Skip to main content
Top

2020 | OriginalPaper | Chapter

5. Designing Insurance Against Extreme Weather Risk: The Case of HuRLOs

Authors : Martin Boyer, Michèle Breton, Pascal François

Published in: Ecological, Societal, and Technological Risks and the Financial Sector

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

This article studies the market for HuRLOs (Hurricane Risk Landfall Option), launched in 2008 by Weather Risk Solutions. The HuRLO market allows investors to hedge against, or speculate on, the risk that a specific region in the Gulf of Mexico and on the East Coast of the United States will be the first to be hit by a hurricane. We simulate HuRLO market operations under various strategies used by risk-averse players using a formulation that accounts for the pari-mutuel price formation mechanism. We show that the order type, sequence, and order packaging significantly impact on the price paid, and on the number of traded options. We thus highlight that HuRLOs are difficult to evaluate and to purchase optimally, which limits the ability of the HuRLO market to act as an effective insurance mechanism. Potential improvements in the design of HuRLO contracts are suggested.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Appendix
Available only for authorised users
Footnotes
1
See the hurricane generation models of Hall and Jewson (2007) and Rumpf et al. (2009) for the case of the North Atlantic, and of Rumpf et al. (2007) and of Yonekura and Hall (2011) for the case of the western North-Pacific.
 
2
According to Pielke et al. (2008) the hurricanes that landed in Miami in 1926 resulted in losses of 760 million dollars. If such a hurricane were to hit the Miami agglomeration today, the financial losses would amount to approximately 150 billion dollars (or 102 billion 2004-dollars according to Kunreuther and Michel-Kerjan 2009). Hurricane Katrina, which hit New Orleans in 2005, caused damages estimated at 108 billion dollars according to the National Oceanic and Atmospheric Administration.
 
3
The pari-mutuel mechanism was invented by Pierre Oller in 1865 in order to limit the profit of bookmarkers who were then controlling the betting industry in France. Since 2002, many investment banks have used a pari-mutuel mechanism for wagering on various economic statistics; odds on these statistics have been shown to be efficient forecasts of their future values (Gürkaynak and Wolfers 2006). The pari-mutuel market microstructure is analyzed by Lange and Economides (2005) who show the existence of a unique price equilibrium and find many advantages of pari-mutuel over the traditional exchange mechanism. A pari-mutuel auction system for capital markets is proposed by Baron and Lange (2007).
 
4
www.​weatherrisksolut​ions.​com (last visited in January 2019).
 
5
To qualify, a hurricane must be identified as such by the NHC and must cause more than 1 million dollars damage according to EQECAT (now part of Corelogic).
 
6
A new series of options is launched every time a new hurricane is identified by the National Hurricane Center.
 
7
A list of notations for all parameters and variables used in this paper is provided in Appendix 1.
 
8
In reality, it seems that λ is between 5 and 6. See http://​climateaudit.​org/​2007/​01/​14/​more-evidence-that-hurricanes-are-the-result-of-a-poisson-process/​ (last visited on February 22th, 2019).
 
