Second order tail asymptotics for the sum of dependent, tail-independent regularly varying risks

In this paper we consider dependent random variables with common regularly varying marginal distribution. Under the assumption that these random variables are tail-independent, it is well known that the tail of the sum behaves like in the independence case. Under some conditions on the marginal distributions and the dependence structure (including Gaussian copula's and certain Archimedean copulas) we provide the second-order asymptotic behavior of the tail of the su

Tail asymptotics of randomly weighted large risks

In this paper we are concerned with a sample of asymptotically independent risks. Tail asymptotic probabilities for linear combinations of randomly weighted order statistics are approximated under various assumptions, where the individual tail behaviour has a crucial role. An application is provided for Log-Normal risks

Ruin problem in a changing environment and application to the cost of climate change for an insurance company

In this paper we obtain asymptotics for ruin probability in a risk model where claim size distribution as well as claim frequency change over time. This is a way to take into account observed and/or projected changes, due to climate change, in some specific weather-related events like tropical storms for instance. Some examples will be presented in order to illustrate the theory and start a discussion on the possible cost of climate change for an insurance company who wants to remain financially solvent

Aggregation of randomly weighted large risks

Asymptotic tail probabilities for linear combinations of randomly weighted order statistics are approximated under various assumptions. One key assumption is the asymptotic independence for all risks. Therefore, it is not surprising that the maxima represents the most influential factor when one investigates the tail behaviour of our considered risk aggregation, which, for example, can be found in the reinsurance market. This extreme behaviour confirms the ‘one big jump’ property that has been vastly discussed in the existing literature in various forms whenever asymptotic independence is present. An illustration of our results together with a specific application are explored under the assumption that the underlying risks follow the multivariate log-normal distribution

Quasi-Monte Carlo Techniques and Rare Event Sampling ⋆

In the last decade considerable practical interest, e.g. in credit and insurance risk or telecommunication applications, as well as methodological challenges caused intensive research on estimation of rare event probabilities. This article aims to show that recently developed rare event estimators are especially well-suited for a quasi-Monte Carlo framework by establishing limit relations for the so-called effective dimension and proposing smoothing methods to overcome problems with cusps of the integrand

On ruin probability and aggregate claim representations for Pareto claim size distributions

We generalize an integral representation for the ruin probability in a Crámer-Lundberg risk model with shifted (or also called US-)Pareto claim sizes, obtained by Ramsay (2003), to classical Pareto(a) claim size distributions with arbitrary real values a>1 and derive its asymptotic expansion. Furthermore an integral representation for the tail of compound sums of Pareto-distributed claims is obtained and numerical illustrations of its performance in comparison to other aggregate claim approximations are provided.

An asymptotic expansion for the tail of compound sums of Burr distributed random variables

In this paper we show that it is possible to write the Laplace transform of the Burr distribution as the sum of four series. This representation is then used to provide a complete asymptotic expansion of the tail of the compound sum of Burr distributed random variables. Furthermore it is shown that if the number of summands is fixed, this asymptotic expansion is actually a series expansion if evaluated at sufficiently large arguments.