Univariate and bivariate GPD methods for predicting extreme wind storm losses

Insurance: Mathematics and Economics

Volumn 44, Issue 3, 2009, Pages 345-356

  Brodin, Erik ^a,b   Rootzén, Holger ^a,b  

^a CHALMERS UNIVERSITY OF TECHNOLOGY   (Sweden)

^b UNIVERSITY OF GOTHENBURG   (Sweden)

Author keywords

Extreme value statistics; Generalized Pareto distribution; Likelihood prediction intervals; Peaks over threshold; Trend analysis; Wind storm losses

Indexed keywords

EID: 67349212223     PISSN: 01676687     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.insmatheco.2008.11.002     Document Type: Article

References (16)

1. Beirlant J., Goegebeur Y., Segers J., Teugels, and J. Statistics of Extremes: Theory and Applications (2004), Wiley, New York
2. Bruun J.T., and Tawn J.A. Comparison of approaches for estimating the probability of coastal flooding. Journal of Royal Statistical Society Series C 47 Part 3 (1998) 405-423
3. Coles S.G. An Introduction to Statistical Modeling of Extreme Values (2001), Springer, London
4. Cossette H., Duchesne T., and Marceau E. Modeling catastrophes and their impact on insurance portfolios. North American Actuarial Journal 7 (2003) 1-22
5. Embrechts P., Klüppelberg C., and Mikosch T. Modelling Extremal Events for Insurance and Finance (1997), Springer, Berlin
6. Hall P., Peng L., and Tajvidi N. On prediction intervals based on predictive likelihood or bootstrap methods. Biometrika 86 (1999) 871-880
7. Hall P., Peng L., and Tajvidi N. Effect of extrapolation on coverage accuracy of prediction intervals computed from Pareto-type data. The Annals of Statistics 30 (2002) 875-895
8. Holmberg,, 2005. Sammanställning av stormskador på skog i Sverige under de senaste 210 åren. Report no. 9, Skogsvårdsstyrelsen, Skogsstyrelsens förlag 551 83 Jönköping
9. Jaffee, D.M., Russell, T., 1996. Catastrophe insurance, capital markets and uninsurable risk. Cummins, J.D. (Ed.) In: Proceedings of the Conference on Risk Management in Insurance Firms. Financial Institutions Center, The Wharton School, Philadelphia
10. Lescourret L., and Robert C. Extreme dependence of multivariate catastrophic losses. Scandinavian Actuarial Journal 4 (2006) 203-225
11. Lies, M., 2000. Storm over Europe An underestimated risk. Swiss Re
12. Rootzén H., and Tajvidi N. Extreme value statistics and wind storm losses: A case study. Scandinavian Actuarial Journal 1 (1997) 70-94
13. Rootzén H., and Tajvidi N. Can wind storm losses be predicted from meteorological observations?. Scandinavian Actuarial Journal 5 (2001) 162-175
14. Rootzén H., and Taijvidi N. Multivariate generalized Pareto distribution. Bernoulli 12 (2006) 917-930
15. Swedish Meteorological and Hydrological Institute (SMHI), 2005. Årsredovisning
16. Valinger, E., Ottosson Lövenius, M., Johansson, U., Fridman, J., Claeson, S., Gustafsson, Å, 2006. Analys av riskfaktorer efter stormen Gudrun. Report No. 8, Skogsvårdsstyrelsen, Skogsstyrelsens förlag 551 83 Jönköping