Modeling Extreme Insurance Losses Using Transmutation and Copula

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Date

2023-01-01

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Abstract

In this dissertation, we apply transmutation to the theoretical work in insurance. From our extensive literature search, this seems to be a novel piece of work with regards to the transmutation, we particularly focus on the theoretical application of the exponential, Pareto and Weibull distributions. By shedding light on this unexplored area, our findings contribute valuable insights into the broader domain of insurance studies. We also do some exploratory work with regard to future research pursuit on a combined application of copula and transmutation to insurance data.

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Keywords

Bayesian, Copula, Insurance, Tail-Value-at-Risk, Transmutation, Value-at-Risk

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