IDEAS home Printed from https://ideas.repec.org/p/zbw/thkivw/284399.html
   My bibliography  Save this paper

Aggregation in einem Risikoportfolio mit Abhängigkeitsstruktur

Author

Listed:
  • Knobloch, Ralf

Abstract

Unternehmen sehen sich üblicherweise den unterschiedlichsten operativen und strategischen Risiken ausgesetzt. Daher ist das Risikoportfolio eines Unternehmens aus Sicht des betriebswirtschaftlichen Risikomanagement i.d.R. sehr inhomogen bezüglich der verwendeten Verteilungsmodelle. Neben der Bewertung der Einzelrisiken ist es die Aufgabe des quantitativen Risikomanagements, alle Einzelrisiken in einer Risikokennzahl (z.B. Value at Risk oder Expected Shortfall) zu aggregieren. Dazu werden Szenarien (mit einer Monte-Carlo-Simulation) simuliert, so dass die Verteilung des Gesamtrisikos mit Risikokennzahlen aggregiert und analysiert werden kann. Dabei muss zusätzlich die Abhängigkeitsstruktur der Einzelrisiken modelliert werden. Ein möglicher Ansatz zur Modellierung der Abhängigkeitsstruktur ist die Vorgabe einer Korrelationsmatrix. Der vorliegende Artikel beschäftigt anhand von Beispielen zum einen mit Konzepten und Methoden einer solchen Modellierung und zum anderen mit den Schwierigkeiten, die damit verbunden sind. Es zeigt sich, dass man bei der Wahl einer Korrelationsmatrix verschiedene Einschränkungen zu beachten hat. Ferner kann es zu einer vorgegebenen Korrelationsmatrix mehrere passende gemeinsame Verteilungen der Einzelrisken geben. Dies hat zur Folge, dass die Aggregation der Einzelrisiken in einer Risikokennzahl aus mathematischer Sicht nicht eindeutig ist.

Suggested Citation

  • Knobloch, Ralf, 2024. "Aggregation in einem Risikoportfolio mit Abhängigkeitsstruktur," Forschung am ivwKöln 2/2024, Technische Hochschule Köln – University of Applied Sciences, Institute for Insurance Studies.
  • Handle: RePEc:zbw:thkivw:284399
    DOI: 10.57684/COS-1234
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/284399/1/1882377060.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.57684/COS-1234?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
    ---><---

    References listed on IDEAS

    as
    1. Dhaene, Jan & Goovaerts, Marc J., 1996. "Dependency of Risks and Stop-Loss Order1," ASTIN Bulletin, Cambridge University Press, vol. 26(2), pages 201-212, 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. Goovaerts, M. J. & Dhaene, J., 1999. "Supermodular ordering and stochastic annuities," Insurance: Mathematics and Economics, Elsevier, vol. 24(3), pages 281-290, May.
    2. Mansour Shrahili & Mohamed Kayid, 2023. "Stochastic Orderings of the Idle Time of Inactive Standby Systems," Mathematics, MDPI, vol. 11(20), pages 1-21, October.
    3. Yeo, Keng Leong & Valdez, Emiliano A., 2006. "Claim dependence with common effects in credibility models," Insurance: Mathematics and Economics, Elsevier, vol. 38(3), pages 609-629, June.
    4. Frostig, Esther, 2006. "On risk dependence and mrl ordering," Statistics & Probability Letters, Elsevier, vol. 76(3), pages 231-243, February.
    5. Kaas, Rob & Tang, Qihe, 2005. "A large deviation result for aggregate claims with dependent claim occurrences," Insurance: Mathematics and Economics, Elsevier, vol. 36(3), pages 251-259, June.
    6. Kaas, Rob & Laeven, Roger J.A. & Nelsen, Roger B., 2009. "Worst VaR scenarios with given marginals and measures of association," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 146-158, April.
    7. Albers, Willem, 1999. "Stop-loss premiums under dependence," Insurance: Mathematics and Economics, Elsevier, vol. 24(3), pages 173-185, May.
    8. Yi, Zhang & Weng, Chengguo, 2006. "On the correlation order," Statistics & Probability Letters, Elsevier, vol. 76(13), pages 1410-1416, July.
    9. Dhaene, Jan & Denuit, Michel, 1999. "The safest dependence structure among risks," Insurance: Mathematics and Economics, Elsevier, vol. 25(1), pages 11-21, September.
    10. Lu, Tong-Yu & Yi, Zhang, 2004. "Generalized correlation order and stop-loss order," Insurance: Mathematics and Economics, Elsevier, vol. 35(1), pages 69-76, August.
    11. Dhaene, J. & Denuit, M. & Goovaerts, M. J. & Kaas, R. & Vyncke, D., 2002. "The concept of comonotonicity in actuarial science and finance: theory," Insurance: Mathematics and Economics, Elsevier, vol. 31(1), pages 3-33, August.
    12. Cheung, Ka Chun & Lo, Ambrose, 2013. "General lower bounds on convex functionals of aggregate sums," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 884-896.
    13. Tavin, Bertrand, 2015. "Detection of arbitrage in a market with multi-asset derivatives and known risk-neutral marginals," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 158-178.
    14. Li, Xiaohu & You, Yinping, 2012. "On allocation of upper limits and deductibles with dependent frequencies and comonotonic severities," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 423-429.
    15. Irmina Czarna & Zbigniew Palmowski, 2009. "De Finetti's dividend problem and impulse control for a two-dimensional insurance risk process," Papers 0906.2100, arXiv.org, revised Feb 2011.
    16. Maria Mercè Claramunt & Maite Màrmol, 2020. "Refundable deductible insurance," Working Papers hal-02909299, HAL.
    17. Jorge Navarro & Franco Pellerey & Miguel A. Sordo, 2020. "Weak Dependence Notions and Their Mutual Relationships," Mathematics, MDPI, vol. 9(1), pages 1-27, December.
    18. Dhaene, Jan & Laeven, Roger J.A. & Zhang, Yiying, 2022. "Systemic risk: Conditional distortion risk measures," Insurance: Mathematics and Economics, Elsevier, vol. 102(C), pages 126-145.
    19. Genest, Christian & Marceau, Étienne & Mesfioui, Mhamed, 2002. "Upper stop-loss bounds for sums of possibly dependent risks with given means and variances," Statistics & Probability Letters, Elsevier, vol. 57(1), pages 33-41, March.
    20. Chan, Wai-Sum & Yang, Hailiang & Zhang, Lianzeng, 2003. "Some results on ruin probabilities in a two-dimensional risk model," Insurance: Mathematics and Economics, Elsevier, vol. 32(3), pages 345-358, July.

    More about this item

    Keywords

    Quantitatives Risikomanagement; Value at Risk; Korrelationsmatrix; Risikoaggregation; Fréchet-Hoeffding-Schranken; Quantitative Risk Management; Value at Risk; Correlation Matrix; Risk Aggregation; Fréchet-Hoeffding-Bounds;
    All these keywords.

    JEL classification:

    • G - Financial Economics
    • G2 - Financial Economics - - Financial Institutions and Services
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:thkivw:284399. 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/fwfhkde.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.