OPTIMAL INSURANCE STRATEGIES: A HYBRID DEEP LEARNING MARKOV CHAIN APPROXIMATION APPROACH

DOI10.1017/asb.2020.9zbMath1447.91129OpenAlexW3021614052MaRDI QIDQ5119564

Zhuo Jin, Hailiang Yang, Xiang Cheng

Publication date: 31 August 2020

Published in: ASTIN Bulletin (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/asb.2020.9

zbMATH Keywords

neural networksMarkov chain approximationdeep learningreinsurance strategies

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Applications of continuous-time Markov processes on discrete state spaces (60J28) Actuarial mathematics (91G05)

Related Items

The balance property in neural network modelling, A hybrid deep learning method for optimal insurance strategies: algorithms and convergence analysis, A survey of numerical solutions for stochastic control problems: some recent progress, On optimality of barrier dividend control under endogenous regime switching with application to Chapter 11 bankruptcy, On de Finetti's optimal impulse dividend control problem under Chapter 11 bankruptcy, Optimal risk sharing and dividend strategies under default contagion: a semi-analytical approach

Uses Software

• Adam

Cites Work

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