Optimal insurance strategies : a hybrid deep learning Markov chain approximation approach

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<dc:creator>Cheng, Xiang </dc:creator>
<dc:creator>Jin, Zhuo</dc:creator>
<dc:creator>Yang, Hailiang</dc:creator>
<dc:date>2020-05-01</dc:date>
<dc:description xml:lang="es">Sumario: This paper studies deep learning approaches to find optimal reinsurance and dividend strategies for insurance companies. Due to the randomness of the financial ruin time to terminate the control processes, a Markov chain approximation-based iterative deep learning algorithm is developed to study this type of infinite-horizon optimal control problems. The optimal controls are approximated as deep neural networks in both cases of regular and singular types of dividend strategies. The framework of Markov chain approximation plays a key role in building the iterative equations and initialization of the algorithm. We implement our method to classic dividend and reinsurance problems and compare the learning results with existing analytical solutions. The feasibility of our method for complicated problems has been demonstrated by applying to an optimal dividend, reinsurance and investment problem under a high-dimensional diffusive model with jumps and regime switching.</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/171967.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Modelo de Markov</dc:subject>
<dc:subject xml:lang="es">Empresas de seguros</dc:subject>
<dc:subject xml:lang="es">Control estocástico</dc:subject>
<dc:subject xml:lang="es">Cálculo actuarial</dc:subject>
<dc:subject xml:lang="es">Reaseguro</dc:subject>
<dc:subject xml:lang="es">Algoritmos</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Optimal insurance strategies : a hybrid deep learning Markov chain approximation approach</dc:title>
<dc:relation xml:lang="es">En: Astin bulletin. - Belgium : ASTIN and AFIR Sections of the International Actuarial Association = ISSN 0515-0361. - 01/05/2020 Volumen 50 Número 2 - mayo 2020 , p. 449-477</dc:relation>
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