Abstract
For insurance companies, wind storms represent a main source of volatility, leading to potentially huge aggregated claim amounts. In this article, we compare different constructions of a storm index allowing us to assess the economic impact of storms on an insurance portfolio by exploiting information from historical wind speed data. Contrary to historical insurance portfolio data, meteorological variables can be considered as stationary between years and are easily available with long observation records; hence, they represent a valuable source of additional information for insurers if the relation between observations of claims and wind speeds can be revealed. Since standard correlation measures between raw wind speeds and insurance claims are weak, a storm index focusing on high wind speeds can afford better information. This method has been used on the German territory by Klawa and Ulbrich and gave good results for yearly aggregated claims. Using historical meteorological and insurance data, we assess the consistency of the pro-posed indices construction and we test their sensitivity to their various parameters and weights. Moreover, we are able to place the major insurance events since 1998 on a broader horizon of 40+ years. Our approach provides a meteorological justification for calculating the return periods of extreme storm-related insurance events whose magnitude has rarely been reached.