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Estimating Extreme Losses for the Florida Public Hurricane Model

Authors:

Sneh Gulati ,

Department of Mathematics and Statistics, Florida International University, Miami, FL 33199,, US
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Florence George,

Department of Mathematics and Statistics, Florida International University, Miami, FL 33199,, US
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Fan Yang,

Department of Mathematics and Statistics, Florida International University, Miami, FL 33199,, US
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B. M. Golam Kibria,

Department of Mathematics and Statistics, Florida International University, Miami, FL 33199,, US
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Shahid Hamid

Department of Finance, Florida International University, Miami, FL 33199, US
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Abstract

While the world thinks of coastal Florida as a paradise and retirement haven, residents in these areas don’t always agree with that depiction. Living under the threat of hurricanes for six months of the year and paying enormous sums of money for wind storm insurance is not exactly paradise. However this has not deterred people from wanting a piece of paradise and migration to Florida has continued unabated. Exposure has increased significantly along coastal regions causing insurance companies to reevaluate their risks. They still focus on estimation of annual insured loss, but increasingly they want to be prepared for extreme losses. This paper attempts to look at various methods of estimating extreme quantiles of the loss distribution in the Public Hurricane Loss Model. Both nonparametric and parametric models are used to estimate the catastrophic quantiles and then compared for accuracy. We found that the Weibull distribution fitted the data very well compare to simple exponential and GDP distributions.

DOI: http://dx.doi.org/10.4038/sljastats.v5i4.7793

DOI: http://doi.org/10.4038/sljastats.v5i4.7793
How to Cite: Gulati, S. et al., (2014). Estimating Extreme Losses for the Florida Public Hurricane Model. Sri Lankan Journal of Applied Statistics. 5(4), pp.247–271. DOI: http://doi.org/10.4038/sljastats.v5i4.7793
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Published on 15 Dec 2014.
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