Premium control with reinforcement learning

We consider a premium control problem in discrete time, formulated in terms of a Markov decision process. In a simplified setting, the optimal premium rule can be derived with dynamic programming methods. However, these classical methods are not feasible in a more realistic setting due to the dimens...

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Vydané v:	ASTIN Bulletin : The Journal of the IAA Ročník 53; číslo 2; s. 233 - 257
Hlavní autori:	Palmborg, Lina, Lindskog, Filip
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, USA Cambridge University Press 01.05.2023
Predmet:	Actuarial science Approximation Control algorithms Deep learning Dividends Dynamical systems Hedging Insurance premiums Markov analysis Markov decision process matematisk statistik Mathematical Statistics Mutual insurance companies Premium control Present value Probability reinforcement learning Stochastic control theory Stochastic models Teaching methods Markov decision process Premium control C60 G22 reinforcement learning
ISSN:	0515-0361, 1783-1350, 1783-1350
On-line prístup:	Získať plný text
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