Hybrid-Triggered CAT Bond Pricing For Flood Risk Using Copula-EVT Models

Date

2025-9-01

Author

Biçer Gürgen, Tuğçe

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

3282
views

0
downloads

Cite This

This thesis develops a hybrid triggered catastrophe (CAT) bond pricing model for flood risk. As a case study we employ the data from Harris County, Texas where three trigger indicators are selected for their relevance to extreme flood events. These are GDP-indexed economic damages, daily precipitation, and minimum wind speed. The statistical modelling of extremes is conducted within the extreme value theory (EVT) framework using the peaks over threshold (POT) approach and the generalized pareto distribution (GPD). Upper tail dependence among the variables is captured by a trivariate Gumbel copula. The resulting joint exceedance probabilities are incorporated into a multi-year CAT bond pricing formula under the Cox-Ingersoll-Ross (CIR) stochastic interest rate model. Empirical analysis shows that CAT bond prices are negatively correlated with maturity, nominal interest rate, and upper tail dependence among trigger indicators, while positively correlated with trigger levels and coupon rate. The findings indicate that meteorological triggers have a greater impact on pricing than economic damages, and that stronger dependence increases the probability of simultaneous trigger activation, which reduces bond value. This study presents a comprehensive framework that integrates EVT based marginal modelling, dependence analysis, and stochastic discounting. It offers practical guidance for designing pricing strategies that balance investor return and catastrophic risk transfer.

Subject Keywords

Extreme Value Theory (EVT), Copula, Hybrid Trigger, Flood Risk, Climate Change, CAT Bond

URI

https://hdl.handle.net/11511/115663

Collections

Graduate School of Applied Mathematics, Thesis