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A random forest based approach for predicting spreads in the primary catastrophe bond market

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  • Despoina Makariou
  • Pauline Barrieu
  • Yining Chen

Abstract

We introduce a random forest approach to enable spreads' prediction in the primary catastrophe bond market. We investigate whether all information provided to investors in the offering circular prior to a new issuance is equally important in predicting its spread. The whole population of non-life catastrophe bonds issued from December 2009 to May 2018 is used. The random forest shows an impressive predictive power on unseen primary catastrophe bond data explaining 93% of the total variability. For comparison, linear regression, our benchmark model, has inferior predictive performance explaining only 47% of the total variability. All details provided in the offering circular are predictive of spread but in a varying degree. The stability of the results is studied. The usage of random forest can speed up investment decisions in the catastrophe bond industry.

Suggested Citation

  • Despoina Makariou & Pauline Barrieu & Yining Chen, 2020. "A random forest based approach for predicting spreads in the primary catastrophe bond market," Papers 2001.10393, arXiv.org.
    • Handle: RePEc:arx:papers:2001.10393
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    References listed on IDEAS

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    1. Mathieu Gatumel & Dominique Guegan, 2008. "Towards an understanding approach of the insurance linked securities market," Documents de travail du Centre d'Economie de la Sorbonne b08006, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. Marcello Galeotti & Marc Gürtler & Christine Winkelvos, 2013. "Accuracy of Premium Calculation Models for CAT Bonds—An Empirical Analysis," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 80(2), pages 401-421, June.
    3. Mathieu Gatumel & Dominique Guegan, 2008. "Towards an understanding approach of the insurance linked securities market," Post-Print halshs-00235354, HAL.
    4. Alexander Braun, 2016. "Pricing in the Primary Market for Cat Bonds: New Empirical Evidence," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(4), pages 811-847, December.
    5. Lane, Morton & Mahul, Olivier, 2008. "Catastrophe risk pricing : an empirical analysis," Policy Research Working Paper Series 4765, The World Bank.
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    Cited by:

    1. Tobias Götze & Marc Gürtler & Eileen Witowski, 2020. "Improving CAT bond pricing models via machine learning," Journal of Asset Management, Palgrave Macmillan, vol. 21(5), pages 428-446, September.
    2. Tobias Götze & Marc Gürtler & Eileen Witowski, 0. "Improving CAT bond pricing models via machine learning," Journal of Asset Management, Palgrave Macmillan, vol. 0, pages 1-19.

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