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Risk measures for processes and BSDEs

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  • Irina Penner
  • Anthony Réveillac

Abstract

The paper analyzes risk assessment for cash flow processes in continuous time. We combine the framework of convex risk measures for processes with a decomposition result for optional and predictable measures to provide a systematic approach to the issues of model ambiguity and uncertainty about the time value of money. We also establish a link between risk measures for processes and BSDEs. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Irina Penner & Anthony Réveillac, 2015. "Risk measures for processes and BSDEs," Finance and Stochastics, Springer, vol. 19(1), pages 23-66, January.
    • Handle: RePEc:spr:finsto:v:19:y:2015:i:1:p:23-66
    DOI: 10.1007/s00780-014-0243-x
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    References listed on IDEAS

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    Cited by:

    1. Ji, Ronglin & Shi, Xuejun & Wang, Shijie & Zhou, Jinming, 2019. "Dynamic risk measures for processes via backward stochastic differential equations," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 43-50.
    2. Fei Sun & Jingchao Li & Jieming Zhou, 2018. "Dynamic risk measures with fluctuation of market volatility under Bochne-Lebesgue space," Papers 1806.01166, arXiv.org, revised Mar 2024.

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    More about this item

    Keywords

    Convex risk measures for processes; Discounting ambiguity; Model ambiguity; Cash subadditivity; Decomposition of optional measures; BSDEs; 60G07; 91B30; 91B16; 60H10; 60G40; D81;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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