, 2018. "Asset specificity and firm value: Evidence from mergers," Journal of Corporate Finance, Elsevier, vol. 48(C), pages 375-412.
    19. Bhanot, Karan & François, Pascal & Kadapakkam, Palani-Rajan, 2025. "How does the structure of an interest expense cap change the tax benefits of debt?," Journal of Corporate Finance, Elsevier, vol. 91(C).
    20. Jackson, Richard H.G. & Wood, Anthony, 2013. "The performance of insolvency prediction and credit risk models in the UK: A comparative study," The British Accounting Review, Elsevier, vol. 45(3), pages 183-202.

    More about this item

    Keywords

    Credit Risk; Discriminant Analysis; Altman Model; Logit models; ROC; AUC; Loss Functions; Panel Mode;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ris:apltrx:0025. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Anatoly Peresetsky (email available below). General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.