Modelling extremal claim severity using generalized Pareto regression model

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F15%3A86094167" target="_blank" >RIV/61989100:27510/15:86094167 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Modelling extremal claim severity using generalized Pareto regression model

Popis výsledku v původním jazyce

The paper is focused on modelling claim severity in insurance in which it is crucial to cope with the occurrence of large claims to obtain a reliable and accurate model. We present an approach to modelling extremal claim severity using regression model based on the individual characteristics (rating factors) of policyholders because the model based on the risk theory for all claims is not as convenient when we need to obtain estimates of individual claims. Thus, we assume that the individual claim severity follows mixed distribution using the gamma distribution and generalized Pareto (GP) distribution with various parameters for all of the policyholders. However, while the claim frequency is known, the frequency of regular and extremal claims is not. So, we also present a method how to identify the threshold value (location parameter of GP distribution) which de nes the extremal claims and we estimate the generalized Pareto regression model for extremal events using the real block of motor hull insurance policies.

Název v anglickém jazyce

Modelling extremal claim severity using generalized Pareto regression model

Popis výsledku anglicky

The paper is focused on modelling claim severity in insurance in which it is crucial to cope with the occurrence of large claims to obtain a reliable and accurate model. We present an approach to modelling extremal claim severity using regression model based on the individual characteristics (rating factors) of policyholders because the model based on the risk theory for all claims is not as convenient when we need to obtain estimates of individual claims. Thus, we assume that the individual claim severity follows mixed distribution using the gamma distribution and generalized Pareto (GP) distribution with various parameters for all of the policyholders. However, while the claim frequency is known, the frequency of regular and extremal claims is not. So, we also present a method how to identify the threshold value (location parameter of GP distribution) which de nes the extremal claims and we estimate the generalized Pareto regression model for extremal events using the real block of motor hull insurance policies.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

<a href="/cs/project/EE2.3.20.0296" target="_blank" >EE2.3.20.0296: Výzkumný tým pro modelování ekonomických a finančních procesů na VŠB-TU Ostrava</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Mathematical Methods in Economics, MME 2015 : 33rd international conference : conference proceedings : Cheb, Czech Republic, September 9-11, 2015

ISBN

978-80-261-0539-8

ISSN

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e-ISSN

neuvedeno

Počet stran výsledku

5

Strana od-do

1-5

Název nakladatele

University of West Bohemia

Místo vydání

Plzeň

Místo konání akce

Cheb

Datum konání akce

9. 9. 2015

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

000387898900148