Title
Aggregation Of Dependent Risks With Heavy-Tail Distributions
Abstract
Straightforward methods to evaluate risks arising from several sources are specially difficult when risk components are dependent and, even more if that dependence is strong in the tails. We give an explicit analytical expression for the probability distribution of the sum of non-negative losses that are tail-dependent. Our model allows dependence in the extremes of the marginal beta distributions. The proposed model is flexible in the choice of the parameters in the marginal distribution. The estimation using the method of moments is possible and the calculation of risk measures is easily done with a Monte Carlo approach. An illustration on data for insurance losses is presented.
Year
DOI
Venue
2019
10.1142/S021848851940004X
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
Keywords
Field
DocType
Risk analysis, extremes, beta distribution, sum of losses
Statistical physics,Discrete mathematics,Heavy-tailed distribution,Mathematics
Journal
Volume
Issue
ISSN
27
Supplement-1
0218-4885
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Montserrat Guillen1497.83
José María Sarabia2367.61
Faustino Prieto3102.08
Vanesa Jord 'a400.34