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Credit Risk Management

Author

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  • Fantazzini, Dean

    () (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

  • Fantazzini, Dean, 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
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    Cited by:

    1. 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.
    2. Sangcheol Song, 2014. "Subsidiary Divestment: The Role of Multinational Flexibility," Management International Review, Springer, vol. 54(1), pages 47-70, February.
    3. 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.
    4. 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.
    5. 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.
    6. Raffaella Calabrese, 2012. "Improving Classifier Performance Assessment of Credit Scoring Models," Working Papers 201204, Geary Institute, University College Dublin.
    7. 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.
    8. 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.
    9. 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.
    10. Fantazzini , Dean, 2009. "Credit Risk Management (Cont.)," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 13(1), pages 105-138.
    11. 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.
    12. 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: An empirical analysis," Management Research Review, Emerald Group Publishing, vol. 35(8), pages 727-749, July.
    13. Bologov , Yaroslav, 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.
    14. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.

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    More about this item

    Keywords

    Credit Risk; Discriminant Analysis; Altman Model; Logit models; ROC; AUC; Loss Functions; Panel Models; Merton Model; ZPP; Recovery Rate; Exposure at Default; Value at Risk; Expected Shortfall;
    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

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