Setting the optimal limit value of motor insurance coverage by stochastic optimization
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F18%3A10239543" target="_blank" >RIV/61989100:27510/18:10239543 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.7327/cerei.2018.03.01" target="_blank" >http://dx.doi.org/10.7327/cerei.2018.03.01</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.7327/cerei.2018.03.01" target="_blank" >10.7327/cerei.2018.03.01</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Setting the optimal limit value of motor insurance coverage by stochastic optimization
Popis výsledku v původním jazyce
In this paper, we provide an alternative to a passive approach to the selection of insurance products or policy con-ditions. Specifically, we propose a method to make a decision about the optimal limit value for motor insurance coverage. Respecting the stochastic nature of individual loss, we formulate a problem of stochastic programming in which the total potential financial loss of the policyholder is minimized. Actually, we present a general optimization problem in which various relevant probability distributions of individual loss may be considered. In addition, we extend the work of Valecký (2017) and derive an insurance rate that describes better the dependence between the pure premium and the given limit value under the assumption that the individual potential loss follows a gamma distribution. Because of the absence of a closed-form solution, sample average approximation is applied to the objective function and the optimal solution to this approximated (SAA) problem is determined. Finally, the quality of the obtained solution is assessed by approximation to the optimality gap representing the difference between our candidate and the true solution.
Název v anglickém jazyce
Setting the optimal limit value of motor insurance coverage by stochastic optimization
Popis výsledku anglicky
In this paper, we provide an alternative to a passive approach to the selection of insurance products or policy con-ditions. Specifically, we propose a method to make a decision about the optimal limit value for motor insurance coverage. Respecting the stochastic nature of individual loss, we formulate a problem of stochastic programming in which the total potential financial loss of the policyholder is minimized. Actually, we present a general optimization problem in which various relevant probability distributions of individual loss may be considered. In addition, we extend the work of Valecký (2017) and derive an insurance rate that describes better the dependence between the pure premium and the given limit value under the assumption that the individual potential loss follows a gamma distribution. Because of the absence of a closed-form solution, sample average approximation is applied to the objective function and the optimal solution to this approximated (SAA) problem is determined. Finally, the quality of the obtained solution is assessed by approximation to the optimality gap representing the difference between our candidate and the true solution.
Klasifikace
Druh
J<sub>ost</sub> - Ostatní články v recenzovaných periodicích
CEP obor
—
OECD FORD obor
50202 - Applied Economics, Econometrics
Návaznosti výsledku
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
Ostatní
Rok uplatnění
2018
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Ekonomická revue
ISSN
1212-3951
e-ISSN
—
Svazek periodika
21
Číslo periodika v rámci svazku
1
Stát vydavatele periodika
CZ - Česká republika
Počet stran výsledku
8
Strana od-do
5-12
Kód UT WoS článku
—
EID výsledku v databázi Scopus
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