A Bayesian valuation framework for catastrophe bonds

Abstract

Abstract Catastrophe (CAT) bond markets are incomplete and hence carry uncertainty in instrument pricing. Various pricing approaches have been proposed, but none treats the uncertainty in catastrophes and interest rates in a sufficiently flexible and statistically reliable way within an asset valuation framework. Consequently, little is known empirically about the expected risk premium of CAT bonds. The primary contribution of this article is to present a Bayesian CAT bond valuation framework based on uncertainty quantification of catastrophes and interest rates. We leverage this framework to estimate fair value prices and expected risk premiums for CAT bonds with varying catastrophe risk profiles.