IDEAS home Printed from https://ideas.repec.org/a/ris/apltrx/0028.html
   My bibliography  Save this article

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

    Download full text from publisher

    File URL: http://pe.cemi.rssi.ru/pe_2009_1_105-138.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    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

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


    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.

    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. 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.
    2. Dean Fantazzini, 2022. "Crypto-Coins and Credit Risk: Modelling and Forecasting Their Probability of Death," JRFM, MDPI, vol. 15(7), pages 1-34, July.
    3. Fantazzini, Dean, 2008. "Credit Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 12(4), pages 84-137.
    4. Ruey-Ching Hwang, 2013. "Forecasting credit ratings with the varying-coefficient model," Quantitative Finance, Taylor & Francis Journals, vol. 13(12), pages 1947-1965, December.
    5. Giordani, Paolo & Jacobson, Tor & Schedvin, Erik von & Villani, Mattias, 2014. "Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(4), pages 1071-1099, August.
    6. Hu, Xiaolu & Shi, Jing & Wang, Lafang & Yu, Jing, 2020. "Foreign ownership in Chinese credit ratings industry: Information revelation or certification?," Journal of Banking & Finance, Elsevier, vol. 118(C).
    7. Chen, Shenglan & Ma, Hui & Teng, Haimeng & Wu, Qiang, 2022. "Banking liberalization and corporate tax planning: Evidence from natural experiments," Journal of Corporate Finance, Elsevier, vol. 76(C).
    8. Wang, Peiwen & Chen, Minghua & Wu, Ji & Yan, Yuanyun, 2023. "Do peer effects matter in bank risk? Some cross-country evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    9. Sangcheol Song, 2014. "Subsidiary Divestment: The Role of Multinational Flexibility," Management International Review, Springer, vol. 54(1), pages 47-70, February.
    10. Evan Dudley & Niclas Andrén & Håkan Jankensgård, 2022. "How do firms hedge in financial distress?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1324-1351, July.
    11. Mohsen Afsharian & Anna Kryvko & Peter Reichling, 2011. "Efficiency and Its Impact on the Performance of European Commercial Banks," FEMM Working Papers 110018, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    12. Erwan Morellec & Philip Valta & Alexei Zhdanov, 2015. "Financing Investment: The Choice Between Bonds and Bank Loans," Management Science, INFORMS, vol. 61(11), pages 2580-2602, November.
    13. Ahsan Habib & Mabel D' Costa & Hedy Jiaying Huang & Md. Borhan Uddin Bhuiyan & Li Sun, 2020. "Determinants and consequences of financial distress: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 1023-1075, April.
    14. Huang, Hsing-Hua & Lee, Han-Hsing, 2013. "Product market competition and credit risk," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 324-340.
    15. Miquel-Flores, Ixart & Reghezza, Alessio & Buchetti, Bruno & Perdichizzi, Salvatore, 2024. "Greening the economy: how public-guaranteed loans influence firm-level resource allocation," Working Paper Series 2916, European Central Bank.
    16. Nguyen, Justin Hung & Qiu, Buhui, 2022. "Right-to-Work laws and corporate innovation," Journal of Corporate Finance, Elsevier, vol. 76(C).
    17. Shang, Chenguang, 2021. "Dare to play with fire? Managerial ability and the use of short-term debt," Journal of Corporate Finance, Elsevier, vol. 70(C).
    18. Chen, Jiayuan & Gong, Di & Muckley, Cal, 2020. "Stock market illiquidity, bargaining power and the cost of borrowing," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 181-206.
    19. Cao, June & Ee, Mong Shan & Hasan, Iftekhar & Huang, He, 2024. "Asymmetric reactions of abnormal audit fees jump to credit rating changes," The British Accounting Review, Elsevier, vol. 56(2).
    20. 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.

    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

    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:0028. 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.