Deep Neural Network Algorithms for Parabolic PIDEs and Applications in Insurance Mathematics

R\"udiger Frey and Verena K\"ock

Papers from arXiv.org

Abstract: In recent years a large literature on deep learning based methods for the numerical solution partial differential equations has emerged; results for integro-differential equations on the other hand are scarce. In this paper we study deep neural network algorithms for solving linear and semilinear parabolic partial integro-differential equations with boundary conditions in high dimension. To show the viability of our approach we discuss several case studies from insurance and finance.

Date: 2021-09, Revised 2021-09
New Economics Papers: this item is included in nep-big, nep-cmp, nep-ias and nep-isf
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2109.11403

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