2002
DOI: 10.1016/s0167-6687(02)00135-x
|View full text |Cite
|
Sign up to set email alerts
|

The concept of comonotonicity in actuarial science and finance: applications

Abstract: In an insurance context, one is often interested in the distribution function of a sum of random variables. Such a sum appears when considering the aggregate claims of an insurance portfolio over a certain reference period. It also appears when considering discounted payments related to a single policy or a portfolio at different future points in time. The assumption of mutual independence between the components of the sum is very convenient from a computational point of view, but sometimes not realistic. In D… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

4
163
0

Year Published

2004
2004
2017
2017

Publication Types

Select...
5
5

Relationship

0
10

Authors

Journals

citations
Cited by 305 publications
(169 citation statements)
references
References 16 publications
(10 reference statements)
4
163
0
Order By: Relevance
“…The reason is that the Jamshidian decomposition cannot be applied. An alternative could be the comonotonicity approach of Dhaene et al (2002a) and Dhaene et al (2002b), which results in a lower and upper bound for the bond put option. As an alternative for a two-factor model, a model with a jump component can be considered.…”
Section: Discussionmentioning
confidence: 99%
“…The reason is that the Jamshidian decomposition cannot be applied. An alternative could be the comonotonicity approach of Dhaene et al (2002a) and Dhaene et al (2002b), which results in a lower and upper bound for the bond put option. As an alternative for a two-factor model, a model with a jump component can be considered.…”
Section: Discussionmentioning
confidence: 99%
“…Next we study the dependence in a discounted discrete annuity as discussed in Dhaene et al (2002b). Example 4.2 Consider a series of deterministic payments α 1 , α 2 , .…”
Section: Estimationmentioning
confidence: 99%
“…However, it is impossible to determine the distribution function of S analytically in closed form, because S is a sum of non-independent lognormal variables. We will use the convex upper and lower bounds for S satisfying S ≤ cx S ≤ cx S c as introduced in Dhaene et al (2002b):…”
Section: Problem Descriptionmentioning
confidence: 99%