Literature
go back to reference Baron, K., & Lange, J. (2007). Pari-mutuel applications in finance: New markets for new risks. Basingstoke: Palgrave Macmillan.CrossRef Baron, K., & Lange, J. (2007). Pari-mutuel applications in finance: New markets for new risks. Basingstoke: Palgrave Macmillan.CrossRef
go back to reference Bonazzi, A., Dobbin, A. L., Turner, J. K., Wilson, P. S., Mitas, C., & Bellone, E. (2014). A simulation approach for estimating hurricane risk over a 5-yr horizon. Weather, Climate and Society, 6, 77–90.CrossRef Bonazzi, A., Dobbin, A. L., Turner, J. K., Wilson, P. S., Mitas, C., & Bellone, E. (2014). A simulation approach for estimating hurricane risk over a 5-yr horizon. Weather, Climate and Society, 6, 77–90.CrossRef
go back to reference Bove, M. C., Elsner, J. B., Landsea, C. W., Niu, X., & O’Brien, J. J. (1998). Effect of El Nino on U.S. landfalling hurricanes, revisited. Bulletin of American Meteorological Society, 79, 2477–2482.CrossRef Bove, M. C., Elsner, J. B., Landsea, C. W., Niu, X., & O’Brien, J. J. (1998). Effect of El Nino on U.S. landfalling hurricanes, revisited. Bulletin of American Meteorological Society, 79, 2477–2482.CrossRef
go back to reference Cummins, J. D. (2008). CAT bonds and other risk-linked securities: State of the market and recent developments. Risk Management and Insurance Review, 11, 23–47.CrossRef Cummins, J. D. (2008). CAT bonds and other risk-linked securities: State of the market and recent developments. Risk Management and Insurance Review, 11, 23–47.CrossRef
go back to reference Cummins, J. D. (2012). CAT bonds and other risk-linked securities: Product design and evolution of the market. The Geneva Reports: Risk and Insurance Research, 5, 39–61. Cummins, J. D. (2012). CAT bonds and other risk-linked securities: Product design and evolution of the market. The Geneva Reports: Risk and Insurance Research, 5, 39–61.
go back to reference Cummins, J. D., & Barrieu, P. (2013). Innovations in insurance markets: Hybrid and securitized risk transfer solutions. In G. Dionne (Ed.), Handbook of insurance. Boston: Kluwer Academic Publishers. Cummins, J. D., & Barrieu, P. (2013). Innovations in insurance markets: Hybrid and securitized risk transfer solutions. In G. Dionne (Ed.), Handbook of insurance. Boston: Kluwer Academic Publishers.
go back to reference Epstein, E. S. (1985). Statistical inference and prediction in climatology: A Bayesian approach. Springer. Meteorological Monographs. Epstein, E. S. (1985). Statistical inference and prediction in climatology: A Bayesian approach. Springer. Meteorological Monographs.
go back to reference Doherty, N. A. (1997). Financial innovation in the management of catastrophe risk. Journal of Applied Corporate Finance, 10(3), 84–95.CrossRef Doherty, N. A. (1997). Financial innovation in the management of catastrophe risk. Journal of Applied Corporate Finance, 10(3), 84–95.CrossRef
go back to reference Froot, K. A. (2001). The market for catastrophe risk: A clinical examination. Journal of Financial Economics, 60(2), 529–571.CrossRef Froot, K. A. (2001). The market for catastrophe risk: A clinical examination. Journal of Financial Economics, 60(2), 529–571.CrossRef
go back to reference Gray, W. M., Landsea, C. W., Mielke, P. W., & Berry, K. J. (1992). Predicting Atlantic seasonal hurricane activity 6–11 months in advance. Weather and Forecasting, 7, 440–455.CrossRef Gray, W. M., Landsea, C. W., Mielke, P. W., & Berry, K. J. (1992). Predicting Atlantic seasonal hurricane activity 6–11 months in advance. Weather and Forecasting, 7, 440–455.CrossRef
go back to reference Gürkaynak, R., & Wolfers, J. (2006). Macroeconomic derivatives: An initial analysis of market-based macro forecasts, uncertainty, and risk. National Bureau of Economic Research Working Paper, no. 11929. Cambridge, MA: National Bureau of Economic Research. Gürkaynak, R., & Wolfers, J. (2006). Macroeconomic derivatives: An initial analysis of market-based macro forecasts, uncertainty, and risk. National Bureau of Economic Research Working Paper, no. 11929. Cambridge, MA: National Bureau of Economic Research.
