Nuclear Catastrophe Risk Bonds in a Markov-Dependent Environment
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 3, Issue 4
Abstract
The financing of the 2011 Fukushima disaster and the U.K. Hinkley nuclear power plant investment, respectively by the Japanese, and U.K. and Chinese governments and the private sector, provide a strong motivation for this paper to explore deeper the concept of modeling and pricing nuclear catastrophe (N-CAT) risk bonds. Because of the magnitude of the potential liabilities and reinvestments needed, the demand to develop a dependable liability coverage product that can be triggered in a case of emergency is required more than ever, and it should be considered thoroughly. Thus, in the present paper, under a semi-Markov structure environment to model the relationship between claims severity and intensity, the N-CAT risk bond is further explored under various scenarios supporting further the bond sponsors, allowing them to appreciate more their significance. Consequently, the new version of the N-CAT risk bond includes several absorbing and transit states to make it more suitable for practitioners. Additionally, this paper uses the two most commonly used interest rate models and considers four types of payoff functions. Finally, two numerical examples illustrate the main findings.
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Acknowledgments
The authors would like to acknowledge the partial support of this work through the EPSRC and ESRC Centre for Doctoral Training on Quantification and Management of Risk and Uncertainty in Complex Systems and Environment (EP/L015927/1). The third author acknowledges the financial support of the national Security Analysis Department at the Applied Physics Lab of the Johns Hopkins University during his sabbatical leave from the University of Maryland, College Park.
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ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 3 • Issue 4 • December 2017
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©2017 American Society of Civil Engineers.
History
Received: Jan 24, 2017
Accepted: Apr 14, 2017
Published online: Jul 19, 2017
Published in print: Dec 1, 2017
Discussion open until: Dec 19, 2017
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