459 research outputs found

    Some positive dependence notions, with applications in actuarial sciences.

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    The paper is devoted to the study of several notions of positive dependence among risks, namely association, linear positive quadrant dependence, positive orthant dependence and conditional increasingness in sequence. Various examples illustrate the usefulness of these notions in an actuarial context.Dependence; Applications; Actuarial; Science;

    Does positive dependence between individual risks increase stop-loss premiums?.

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    Actuaries intuitively feel that positive correlations between individual risks reveal a more dangerous situation compared to independence. The purpose of this short note is to formalize this natural idea. Specifically, it is shown that the sum of risks exhibiting a weak form of dependence known as positive cumulative dependence is larger in convex order than the corresponding sum under the theoretical independence assumption.Dependence; Risk;

    Dependencies in multi-life statusses.

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    The usual assumption of independence of the remaining life times involved in joint-life and last survivor statuses is omitted. Given the marginal distributions of the remaining life-times, lower and upper bounds are derived for the single premiums of multi-life insurances and annuities.

    The economics of insurance: a review and some recent developments.

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    The present paper is devoted to different methods of choice under risk in an actuarial setting. The classical expected utility theory is first presented, and its drawbacks are underlined. A second approach based on the so-called distorted expectation hypothesis is then described. It will be seen that the well-known stochastic dominance as well as the stop-loss order have common interpretations in both theories, while defining higher degree stochastic orders leads to different concepts. The aim of this paper is to emphasize the similarities of the two approaches of choice under risk as well as to point out their major differences.Economics; Insurance;

    Some Remarks on IBNR Evaluation Techniques

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    In this short paper we discuss a new methodology for estimating reserves for IBNR (incurred but not reported) claims.

    Stochastic approximations of present value functions.

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    The aim of the paper is to apply the method proposed by Denuit, Genest and Marceau (1999) for deriving stochastic upper and lower bounds on the present value of a sequence of cash flows, where the discounting is performed under a given stochastic return process. The convex approximation provided by Goovaerts, Dhaene and De Schepper (1999) and Goovaerts and Dhaene (1999) is then compared to these stochastic bounds. On the basis of several numerical examples, it will be seen that the convex approximation seems reasonable.Value; Functions;

    A straightforward analytical calculation of the distribution of an annuity certain with stochastic interest rate.

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    Starting from the moment generating function of the annuity certain with stochastic interest rate written by means of a time discretization of the Wiener process as an n-fold integral, a straightforward evaluation of the corresponding distribution function is obtained letting n tend to infinity. The advantage of the present method consists in the direct calculation technique of the n-fold integral, instead of using moment calculation or differential equations, and in the possible applicability of the present method to varying annuities which could be applied to IBNR results, as well as to pension fund calculations, etc.Distribution; Annuities; Processes; Evaluation;

    A simple proof that comonotonic risks have the convex-largest sum.

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    In the recent actuarial literature, several proofs have been given for the fact that if a random vector X(1), X(2), …, X(n) with given marginals has a comonotonic joint distribution, the sum X(1) + X(2) + … + X(n) is the largest possible in convex order. In this note we give a lucid proof of this fact, based on a geometric interpretation of the support of the comonotonic distribution.Risk; Actuarial; Distribution;
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