An improved framework to price risk-based catastrophe bonds for earthquakes

Abstract

Catastrophe bonds (cat bonds in short) are insurance-linked securities developed in the late 90s to improve financial resilience and disaster risk management strategies used in the insurance industry. In the context of disaster risk management, financial risk arises from the economic losses caused by catastrophic event such as earthquakes, hurricanes and floods. The main feature of cat bond is the ability to diversify the financial risk from sponsors (e.g., insurance company) to the capital market. Besides their use as risk transfer products, cat bonds are attractive investment products for institutional investors (e.g. hedge funds) who are interested in diversified and high-yield portfolios. One of the key component in pricing cat bonds is the assessment of the catastrophic risk in terms of probable loss estimates. As earthquakes are one of the prominent catastrophes that have long history of inflicting tremendous financial and human losses across the globe, the present work will focus on earthquakes as main hazard type. Despite of the availability of various earthquake financial risk management strategies, the insurance penetration is still low for major parts of the world which indicates higher protection gaps. With the current capability of insurance industry this issue can be mitigated by developing new technology and products for covering the protection gap. The research presented herein focuses on incorporating region specific knowledge of earthquake risk in pricing cat bonds. More specifically, an improved framework is proposed to integrate seismic hazard models with the current cat bond pricing formulations. The proposed framework involves the development of high resolution hazard, exposure and vulnerability models; these are then used to compute financial losses and cat bonds at urban scale. Further investigation is carried out to explore the effects of uncertainty in the exposure model, specifically related to asset location and their attributes. To this end, a Monte Carlo based stochastic exposure model is proposed to propagate these uncertainties in the seismic loss estimation and cat bond price. A sensitivity analysis is presented to demonstrate the implementation of the proposed approach and to investigate the effects of the spatial resolution of exposure model on the estimated losses and cat bond prices. The last contribution of the present work is to incorporate the effect of aftershocks within the earthquake cat bond pricing framework. This is achieved by developing a time-dependent aggregate loss model, where the occurrence of earthquake events (background and triggered events) are modelled using an epidemic type-aftershock sequencing approach. In the proposed approach the severity of the events is computed by performing a time-dependent seismic loss estimation that accounts for the accumulation of damage due to earthquake sequences. Finally, a case-study is presented to demonstrate the implementation of the proposed model and its importance on the time-dependency on cat bond pricing. To conclude, this study has revealed the importance of using high-resolution earthquake risk models for cat bond pricing as well as it demonstrates the impact due to damage accumulation caused by earthquake sequence on the loss estimates and cat bond price. The work presented in this thesis has the potential of implementing in the catastrophe modelling industry.

Date of Award	22 Aug 2023
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Domenico Lombardi (Main Supervisor) & Andrew Foster (Co Supervisor)