scholarly journals Polynomial Series Expansions and Moment Approximations for Conditional Mean Risk Sharing of Insurance Losses

Author(s):  
Michel Denuit ◽  
Christian Y. Robert
2020 ◽  
Vol 50 (3) ◽  
pp. 1093-1122 ◽  
Author(s):  
Michel Denuit ◽  
Christian Y. Robert

AbstractWe consider the conditional mean risk allocation for an insurance pool, as defined by Denuit and Dhaene (2012). Precisely, we study the asymptotic behavior of the respective relative contributions of the participants as the total loss of the pool tends to infinity. The numerical illustration in Denuit (2019) suggests that the application of the conditional mean risk sharing rule may produce a linear sharing in the tail of the total loss distribution. This paper studies the validity of this empirical finding in the class of compound Panjer–Katz sums consisting of compound Binomial, compound Poisson, and compound Negative Binomial sums with either Gamma or Pareto severities. It is demonstrated that such a behavior does not hold in general since one term may dominate the other ones conditional of large total loss.


2021 ◽  
pp. 1-27
Author(s):  
Michel Denuit ◽  
Christian Y. Robert

Abstract Conditional mean risk sharing appears to be effective to distribute total losses amongst participants within an insurance pool. This paper develops analytical results for this allocation rule in the individual risk model with dependence induced by the respective position within a graph. Precisely, losses are modelled by zero-augmented random variables whose joint occurrence distribution and individual claim amount distributions are based on network structures and can be characterised by graphical models. The Ising model is adopted for occurrences and loss amounts obey decomposable graphical models that are specific to each participant. Two graphical structures are thus used: the first one to describe the contagion amongst member units within the insurance pool and the second one to model the spread of losses inside each participating unit. The proposed individual risk model is typically useful for modelling operational risks, catastrophic risks or cybersecurity risks.


2019 ◽  
Vol 49 (03) ◽  
pp. 591-617 ◽  
Author(s):  
Michel Denuit

AbstractUsing risk-reducing properties of conditional expectations with respect to convex order, Denuit and Dhaene [Denuit, M. and Dhaene, J. (2012). Insurance: Mathematics and Economics 51, 265–270] proposed the conditional mean risk sharing rule to allocate the total risk among participants to an insurance pool. This paper relates the conditional mean risk sharing rule to the size-biased transform when pooled risks are independent. A representation formula is first derived for the conditional expectation of an individual risk given the aggregate loss. This formula is then exploited to obtain explicit expressions for the contributions to the pool when losses are modeled by compound Poisson sums, compound Negative Binomial sums, and compound Binomial sums, to which Panjer recursion applies. Simple formulas are obtained when claim severities are homogeneous. A couple of applications are considered: first, to a peer-to-peer insurance scheme where participants share the first layer of their respective risks while the higher layer is ceded to a (re)insurer; second, to survivor credits to be shared among surviving participants in tontine schemes.


2010 ◽  
Author(s):  
M. A. Saleem ◽  
M. Abul-Ez ◽  
M. Zayed ◽  
Theodore E. Simos ◽  
George Psihoyios ◽  
...  

2011 ◽  
Vol 35 (2) ◽  
pp. 134-143 ◽  
Author(s):  
M.A. Saleem ◽  
M. Abul-Ez ◽  
M. Zayed

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