Forecasting U.S. Insured Hurricane Losses

Condensed summary Coastal hurricanes generate huge financial losses within the insurance industry. The relative infrequency of severe coastal hurricanes implies that empirical probability estimates of the next big loss will be unreliable. Hurricane climatol-ogists have recently developed statistical models to forecast the level of coastal hurricane activity based on climate conditions prior to the season. Motivated by the usefulness of such models, in this chapter we analyze and model a catalog of normalized insured losses caused by hurricanes affecting the United States. The catalog of losses dates back through the twentieth century. The purpose of this work is to develop a preseason forecast tool that can be used for insurance applications. Although wind speed is directly related to damage potential, the amount of damage depends on both storm intensity and storm size. As antici-pated, we found that climate conditions prior to a hurricane season provide information about possible future insured hurricane losses. The models exploit this information to predict the distribution of likely annual losses and th