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Processus de risque : modélisation de la dépendance et évaluation du risque sous des contraintes de convexité

Abstract : In this thesis we focus on two different problems which have as common point the contribution to the modeling and to the risk management in insurance. In the first research theme, we are interested by the modeling of the dependence in insurance. In particular we propose an extension to model with common factor. In the second research theme we consider the class of nonincreasing discrete distributions and we are interested in studying the effect of additional constraint of convexity on the convex extrema. Some applications in ruin theory motivate our interest to this subject. The first part of this thesis is concerned with factor models for the modeling of the dependency in insurance. An interesting property of these models is that the random variables are conditionally independent with respect to a factor. We propose a new model in which the conditioning is with respect to the entire memory of the factor. In this case we give some mixing properties of risk process under conditions related to the mixing properties of the factor process and to the conditional mixing risk process. The law of the sum of random variables has a great interest in actuarial science. Therefore we give some conditions under which the law of the aggregated process converges to a normal distribution. In the second part of the thesis we consider the class of discrete distributions whose probability mass functions (p.m.f.) are nonincreasing on a finite support. Convex extrema in that class of distributions are well-known. Our purpose is to point out how additional shape constraints of convexity type modify these extrema. Two cases are considered : the p.m.f. is globally convex on N or it is convex only from a given positive point. The corresponding convex extrema are derived by using a simple crossing property between two distributions. Several applications to some ruin problems are presented for illustration
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Manel Kacem. Processus de risque : modélisation de la dépendance et évaluation du risque sous des contraintes de convexité. Mathématiques générales [math.GM]. Université Claude Bernard - Lyon I, 2013. Français. ⟨NNT : 2013LYO10051⟩. ⟨tel-01085025⟩

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