VALUATIONS AND DYNAMIC CONVEX RISK MEASURES

By A. Jobert, L. Rogers. 2007

128 citations recorded by the source corpus.

This paper approaches the definition and properties of dynamic convex risk measures through the notion of a family of concave valuation operators satisfying certain simple and credible axioms. Exploring these in the simplest context of a finite time set and finite sample space, we find natural risk‐transfer and time‐consistency properties for a firm seeking to spread its risk across a group of subsidiaries.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/b7825559d72a77f1fddc3a753900fbb82fc9fe15

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In Economics and Econometrics

In Finance

In Management Science and Operations Research

Citations in the corpus

Dynamic risk measures (2010, background): “tion consistency, which require that if some position is accepted (or rejected) for any scenario tomorrow, it should be already accepted (or rejected) today; see [4, 35, 33, 9, 32]. As pointed out in [25, 19], risk assessment in the multi-period setting should also account for uncertainty about the ”
Risk-averse dynamic programming for Markov decision processes (2010, background): “Another important property of a dynamic risk measure is the local property, discussed in detail in [8,25,28].”
Mean-Variance Policy for Discrete-time Cone Constrained Markets: The Consistency in Efficiency and Minimum-Variance Signed Supermartingale Measure (2014, unknown): “ the truncated time horizon. As time consistency (or dynamic consistency) is a basic requirement for dynamic risk measures (see Rosazza Gianin (2006), Boda and Filar (2006), Artzner et al. (2007) and Jobert and Rogers (2008)), all the appropriate dynamic risk measures should necessarily possess cert”
A general theory of finite state Backward Stochastic Difference Equations (2008, background): “In the same discrete time, finite state context as considered here, [9] considers this structure under the name of a ‘concave valuation operator’.”
DYNAMIC INDIFFERENCE VALUATION VIA CONVEX RISK MEASURES (2007, background): “…for dynamic MCUFs which are given by backward stochastic differential equations (BSDEs), and Larsen, Pirvu, Shreve and Tütüncü (2005) treat indifference valuation for a special t. Jobert and Rogers (2008) study several of the above issues in finite discrete time over a finite probability space.”