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Credit Risk Management (Cont.)

Author

Listed:
  • Fantazzini , Dean

    (Moscow School of Economics – Moscow State University)

Abstract

In this issue we publish the fourth part of professor Fantazzini’s consultation series on econometric analysis of financial data in risk management. This time it deals with the topic of credit risk management. After having described one-dimensional models of credit risk in the previous issue the author is analyzing multidimensional models which make it possible to assess the default probability of borrower’s portfolio

Suggested Citation

  • 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.
    • Handle: RePEc:ris:apltrx:0028
    as

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    References listed on IDEAS

    as
    1. Fantazzini, Dean, 2008. "Credit Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 12(4), pages 84-137.
    2. 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.
    3. 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

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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. 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.
    3. 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.

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    More about this item

    Keywords

    Credit Risk; Value at Risk; Expected Shortfall; CreditMetrics; KMV; CreditRisk+; CreditPortfolioView; Backtesting; Berkowitz Test;
    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
    • 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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