Statistical and machine learning approaches for the minimization of trigger errors in parametric earthquake catastrophe bonds

Laura Calvet Mir; Madeleine Lopeman; Jésica de Armas; Guillermo Franco; Ángel Alejandro Juan Pérez

Ayuda

Statistical and machine learning approaches for the minimization of trigger errors in parametric earthquake catastrophe bonds

Laura Calvet ^[1] ; Madeleine Lopeman ; Jésica de Armas ^[2] ; Guillermo Franco ; Angel A. Juan ^[1]
1. [1] Universitat Oberta de Catalunya
  
  Universitat Oberta de Catalunya
  
  Barcelona, España
2. [2] Universitat Pompeu Fabra
  
  Universitat Pompeu Fabra
  
  Barcelona, España
Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 41, Nº. 2, 2017, págs. 373-392
Idioma: inglés
Enlaces
- Texto completo (pdf)

Dialnet Métricas: 1 Cita

Resumen
- Catastrophe bonds are financial instruments designed to transfer risk of monetary losses arising from earthquakes, hurricanes, or floods to the capital markets. The insurance and reinsurance industry, governments, and private entities employ them frequently to obtain coverage. Parametric catastrophe bonds base their payments on physical features. For instance, given parameters such as magnitude of the earthquake and the location of its epicentre, the bond may pay a fixed amount or not pay at all. This paper reviews statistical and machine learning techniques for designing trigger mechanisms and includes a computational experiment. Several lines of future research are discussed.
Referencias bibliográficas
- Cardenas, V., Hochrainer, S., Mechler, R., Pflug, G. and Linnerooth-Bayer, J. (2007). Sovereign financial disaster risk management: the case...
- Croson, D.C. and Kunreuther, H. (1999). Customizing reinsurance and cat bonds for natural hazard risks. In Conference on Global Change and...
- Cummins, J.D. (2007). CAT bonds and other risk-linked securities: state of the market and recent developments. Social Science Research Network....
- Cummins, J.D. and Weiss, M.A. (2009). Convergence of insurance and financial markets: hybrid and securitized risk-transfer solutions. Journal...
- Damnjanovic, I., Aslan, Z. and Mander, J. (2010). Market-implied spread for earthquake CAT bonds: financial implications of engineering decisions....
- DeSarbo, W.S. and Cron, W.L. (1988). A maximum likelihood methodology for clusterwise linear regression. Journal of classification, 5, 249–282.
- Eaton, J.W., Bateman, D., Hauberg, S. and Wehbring, R. (2014). GNU Octave version 3.8.1 manual: a high-level interactive language for numerical...
- Franco, G. (2010). Minimization of trigger error in cat-in-a-box parametric earthquake catastrophe bonds with an application to Costa Rica....
- Franco, G. (2013). Construction of customized payment tables for cat-in-abox earthquake triggers as a basis risk reduction device. In Proceedings...
- Franco, G. (2014). Earthquake mitigation strategies through insurance. Chapter Encyclopedia of Earthquake Engineering. (pp. 1–18). Springer...
- Goda, K. (2013). Basis risk for earthquake catastrophe bond trigger using scenario-based versus station intensity-based approaches: a case...
- Goda, K. (2014). Seismic risk management of insurance portfolio using catastrophe bonds. Computer-Aided Civil and Infrastructure Engineering,...
- Grossi, P. and Kunreuther, H. (2005). Catastrophe Modeling: A New Approach to Managing Risk. Springer.
- Gunardi and Setiawan, E.P. (2015). Valuation of Indonesian catastrophic earthquake bonds with generalized extreme value (GEV) distribution...
- Guy Carpenter (2014). Chart: gap between economic and insured losses. http://www.gccapitalideas.com/ 2014/01/20/chart-gap-between-economic-and-insured-losses/.
- HaÌrdle, W.K. and Cabrera, B.L. (2010). Calibrating CAT bonds for Mexican earthquakes. Journal of Risk and Insurance, 77, 625–650.
- Hastie, T., Tibshirani, R. and Friedman, J. (2009). The Elements of Statistical Learning. (2nd ed.). Springer.
- Kotsiantis, S. (2007). Supervised machine learning: a review of classification techniques. Informatica, 31, 249–268.
- Lantz, B. (2015). Machine Learning with R. Packt Publishing Ltd.
- Pucciano, S., Franco, G. and Bazzurro, P. (under review). Loss predictive power for strong motion networks for usage in parametric risk transfer:...
- R Core Team (2012). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing Vienna, Austria. ISBN...
- Scilab Enterprises (2012). Scilab: Free and Open Source Software for Numerical Computation. Scilab Enterprises Orsay, France.
- Shao, J., Pantelous, A. and Papaioannou, A.D. (2015). Catastrophe risk bonds with applications to earthquakes. European Actuarial Journal,...
- Tao, X.X. and Tao, Z.R. (2005). Financial instruments integrated with engineering risk assessment for earthquake disaster reduction. WIT Transactions...
- Tao, Z., Tao, X. and Li, P. (2009). Pricing Model for Earthquake CAT Bonds. In International Conference on Business Intelligence and Financial...
- Wald, D. and Franco, G. (2017). Financial decision-making based on near-realtime earthquake information. In Proceedings of the 16th World...
- Wu, D. and Zhou, Y. (2010). Catastrophe bond and risk modeling: a review and calibration using Chinese earthquake loss data. Human and Ecological...
- Zimbidis, A.A., Frangos, N.E. and Pantelous, A.A. (2007). Modeling earthquake risk via extreme value theory and pricing the respective catastrophe...