IDEAS home Printed from https://ideas.repec.org/p/zbw/iwhdps/iwh-3-09.html

Berücksichtigung von Schätzunsicherheit bei der Kreditrisikobewertung: Vergleich des Value at Risk der Verlustverteilung des Kreditrisikos bei Verwendung von Bootstrapping und einem asymptotischen Ansatz

Author

Listed:
  • Dannenberg, Henry

Abstract

Bei der Kreditrisikobewertung müssen die Parameter Ausfallwahrscheinlichkeit und korrelation geschätzt werden. Diese Schätzung erfolgt unter Unsicherheit. In der Literatur werden asymptotische Konfidenzregionen diskutiert, um diese Unsicherheit bei der simultanen Schätzung beider Parameter zu bewerten. Diese Regionen setzen allerdings eine sehr lange Datenhistorie für eine genaue Bewertung voraus. Als Alternative bietet sich bei kurzen Datenhistorien Bootstrapping an. Diese Methode ist allerdings deutlich rechenintensiver. Im vorliegenden Beitrag wird untersucht, ab welcher Anzahl historisch verfügbarer Perioden Bootstrapping und eine WaldKonfidenzregion zu einer vergleichbaren Bewertung des Kreditrisikos gelangen. Die hier genutzten Methoden führen zu ähnlichen Ergebnissen, wenn über 100 historische Perioden zur Verfügung stehen.

Suggested Citation

  • Dannenberg, Henry, 2009. "Berücksichtigung von Schätzunsicherheit bei der Kreditrisikobewertung: Vergleich des Value at Risk der Verlustverteilung des Kreditrisikos bei Verwendung von Bootstrapping und einem asymptotischen Ansatz," IWH Discussion Papers 3/2009, Halle Institute for Economic Research (IWH).
  • Handle: RePEc:zbw:iwhdps:iwh-3-09
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/29982/1/598002146.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Miao W. & Gastwirth J.L., 2004. "The Effect of Dependence on Confidence Intervals for a Population Proportion," The American Statistician, American Statistical Association, vol. 58, pages 124-130, May.
    2. Hamerle, Alfred & Knapp, Michael & Liebig, Thilo & Wildenauer, Nicole, 2005. "Incorporating prediction and estimation risk in point-in-time credit portfolio models," Discussion Paper Series 2: Banking and Financial Studies 2005,13, Deutsche Bundesbank.
    3. Christensen, Jens H.E. & Hansen, Ernst & Lando, David, 2004. "Confidence sets for continuous-time rating transition probabilities," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2575-2602, November.
    Full references (including those not matched with items on IDEAS)

    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. Schechtman, Ricardo, 2013. "Default matrices: A complete measurement of banks’ consumer credit delinquency," Journal of Financial Stability, Elsevier, vol. 9(4), pages 460-474.
    2. Trueck, Stefan & Rachev, Svetlozar T., 2008. "Rating Based Modeling of Credit Risk," Elsevier Monographs, Elsevier, edition 1, number 9780123736833.
    3. Weißbach, Rafael & Mollenhauer, Thomas, 2011. "Modelling Rating Transitions," VfS Annual Conference 2011 (Frankfurt, Main): The Order of the World Economy - Lessons from the Crisis 48698, Verein für Socialpolitik / German Economic Association.
    4. Figlewski, Stephen & Frydman, Halina & Liang, Weijian, 2012. "Modeling the effect of macroeconomic factors on corporate default and credit rating transitions," International Review of Economics & Finance, Elsevier, vol. 21(1), pages 87-105.
    5. Ángel Beade & Manuel Rodríguez & José Santos, 2024. "Multiperiod Bankruptcy Prediction Models with Interpretable Single Models," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1357-1390, September.
    6. Arnaud_de_Servigny & Norbert_Jobst, 2005. "An Empirical Analysis of Equity Default Swaps (I): Univariate Insights," International Finance 0503007, University Library of Munich, Germany.
    7. Jones, Stewart & Johnstone, David & Wilson, Roy, 2015. "An empirical evaluation of the performance of binary classifiers in the prediction of credit ratings changes," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 72-85.
    8. François Coppens & Fernando Gonzáles & Gerhard Winkler, 2007. "The performance of credit rating systems in the assessment of collateral used in Eurosystem monetary policy operations," Working Paper Research 118, National Bank of Belgium.
    9. Jeffrey R. Stokes, 2023. "A nonlinear inversion procedure for modeling the effects of economic factors on credit risk migration," Review of Quantitative Finance and Accounting, Springer, vol. 61(3), pages 855-878, October.
    10. Anisa Caja & Frédéric Planchet, 2014. "Modeling Cycle Dependence in Credit Insurance," Risks, MDPI, vol. 2(1), pages 1-15, March.
    11. Mogens Bladt & Michael SØrensen, 2009. "Efficient estimation of transition rates between credit ratings from observations at discrete time points," Quantitative Finance, Taylor & Francis Journals, vol. 9(2), pages 147-160.
    12. Dimitris Gavalas & Theodore Syriopoulos, 2014. "Bank Credit Risk Management and Migration Analysis; Conditioning Transition Matrices on the Stage of the Business Cycle," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 20(2), pages 151-166, May.
    13. Xing, Haipeng & Sun, Ning & Chen, Ying, 2012. "Credit rating dynamics in the presence of unknown structural breaks," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 78-89.
    14. Dionne, Georges & Gauthier, Geneviève & Hammami, Khemais & Maurice, Mathieu & Simonato, Jean-Guy, 2011. "A reduced form model of default spreads with Markov-switching macroeconomic factors," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1984-2000, August.
    15. Fuertes, Ana-Maria & Kalotychou, Elena, 2007. "On sovereign credit migration: A study of alternative estimators and rating dynamics," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3448-3469, April.
    16. Orth, Walter, 2011. "Default probability estimation in small samples: With an application to sovereign bonds," Discussion Papers in Econometrics and Statistics 5/11, University of Cologne, Institute of Econometrics and Statistics.
    17. Nian Yao & Zhiming Yang, 2017. "Optimal excess-of-loss reinsurance and investment problem for an insurer with default risk under a stochastic volatility model," Papers 1704.08234, arXiv.org.
    18. Guglielmo D’Amico, 2015. "Rate of Occurrence of Failures (ROCOF) of Higher-Order for Markov Processes: Analysis, Inference and Application to Financial Credit Ratings," Methodology and Computing in Applied Probability, Springer, vol. 17(4), pages 929-949, December.
    19. Thomas Lagner & Dodozu Knyphausen‐Aufseß, 2012. "Rating Agencies as Gatekeepers to the Capital Market: Practical Implications of 40 Years of Research," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 21(3), pages 157-202, August.
    20. Steffi Höse & Stefan Huschens, 2011. "Confidence Intervals for Asset Correlations in the Asymptotic Single Risk Factor Model," Operations Research Proceedings, in: Bo Hu & Karl Morasch & Stefan Pickl & Markus Siegle (ed.), Operations Research Proceedings 2010, pages 111-116, Springer.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    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:zbw:iwhdps:iwh-3-09. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/iwhhhde.html .

    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.