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- Q5155190 subject Q7451992.
- Q5155190 subject Q8425180.
- Q5155190 subject Q8817194.
- Q5155190 abstract "In probability theory, comonotonicity mainly refers to the perfect positive dependence between the components of a random vector, essentially saying that they can be represented as increasing functions of a single random variable. In two dimensions it is also possible to consider perfect negative dependence, which is called countermonotonicity. Comonotonicity is also related to the comonotonic additivity of the Choquet integral.The concept of comonotonicity has applications in financial risk management and actuarial science, see e.g. Dhaene et al. (2002a) and Dhaene et al. (2002b). In particular, the sum of the components X1 + X2 + · · · + Xn is the riskiest if the joint probability distribution of the random vector (X1, X2, . . . , Xn) is comonotonic. Furthermore, the α-quantile of the sum equals of the sum of the α-quantiles of its components, hence comonotonic random variables are quantile-additive. In practical risk management terms it means that there is minimal (or eventually no) variance reduction from diversification.For extensions of comonotonicity, see Jouini & Napp (2004) and Puccetti & Scarsini (2010).".
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- Q5155190 wikiPageExternalLink MED090320-Scarsini.pdf.
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- Q5155190 wikiPageWikiLink Q7451992.
- Q5155190 wikiPageWikiLink Q8425180.
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- Q5155190 wikiPageWikiLink Q8817194.
- Q5155190 comment "In probability theory, comonotonicity mainly refers to the perfect positive dependence between the components of a random vector, essentially saying that they can be represented as increasing functions of a single random variable. In two dimensions it is also possible to consider perfect negative dependence, which is called countermonotonicity.".
- Q5155190 label "Comonotonicity".