Convergence of a sequence of bivariate Archimedean copulas to another Archimedean copula or to the comonotone copula is shown to be equivalent with convergence of the corresponding sequence of Kendall distribution functions. No extra differentiability conditions on the generators are needed

The present research relaxes three of the usual assumptions made in the insurance literature. It is assumed that (1) there is a finite number of risks, (2) the risks are not statistically independent and (3) the structure of the market is monopolistic. In this context, the article analyses two...

We revisit Machina's local utility as a tool to analyze attitudes to multivariate risks. Using martingale embedding techniques, we show that for non-expected utility maximizers choosing between multivariate prospects, aversion to multivariate mean preserving increases in risk is equivalent to...

This paper develops a theoretical framework for analyzing the decision to provide or buy insurance against the risk of natural catastrophes. In contrast to conventional models of insurance, the insurer has a non-zero probability of insolvency which depends on the distribution of the risks, the...

In this paper, we investigate the impact of the claim reporting strategy of drivers, within a bonus malus system. We exhibit the induced modification of the corresponding class level transition matrix and derive the optimal reporting strategy for rational drivers. The hunger for bonuses induces...