go back to reference Hall, T. M., & Jewson, S. (2007). Statistical modelling of North Atlantic tropical cyclone tracks. Tellus, 59A(4), 486–498.CrossRef Hall, T. M., & Jewson, S. (2007). Statistical modelling of North Atlantic tropical cyclone tracks. Tellus, 59A(4), 486–498.CrossRef
go back to reference Horowitz, K. A., Bequillard, A. L., Nyren, A. P., Protter, P. E., & Wilks, D. S. (2012). U.S. patent No. 8,266,042. Washington, DC: U.S. Patent and Trademark Office. Horowitz, K. A., Bequillard, A. L., Nyren, A. P., Protter, P. E., & Wilks, D. S. (2012). U.S. patent No. 8,266,042. Washington, DC: U.S. Patent and Trademark Office.
go back to reference Jewson, S., & Hall, T. M. (2007). Comparison of local and basin-wide methods for risk assessment of tropical cyclone landfall. Journal of Applied Meteorology and Climatology, 47(2), 361–367. Jewson, S., & Hall, T. M. (2007). Comparison of local and basin-wide methods for risk assessment of tropical cyclone landfall. Journal of Applied Meteorology and Climatology, 47(2), 361–367.
go back to reference Kelly, D. L., Letson, D., Nelson, F., Nolan, D. S., & Solís, D. (2012). Evolution of subjective hurricane risk perceptions: A Bayesian approach. Journal of Economic Behavior & Organization, 81(2), 644–663.CrossRef Kelly, D. L., Letson, D., Nelson, F., Nolan, D. S., & Solís, D. (2012). Evolution of subjective hurricane risk perceptions: A Bayesian approach. Journal of Economic Behavior & Organization, 81(2), 644–663.CrossRef
go back to reference Kriesche, B., Weindl, H., Smolka, A., & Schmidt, V. (2014). Stochastic simulation model for tropical cyclone tracks with special emphasis on landfall behavior. Natural Hazards, 73, 335–353.CrossRef Kriesche, B., Weindl, H., Smolka, A., & Schmidt, V. (2014). Stochastic simulation model for tropical cyclone tracks with special emphasis on landfall behavior. Natural Hazards, 73, 335–353.CrossRef
go back to reference Kunreuther, H., & Michel-Kerjan, E. (2009). The development of new catastrophe risk markets. Annual Review of Resource Economics, 1, 119–137. Kunreuther, H., & Michel-Kerjan, E. (2009). The development of new catastrophe risk markets. Annual Review of Resource Economics, 1, 119–137.
go back to reference Lange, J., & Economides, N. (2005). A pari-mutuel market microstructure for contingent claims. Journal of European Financial Management, 11(1), 25–49.CrossRef Lange, J., & Economides, N. (2005). A pari-mutuel market microstructure for contingent claims. Journal of European Financial Management, 11(1), 25–49.CrossRef
go back to reference Meyer, R. J., Horowitz, M., Wilks, D. S., & Horowitz, K. A. (2008). A mutualized risk market with endogenous prices with application to U.S. landfalling hurricanes. Working Paper 2008-12-08, Risk Management and Decision Processes Center, The Wharton School of the University of Pennsylvania. Meyer, R. J., Horowitz, M., Wilks, D. S., & Horowitz, K. A. (2008). A mutualized risk market with endogenous prices with application to U.S. landfalling hurricanes. Working Paper 2008-12-08, Risk Management and Decision Processes Center, The Wharton School of the University of Pennsylvania.
go back to reference Meyer, R. J., Horowitz, M., Wilks, D. S., & Horowitz, K. A. (2014). A novel financial market for mitigating hurricane risk. II. Empirical validation. Weather, Climate, and Society, 6, 318–330.CrossRef Meyer, R. J., Horowitz, M., Wilks, D. S., & Horowitz, K. A. (2014). A novel financial market for mitigating hurricane risk. II. Empirical validation. Weather, Climate, and Society, 6, 318–330.CrossRef
go back to reference Milgrom, P., & Stokey, N. (1982). Information, trade and common knowledge. Journal of Economic Theory, 26(1), 17–27.CrossRef Milgrom, P., & Stokey, N. (1982). Information, trade and common knowledge. Journal of Economic Theory, 26(1), 17–27.CrossRef
