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Global losses from extreme events are on the rise. Insurance companies highly rely on the ILS market and especially on CAT bonds to transfer the risk they are exposed to onto investors. However, because CAT bonds are not standardized, it is a challenging question how to price them accurately. With this work I intend to offer a model that is grounded in theory yet also tractable. In order to identify the main determinants of the cat bond spread at issuance I run a series of OLS regressions using a dataset that comprises 1087 CAT bond tranches issued between June 1997 and March 2020. I find evidence that besides expected loss, CAT bond spreads fluctuate in line with the general level of reinsurance premiums and the BB-Spread. Covered territory, sponsoring firm and rating have also a great impact. The pricing model proposed exhibits a robust fit across different calibration subsamples and achieves a higher in-sample and out-of-sample accuracy than several previous specifications.
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CAT bond spread Pricing model Out-of-sample analysis