Another look at risk apportionment
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Publication:387334
DOI10.1016/j.jmateco.2013.04.007zbMath1282.91148OpenAlexW2080076391MaRDI QIDQ387334
Béatrice Rey, Michel M. Denuit
Publication date: 20 December 2013
Published in: Journal of Mathematical Economics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmateco.2013.04.007
expected utilitystochastic dominancehigher-order risk apportionmenthigher-order risk aversionwealth effect
Related Items (4)
On ambiguity apportionment ⋮ New results for additive and multiplicative risk apportionment ⋮ Preserving the Rothschild-Stiglitz type increase in risk with background risk: a characterization ⋮ Risk apportionment and multiply monotone targets
Cites Work
- On relative and partial risk attitudes: theory and implications
- Mixed risk aversion and preference for risk disaggregation: a story of moments
- Multiplicative risk apportionment
- Some consequences of correlation aversion in decision science
- Apportioning of risks via stochastic dominance
- The values of relative risk aversion and prudence: a context-free interpretation
- A class of bivariate stochastic orderings, with applications in actuarial sciences
- Extremal generators and extremal distributions for the continuous \(s\)-convex stochastic orderings
- Orthant orderings of discrete random vectors
- Some new classes of stochastic order relations among arithmetic random variables, with applications in actuarial sciences
- Moment characterization of higher-order risk preferences
- Risk apportionment via bivariate stochastic dominance
- Prudence, temperance, edginess, and risk apportionment as decreasing sensitivity to detrimental changes
- Stochastic Orderings of Convex/Concave-Type on an Arbitrary Grid
- Multiattribute Utility Satisfying a Preference for Combining Good with Bad
- Multivariate Risk Aversion, Utility Independence and Separable Utility Functions
- Stochastic Orderings of Convex-Type for Discrete Bivariate Risks
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