IDEAS home Printed from https://ideas.repec.org/a/spr/comgts/v5y2008i4p337-354.html
   My bibliography  Save this article

Credit portfolio risk and asset price cycles

Author

Listed:
  • Klaus Rheinberger
  • Martin Summer

Abstract

No abstract is available for this item.

Suggested Citation

  • Klaus Rheinberger & Martin Summer, 2008. "Credit portfolio risk and asset price cycles," Computational Management Science, Springer, vol. 5(4), pages 337-354, October.
    • Handle: RePEc:spr:comgts:v:5:y:2008:i:4:p:337-354
    DOI: 10.1007/s10287-007-0057-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10287-007-0057-9
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10287-007-0057-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bernanke, Ben S. & Gertler, Mark & Gilchrist, Simon, 1999. "The financial accelerator in a quantitative business cycle framework," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 21, pages 1341-1393, Elsevier.
    2. Charles Goodhart & Boris Hofmann & Miguel Segoviano, 2004. "Bank Regulation and Macroeconomic Fluctuations," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 20(4), pages 591-615, Winter.
    3. Gordy, Michael B., 2000. "A comparative anatomy of credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 119-149, January.
    4. repec:bla:ecnote:v:33:y:2004:i:2:p:183-208 is not listed on IDEAS
    5. repec:zbw:bofrdp:2000_002 is not listed on IDEAS
    6. Gurdip Bakshi & Dilip B. Madan & Frank X. Zhang, 2001. "Understanding the role of recovery in default risk models: empirical comparisons and implied recovery rates," Finance and Economics Discussion Series 2001-37, Board of Governors of the Federal Reserve System (U.S.).
    7. 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.
    8. Jordi Molins & Eduard Vives, 2004. "Long range Ising model for credit risk modeling in homogeneous portfolios," Papers cond-mat/0401378, arXiv.org.
    9. Düllmann, Klaus & Trapp, Monika, 2004. "Systematic Risk in Recovery Rates: An Empirical Analysis of US Corporate Credit Exposures," Discussion Paper Series 2: Banking and Financial Studies 2004,02, Deutsche Bundesbank.
    10. Gürtler, Marc & Heithecker, Dirk, 2005. "Systematic credit cycle risk of financial collaterals: Modelling and evidence," Working Papers FW15V2, Technische Universität Braunschweig, Institute of Finance.
    11. Crouhy, Michel & Galai, Dan & Mark, Robert, 2000. "A comparative analysis of current credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 59-117, January.
    12. Acharya, Viral & Bharath, Sreedhar T & Srinivasan, Anand, 2003. "Understanding the Recovery Rates on Defaulted Securities," CEPR Discussion Papers 4098, C.E.P.R. Discussion Papers.
    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. Annalisa Di Clemente, 2013. "Considering the dependence between the credit loss severity and the probability of default in the estimate of portfolio credit risk: an experimental analysis," STUDI ECONOMICI, FrancoAngeli Editore, vol. 2013(109), pages 5-24.
    2. Maclachlan, Iain C, 2007. "An empirical study of corporate bond pricing with unobserved capital structure dynamics," MPRA Paper 28416, University Library of Munich, Germany.
    3. Gürtler, Marc & Heithecker, Dirk, 2005. "Systematic credit cycle risk of financial collaterals: Modelling and evidence," Working Papers FW15V2, Technische Universität Braunschweig, Institute of Finance.
    4. Pesaran, M. Hashem & Schuermann, Til & Treutler, Bjorn-Jakob & Weiner, Scott M., 2006. "Macroeconomic Dynamics and Credit Risk: A Global Perspective," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1211-1261, August.
    5. Georges Dionne & Geneviève Gauthier & Khemais Hammami & Mathieu Maurice & Jean‐Guy Simonato, 2010. "Default Risk in Corporate Yield Spreads," Financial Management, Financial Management Association International, vol. 39(2), pages 707-731, June.
    6. 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.
    7. Ambrocio, Gene & Jokivuolle, Esa, 2017. "Should bank capital requirements be less risk-sensitive because of credit constraints?," Bank of Finland Research Discussion Papers 10/2017, Bank of Finland.
    8. Maria Stefanova, 2012. "Recovery Risiko in der Kreditportfoliomodellierung," Springer Books, Springer, number 978-3-8349-4226-5, February.
    9. Gürtler, Marc & Heithecker, Dirk, 2004. "Modellkonsistente Bestimmung des LGD im IRB-Ansatz von Basel II," Working Papers FW08V3, Technische Universität Braunschweig, Institute of Finance.
    10. Giandomenico Piluso & Roberto Ricciuti, 2008. "Fiscal Policy and the Banking System in Italy. Have Taxes, Public Spending and Banks been Procyclical in the Long-Run?," CESifo Working Paper Series 2442, CESifo.
    11. Varotto, Simone, 2012. "Stress testing credit risk: The Great Depression scenario," Journal of Banking & Finance, Elsevier, vol. 36(12), pages 3133-3149.
    12. Mejra Festić, 2006. "Procyclicality of Financial and Real Sector in Transition Economies," Prague Economic Papers, Prague University of Economics and Business, vol. 2006(4), pages 315-349.
    13. 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.
    14. Abdelkader Derbali & Lamia Jamel, 2019. "Dependence of Default Probability and Recovery Rate in Structural Credit Risk Models: Case of Greek Banks," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(2), pages 711-733, June.
    15. Park, Yun W. & Bang, Doo Won, 2014. "Loss given default of residential mortgages in a low LTV regime: Role of foreclosure auction process and housing market cycles," Journal of Banking & Finance, Elsevier, vol. 39(C), pages 192-210.
    16. Sandra Eickmeier & Boris Hofmann & Andreas Worms, 2009. "Macroeconomic Fluctuations and Bank Lending: Evidence for Germany and the Euro Area," German Economic Review, Verein für Socialpolitik, vol. 10(2), pages 193-223, May.
    17. Kern, Markus & Rudolph, Bernd, 2001. "Comparative analysis of alternative credit risk models: An application on German middle market loan portfolios," CFS Working Paper Series 2001/03, Center for Financial Studies (CFS).
    18. Georges Dionne, 2003. "The Foundationsof Banks' Risk Regulation: A Review of Literature," THEMA Working Papers 2003-46, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    19. Meng-Jou Lu & Cathy Yi-Hsuan Chen & Wolfgang Karl Härdle, 2017. "Copula-based factor model for credit risk analysis," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 949-971, November.
    20. Helmut Elsinger & Alfred Lehar & Martin Summer, 2006. "Risk Assessment for Banking Systems," Management Science, INFORMS, vol. 52(9), pages 1301-1314, September.

    More about this item

    Keywords

    Credit risk; Quantitative risk management; Integration of market and credit risk; G21; E44; C15; C63;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    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:spr:comgts:v:5:y:2008:i:4:p:337-354. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.