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Conditional Certainty Equivalent

Author

Listed:
  • MARCO FRITTELLI

    (Department of Mathematics, University of Milan, via C. Saldini 50 Milan, 20134, Italy)

  • MARCO MAGGIS

    (Department of Mathematics, University of Milan, via C. Saldini 50 Milan, 20134, Italy)

Abstract

In a dynamic framework, we study the conditional version of the classical notion of certainty equivalent when the preferences are described by a stochastic dynamic utility u(x,t,ω). We introduce an appropriate mathematical setting, namely Orlicz spaces determined by the underlying preferences and thus provide a systematic method to go beyond the case of bounded random variables. Finally we prove a conditional version of the dual representation which is a crucial prerequisite for discussing the dynamics of certainty equivalents.

Suggested Citation

  • Marco Frittelli & Marco Maggis, 2011. "Conditional Certainty Equivalent," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 41-59.
    • Handle: RePEc:wsi:ijtafx:v:14:y:2011:i:01:n:s0219024911006255
    DOI: 10.1142/S0219024911006255
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    References listed on IDEAS

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    1. Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci & Luigi Montrucchio, 2008. "Risk Measures: Rationality and Diversification," Carlo Alberto Notebooks 100, Collegio Carlo Alberto.
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    Citations

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    Cited by:

    1. Samuel Drapeau & Asgar Jamneshan, 2014. "Conditional Preference Orders and their Numerical Representations," Papers 1410.5466, arXiv.org, revised Jan 2016.
    2. Elisa Mastrogiacomo & Emanuela Rosazza Gianin, 2015. "Portfolio Optimization with Quasiconvex Risk Measures," Mathematics of Operations Research, INFORMS, vol. 40(4), pages 1042-1059, October.
    3. Edoardo Berton & Alessandro Doldi & Marco Maggis, 2024. "On conditioning and consistency for nonlinear functionals," Papers 2401.09054, arXiv.org, revised May 2024.
    4. Frittelli Marco & Maggis Marco, 2014. "Complete duality for quasiconvex dynamic risk measures on modules of the Lp-type," Statistics & Risk Modeling, De Gruyter, vol. 31(1), pages 103-128, March.
    5. Drapeau, Samuel & Jamneshan, Asgar, 2016. "Conditional preference orders and their numerical representations," Journal of Mathematical Economics, Elsevier, vol. 63(C), pages 106-118.
    6. Hannes Hoffmann & Thilo Meyer-Brandis & Gregor Svindland, 2016. "Strongly Consistent Multivariate Conditional Risk Measures," Papers 1609.07903, arXiv.org.
    7. Massoomeh Rahsepar & Foivos Xanthos, 2020. "On the extension property of dilatation monotone risk measures," Papers 2002.11865, arXiv.org.
    8. Asgar Jamneshan & Michael Kupper & José Miguel Zapata-García, 2020. "Parameter-Dependent Stochastic Optimal Control in Finite Discrete Time," Journal of Optimization Theory and Applications, Springer, vol. 186(2), pages 644-666, August.
    9. Marco Maggis & Andrea Maran, 2018. "Stochastic Dynamic Utilities and Inter-Temporal Preferences," Papers 1803.05244, arXiv.org, revised Feb 2020.
    10. Alessandro Calvia & Emanuela Rosazza Gianin, 2019. "Risk measures and progressive enlargement of filtration: a BSDE approach," Papers 1904.13257, arXiv.org, revised Mar 2020.
    11. Giammarino, Flavia & Barrieu, Pauline, 2013. "Indifference pricing with uncertainty averse preferences," Journal of Mathematical Economics, Elsevier, vol. 49(1), pages 22-27.
    12. Centrone, Francesca & Rosazza Gianin, Emanuela, 2018. "Capital allocation à la Aumann–Shapley for non-differentiable risk measures," European Journal of Operational Research, Elsevier, vol. 267(2), pages 667-675.
    13. Giulio Principi & Fabio Maccheroni, 2022. "Conditional divergence risk measures," Papers 2211.04592, arXiv.org.
    14. Nicole El Karoui & Mohamed Mrad, 2013. "An Exact Connection between two Solvable SDEs and a Nonlinear Utility Stochastic PDE," Post-Print hal-00477381, HAL.

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