go back to reference Nakamura, J., Lall, U., Kushnir, Y., & Rajagopalan, B. (2015). HITS: Hurricane intensity and track simulator with North Atlantic ocean applications for risk assessment. Journal of Applied Meteorology and Climatology, 54, 1620–1636.CrossRef Nakamura, J., Lall, U., Kushnir, Y., & Rajagopalan, B. (2015). HITS: Hurricane intensity and track simulator with North Atlantic ocean applications for risk assessment. Journal of Applied Meteorology and Climatology, 54, 1620–1636.CrossRef
go back to reference Ou-Yang, C., & Doherty, N. (2011). Pari-mutuel insurance for hedging against catastrophic risk. Wharton School Working Paper # 2011-08. Ou-Yang, C., & Doherty, N. (2011). Pari-mutuel insurance for hedging against catastrophic risk. Wharton School Working Paper # 2011-08.
go back to reference Pielke, R. A., Jr., Gratz, J., Landsea, C. W., Collins, D., Saunders, M. A., & Musulin, R. (2008). Normalized hurricane damage in the United States: 1900–2005. Natural Hazards Review, 9(1), 29–42.CrossRef Pielke, R. A., Jr., Gratz, J., Landsea, C. W., Collins, D., Saunders, M. A., & Musulin, R. (2008). Normalized hurricane damage in the United States: 1900–2005. Natural Hazards Review, 9(1), 29–42.CrossRef
go back to reference Ramella, M., & Madeiros, L. (2007). Bermuda sidecars: Supervising reinsurance companies in innovative global markets. Geneva Papers on Risk & Insurance, 32(3), 345–363. Ramella, M., & Madeiros, L. (2007). Bermuda sidecars: Supervising reinsurance companies in innovative global markets. Geneva Papers on Risk & Insurance, 32(3), 345–363.
go back to reference Rumpf, J., Weindl, H., Höppe, P., Rauch, E., & Schmidt, V. (2007). Stochastic modelling of tropical cyclone tracks. Mathematical Methods of Operations Research, 66(3), 475–490.CrossRef Rumpf, J., Weindl, H., Höppe, P., Rauch, E., & Schmidt, V. (2007). Stochastic modelling of tropical cyclone tracks. Mathematical Methods of Operations Research, 66(3), 475–490.CrossRef
go back to reference Rumpf, J., Weindl, H., Höppe, P., Rauch, E., & Schmidt, V. (2009). Tropical cyclone hazard assessment using model-based track simulation. Natural Hazards, 48(3), 383–398.CrossRef Rumpf, J., Weindl, H., Höppe, P., Rauch, E., & Schmidt, V. (2009). Tropical cyclone hazard assessment using model-based track simulation. Natural Hazards, 48(3), 383–398.CrossRef
go back to reference Vickery, P. J., Skerlj, P., & Twisdale, L. (2000). Simulation of hurricane risk in the U.S. using an empirical track model. Journal of Structuring Engineering, 126(10), 1222–1237.CrossRef Vickery, P. J., Skerlj, P., & Twisdale, L. (2000). Simulation of hurricane risk in the U.S. using an empirical track model. Journal of Structuring Engineering, 126(10), 1222–1237.CrossRef
go back to reference Wilks, D. S. (2010). A novel financial market structure for mitigating hurricane risk. Proceedings of the 20th Conference on Probability and Statistics in the Atmospheric Sciences. Wilks, D. S. (2010). A novel financial market structure for mitigating hurricane risk. Proceedings of the 20th Conference on Probability and Statistics in the Atmospheric Sciences.
go back to reference Yonekura, E., & Hall, T. M. (2011). A statistical model of tropical cyclone tracks in the western North Pacific with ENSO-dependent cyclogenesis. Journal of Applied Meteorology and Climatology, 50(8), 1725–1739.CrossRef Yonekura, E., & Hall, T. M. (2011). A statistical model of tropical cyclone tracks in the western North Pacific with ENSO-dependent cyclogenesis. Journal of Applied Meteorology and Climatology, 50(8), 1725–1739.CrossRef
Metadata
Title
Designing Insurance Against Extreme Weather Risk: The Case of HuRLOs
Authors
Martin Boyer
Michèle Breton
Pascal François
Copyright Year
2020
Publisher
Springer International Publishing
DOI
https://doi.org/10.1007/978-3-030-38858-4_5