On a risk model with dependence between interclaim arrivals and claim sizes

By Mathieu Boudreault, Hélène Cossette, David Landriault, É. Marceau. 2006

200 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/f76dc0315ce5b7a1934b9bf24b265f58025bbcd7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. David Landriault
2. Andrei L. Badescu
3. Eric C. K. Cheung
4. Hélène Cossette
5. É. Marceau
6. Jae-Kyung Woo
7. Fouad Marri
8. Alexandru V. Asimit

In Finance

1. Hélène Cossette
2. É. Marceau
3. Mathieu Bargès
4. Stéphane Loisel
5. Alexandru V. Asimit
6. Eric C. K. Cheung
7. Fouad Marri
8. Gordon E. Willmot

In Management Science and Operations Research

1. Eric C. K. Cheung
2. David Landriault
3. Hélène Cossette
4. É. Marceau
5. Andrei L. Badescu
6. Jae-Kyung Woo
7. Mathieu Bargès
8. Stéphane Loisel

Citations in the corpus

• Extremes on the discounted aggregate claims in a time dependent risk model (2010, background): “Another type of dependence structure that assume that the claims size distribution is given by the previous inter-claim time distribution is considered by Boudreault et al. (2006). The present work is not meant to be an exhaustive treatment on all possible dependence structures, but rather an attemp”
• On the Moments of Aggregate Discounted Claims with Dependence Introduced by a FGM Copula (2011, background): “Conversely to Albrecher and Boxma (2004), Boudreault et al. (2006) assumed that if an interclaim time is greater than a certain threshold then the parameters of the distribution of the next claim amount is modified.”
• Structural properties of Gerber-Shiu functions in dependent Sparre Andersen models (2010, background): “Boudreault et al. (2006) considered the dependent Poisson riskmodelwith K(t) = 1−e−λt and Pt(y) = e−βt P (1)(y) + (1 − e−βt)P (2)(y) where P (1)(y) and P (2)(y) are ‘‘usual’’ and ‘‘severe’’ claim size distribution functions, respectively.”
• Dependent Risk Models with Bivariate Phase-Type Distributions (2009, background): “For the case ∆ = ∅, the relations (7) to (15) remains valid by simply letting t0 = 0, t1 = 0 and t2 = 0 in (7), (10) and (14).”
• Analysis of ruin measures for the classical compound Poisson risk model with dependence (2010, background): “( 2006 ) propose an extension to the classical compound Poisson risk model assuming a dependence structure for ( X , W) , in which the distribution of the next claim amount is defined in terms of the time elapsed since the last claim.”