IDEAS home Printed from https://ideas.repec.org/a/spr/astaws/v5y2011i1p59-76.html
   My bibliography  Save this article

Risikomaßzahlen für Kreditportfoliotranchen

Author

Listed:
  • Daniel Tillich

Abstract

There is a multitude of measures to evaluate the tranches of a structured credit portfolio. One problem is that for each concept there exists a variety of different terms. Furthermore, some of these terms are used for different measures. For this reason, this paper aims to catalog the terms used and to define a term that is appropriate and unique. Additionally, characteristic properties for each measure are collected. It turns out that in principle two of the considered measures suffice to evaluate the tranches of a portfolio. Copyright Springer 2011

Suggested Citation

  • Daniel Tillich, 2011. "Risikomaßzahlen für Kreditportfoliotranchen," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 5(1), pages 59-76, March.
  • Handle: RePEc:spr:astaws:v:5:y:2011:i:1:p:59-76
    DOI: 10.1007/s11943-011-0095-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11943-011-0095-1
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11943-011-0095-1?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. Jean-Paul Laurent & Jon Gregory, 2005. "Basket default swaps, CDOs and factor copulas," Post-Print hal-03679517, HAL.
    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. Hans Brachinger, 2011. "Vorwort des Herausgebers," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 4(4), pages 249-251, January.

    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. Xiao, Tim, 2018. "The Valuation of Credit Default Swap with Counterparty Risk and Collateralization," EconStor Preprints 203447, ZBW - Leibniz Information Centre for Economics.
    2. Xiao,Tim, 2018. "Pricing Financial Derivatives Subject to Multilateral Credit Risk and Collateralization," EconStor Preprints 202075, ZBW - Leibniz Information Centre for Economics.
    3. Dong Hwan Oh & Andrew J. Patton, 2017. "Modeling Dependence in High Dimensions With Factor Copulas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 139-154, January.
    4. Nneka Umeorah & Phillip Mashele & Matthias Ehrhardt, 2021. "Pricing basket default swaps using quasi-analytic techniques," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 241-267, June.
    5. Puneet Pasricha & Dharmaraja Selvamuthu & Selvaraju Natarajan, 2022. "A contagion process with self-exciting jumps in credit risk applications," Papers 2202.12946, arXiv.org.
    6. Alan White, 2018. "Pricing Credit Default Swap Subject to Counterparty Risk and Collateralization," Working Papers hal-01739310, HAL.
    7. Fermanian, Jean-David, 2014. "The limits of granularity adjustments," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 9-25.
    8. Ascheberg, Marius & Bick, Björn & Kraft, Holger, 2013. "Hedging structured credit products during the credit crisis: A horse race of 10 models," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1687-1705.
    9. Xiao, Tim, 2013. "The Impact of Default Dependency and Collateralization on Asset Pricing and Credit Risk Modeling," MPRA Paper 47136, University Library of Munich, Germany.
    10. Cousin, Areski & Laurent, Jean-Paul, 2008. "Comparison results for exchangeable credit risk portfolios," Insurance: Mathematics and Economics, Elsevier, vol. 42(3), pages 1118-1127, June.
    11. Chen, Jianli & Liu, Zhen & Li, Shenghong, 2014. "Mixed copula model with stochastic correlation for CDO pricing," Economic Modelling, Elsevier, vol. 40(C), pages 167-174.
    12. Smith, Michael Stanley, 2023. "Implicit Copulas: An Overview," Econometrics and Statistics, Elsevier, vol. 28(C), pages 81-104.
    13. Jean-David Fermanian & Olivier Vigneron, 2012. "On break-even correlation: the way to price structured credit derivatives by replication," Papers 1204.2251, arXiv.org.
    14. Gregory Connor & Lisa R. Goldberg & Robert A. Korajczyk, 2010. "Portfolio Risk Analysis," Economics Books, Princeton University Press, edition 1, number 9224.
    15. Cyril Bénézet & Emmanuel Gobet & Rodrigo Targino, 2023. "Transform MCMC Schemes for Sampling Intractable Factor Copula Models," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-41, March.
    16. Kijima, Masaaki & Motomiya, Shin-ichi & Suzuki, Yoichi, 2010. "Pricing of CDOs based on the multivariate Wang transform," Journal of Economic Dynamics and Control, Elsevier, vol. 34(11), pages 2245-2258, November.
    17. Broer, Tobias & Kero, Afroditi, 2021. "Collateralization and asset price bubbles when investors disagree about risk," Journal of Banking & Finance, Elsevier, vol. 128(C).
    18. Frahm, Gabriel & Junker, Markus & Schmidt, Rafael, 2005. "Estimating the tail-dependence coefficient: Properties and pitfalls," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 80-100, August.
    19. Broer, Tobias, 2016. "Securitisation Bubbles: Structured finance with disagreement about default correlations," CEPR Discussion Papers 11145, C.E.P.R. Discussion Papers.
    20. Tim, Xiao, 2019. "Pricing Credit Default Swap Subject to Counterparty Risk and Collateralization," MPRA Paper 94701, University Library of Munich, Germany.

    More about this item

    Keywords

    Risikomessung; Kreditportfolio; Tranche; G32; G24; G13; Risk; Measurement; Tranche; Credit portfolio;
    All these keywords.

    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    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:astaws:v:5:y:2011:i:1:p:59-76. 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.