Modelling and valuation of catastrophe bonds across multiple regions

TL;DR

This paper develops and compares different models for pricing catastrophe bonds across multiple regions, incorporating dependence structures and market risk adjustments, with practical illustrations using real data.

Contribution

It introduces new multi-region catastrophe bond pricing models that account for various dependence scenarios and market risk, including a normal approximation and Wang's transform.

Findings

Dependence structure significantly affects bond prices.

Normal approximation performs well in practical scenarios.

Market risk adjustment via Wang's transform alters valuation.

Abstract

The insurance-linked securities (ILS) market, as a form of alternative risk transfer, has been at the forefront of innovative risk-transfer solutions. The catastrophe bond (CAT bond) market now represents almost half of the entire ILS market and is growing steadily. Since CAT bonds are often tied to risks in different regions, we follow this idea by constructing different pricing models that incorporate various scenarios of dependence between catastrophe losses in different areas. Namely, we consider independent, proportional, and arbitrary two-dimensional distribution cases. We also derive a normal approximation of the prices. Finally, to include the market price of risk, we apply Wang's transform. We illustrate the differences between the scenarios and the performance of the approximation on the Property Claim Services data.