A regional compound Poisson process for hurricane and tropical storm damage

In light of intense hurricane activity along the US Atlantic coast, attention has turned to understanding both the economic effect and the behaviour of these storms. The compound Poisson–log-normal process has been proposed as a model for aggregate storm damage but does not shed light on regional analysis since storm path data are not used. We propose a fully Bayesian regional prediction model which uses conditional auto-regressive models to account for both storm paths and spatial patterns for storm damage. When fitted to historical data, the analysis from our model both confirms previous findings and reveals new insights on regional storm tendencies. Posterior predictive samples can also be used for pricing regional insurance premiums, which we illustrate by using three different risk measures.

Duke Scholars

Author Simon Mak Statistical Science