IDEAS home Printed from https://ideas.repec.org/p/han/dpaper/dp-468.html
   My bibliography  Save this paper

Modellrisiko = Spezifikation + Validierung

Author

Listed:
  • Stahl, Gerhard
  • Sibbertsen, Philipp
  • Bertram, Philip

Abstract

Als Teil des operationellen Risikos stellt das Modellrisiko eine wichtige Komponente für die Risikoermittlung bei Finanzinstitutionen dar. Da letztere z.B. bei der Tarifierung und Bepreisung von Derivaten bzw. Portfolien oder bei der Markt- und Kreditrisikoberechnung auf stochastische Modelle zurückgreifen, kann die Spezifikation falscher Modelle zu einer erheblichen Fehlkalkulation des Risikos führen. Aufbauend auf einer prozessorientierten Definition von Modellrisiko werden Beispiele des Auftretens von Modellrisiko in der aktuariellen Praxis angeführt. Dies wird anhand des Market Consistent Embedded Value und des Wilkie-Modells illustriert. Bei der Schätzung, Spezifikation und Validierung von letzterem verdeutlichen wir das Zusammenspiel dieser drei Komponenten mit dem Modellrisiko. Hierzu wird das Wilkie-Modell im Rahmen von multivariaten Zeitreihenmodellen dargestellt und analysiert.

Suggested Citation

  • Stahl, Gerhard & Sibbertsen, Philipp & Bertram, Philip, 2011. "Modellrisiko = Spezifikation + Validierung," Hannover Economic Papers (HEP) dp-468, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    • Handle: RePEc:han:dpaper:dp-468
    as

    Download full text from publisher

    File URL: http://diskussionspapiere.wiwi.uni-hannover.de/pdf_bib/dp-468.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Helmut Lütkepohl, 2005. "New Introduction to Multiple Time Series Analysis," Springer Books, Springer, number 978-3-540-27752-1, June.
    2. Bénédicte Vidaillet & V. d'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    3. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809.
    4. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    5. Kai Detlefsen & Wolfgang Härdle, 2006. "Calibration Risk for Exotic Options," SFB 649 Discussion Papers SFB649DP2006-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Sibbertsen, Philipp & Stahl, Gerhard & Luedtke, Corinna, 2008. "Measuring Model Risk," Hannover Economic Papers (HEP) dp-409, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    7. Wilkie, A.D., 1995. "More on a Stochastic Asset Model for Actuarial Use," British Actuarial Journal, Cambridge University Press, vol. 1(5), pages 777-964, December.
    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. Helmut Lütkepohl, 2013. "Vector autoregressive models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 6, pages 139-164, Edward Elgar Publishing.
    2. Matteo Fragetta & Emanuel Gasteiger, 2014. "Fiscal Foresight, Limited Information and the Effects of Government Spending Shocks," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(5), pages 667-692, October.
    3. Koo, Tay T.R. & Tan, David T. & Duval, David Timothy, 2013. "Direct air transport and demand interaction: A vector error-correction model approach," Journal of Air Transport Management, Elsevier, vol. 28(C), pages 14-19.
    4. Enzo Weber, 2006. "British Interest Rate Convergence Between The Us And Europe: A Recursive Cointegration Analysis," The IUP Journal of Monetary Economics, IUP Publications, vol. 0(4), pages 29-47, November.
    5. Woźniak, Tomasz, 2015. "Testing causality between two vectors in multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 876-894.
    6. Nick, Sebastian, 2013. "Price Formation and Intertemporal Arbitrage within a Low-Liquidity Framework: Empirical Evidence from European Natural Gas Markets," EWI Working Papers 2013-14, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    7. Tomasz Wozniak, 2012. "Granger-causal analysis of VARMA-GARCH models," Economics Working Papers ECO2012/19, European University Institute.
    8. Elena Argentesi & Helmut Lütkepohl & Massimo Motta, 2010. "Acquisition of Information and Share Prices: An Empirical Investigation of Cognitive Dissonance," German Economic Review, Verein für Socialpolitik, vol. 11(3), pages 381-396, August.
    9. Emirmahmutoglu, Furkan & Kose, Nezir, 2011. "Testing for Granger causality in heterogeneous mixed panels," Economic Modelling, Elsevier, vol. 28(3), pages 870-876, May.
    10. Helmut Luetkepohl, 2007. "Econometric Analysis with Vector Autoregressive Models," Economics Working Papers ECO2007/11, European University Institute.
    11. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911.
    12. Abdulnasser Hatemi-J, 2012. "Asymmetric causality tests with an application," Empirical Economics, Springer, vol. 43(1), pages 447-456, August.
    13. Robert Lehmann & Antje Weyh, 2016. "Forecasting Employment in Europe: Are Survey Results Helpful?," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 12(1), pages 81-117, September.
    14. Cubadda, Gianluca & Hecq, Alain & Palm, Franz C., 2009. "Studying co-movements in large multivariate data prior to multivariate modelling," Journal of Econometrics, Elsevier, vol. 148(1), pages 25-35, January.
    15. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    16. Mauro Costantini & Ulrich Gunter & Robert M. Kunst, 2017. "Forecast Combinations in a DSGE‐VAR Lab," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(3), pages 305-324, April.
    17. Ana María Iregui & Jesús Otero, 2013. "A Spatiotemporal Analysis of Agricultural Prices: An Application to Colombian Data," Agribusiness, John Wiley & Sons, Ltd., vol. 29(4), pages 497-508, September.
    18. Tomasz Woźniak, 2016. "Bayesian Vector Autoregressions," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 49(3), pages 365-380, September.
    19. Cudjoe, Godsway & Breisinger, Clemens & Diao, Xinshen, 2010. "Local impacts of a global crisis: Food price transmission, consumer welfare and poverty in Ghana," Food Policy, Elsevier, vol. 35(4), pages 294-302, August.
    20. Kühl, Michael, 2007. "Cointegration in the foreign exchange market and market efficiency since the introduction of the Euro: Evidence based on bivariate cointegration analyses," University of Göttingen Working Papers in Economics 68, University of Goettingen, Department of Economics.

    More about this item

    Keywords

    Modellrisiko; multivariate Zeitreihenmodelle; Wilkie-Modell;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:han:dpaper:dp-468. 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: Heidrich, Christian (email available below). General contact details of provider: https://edirc.repec.org/data/fwhande.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.