 Mitigating wildfire losses via insurance‐linked securities: Modeling and risk management perspectivesHong Li and Jianxi Su Journal of Risk & Insurance, 2024, vol. 91, issue 2, 383-414 Abstract: This paper investigates the use of catastrophe (CAT) bonds as a risk management tool for wildfires. We introduce a set of Bayesian dynamic models designed to accurately represent wildfire losses, allowing a thorough examination of wildfire CAT bond pricing and hedge effectiveness. Our model captures crucial attributes of wildfire data, such as zero inflation, overdispersion, temporal fluctuations, and spatial dependence. Employing extensive quantitative analyses of US wildfire data, we highlight that CAT bonds can substantially mitigate tail risk associated with insurers' liability. Importantly, index‐based CAT bonds, drawing their payouts from aggregate wildfire losses over a larger geographical scope than an insurer's operational area, also provide effective hedges. Our research underscores the potential of wildfire CAT bonds as an enhancement to traditional reinsurance strategies, offering insurers an improved means to manage and mitigate wildfire exposures amidst inherent uncertainties. Date: 2024 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:jrinsu:v:91:y:2024:i:2:p:383-414 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of Risk & Insurance is currently edited by Joan T. Schmit More articles in Journal of Risk & Insurance from The American Risk and Insurance Association Contact information at EDIRC. |
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