Multivariate Ruin in Lévy-driven Insurance Risk Models under Heavy Tails

Source abstract

The paper studies finite-horizon ruin for an insurance company with several lines of business admitting heavy-tailed claims. The claim amount process of the insurance company is modeled as a multivariate increasing Lévy process possibly perturbed with fluctuations. A relevant insolvency event may involve the failure of a single line, of several lines at once, or of groups of lines linked through internal transfers, reinsurance, or a guarantee arrangement. These events have different geometries and need not occur on the same probability scale. Under asymptotic tail independence among claims from different lines, classical regular variation assigns zero limiting probability to a multi-line failure and is therefore unable to identify either the ruin probability or the corresponding solvency capital requirement. Using a multivariate Lévy process to model cumulative claims and regular variation on a nested sequence of subcones of the positive orthant to model dependence across lines, we provide the exact scaling rate of the ruin probability and the limit behavior. Additionally, explicit computations are presented for examples with independent business lines, common arrivals of independent claims, Gaussian copula dependent claims, Marshall-Olkin dependent claims, and bipartite insurance networks. Finally, we use Monte Carlo simulations to support our theoretical findings.