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Asymptotically Stable Dynamic Risk Assessments

Author

Listed:
  • KARL-THEODOR EISELE

    (LaRGE Research Center, Université de Strasbourg)

  • MICHAEL KUPPER

Abstract

In this paper asymptotically stable risk assessments are studied. They are characterized by not being sensitive with respect to huge additional capital in the very far future. Under the additional hypothesis of being locally continuous from below, these risk assessments are exactly those which allow a robust representation with so-called local test probabilities having a support with finite time horizon. Time-consistent risk assessments can be constructed by composing a sequence of generators. We give several conditions for the generators such that the resulting risk assessments are indeed asymptotically stable.

Suggested Citation

  • Karl-Theodor Eisele & Michael Kupper, 2013. "Asymptotically Stable Dynamic Risk Assessments," Working Papers of LaRGE Research Center 2013-04, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.
    • Handle: RePEc:lar:wpaper:2013-04
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    File URL: http://ifs.u-strasbg.fr/large/publications/2013/2013-04.pdf
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    References listed on IDEAS

    as
    1. Marco Frittelli & Giacomo Scandolo, 2006. "Risk Measures And Capital Requirements For Processes," Mathematical Finance, Wiley Blackwell, vol. 16(4), pages 589-612, October.
    2. Damir Filipović & Michael Kupper, 2008. "Equilibrium Prices For Monetary Utility Functions," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 11(03), pages 325-343.
    3. A. Jobert & L. C. G. Rogers, 2008. "Valuations And Dynamic Convex Risk Measures," Mathematical Finance, Wiley Blackwell, vol. 18(1), pages 1-22, January.
    4. Patrick Cheridito & Michael Kupper, 2011. "Composition Of Time-Consistent Dynamic Monetary Risk Measures In Discrete Time," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 137-162.
    5. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    asymptotic stability of risk assessments; construction by generators; local test probabilities; robust representation; time-consistency.;
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