A Deep Neural Network Algorithm for Semilinear Elliptic PDEs with Applications in Insurance Mathematics

A Deep Neural Network Algorithm for Semilinear Elliptic PDEs with Applications in Insurance Mathematics

In insurance mathematics, optimal control problems over an infinite time horizon arise when computing risk measures. An example of such a risk measure is the expected discounted future dividend payments. In models which take multiple economic factors into account, this problem is high-dimensional. T...

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Bibliographic Details
Main Authors: Stefan Kremsner, Alexander Steinicke, Michaela Szölgyenyi
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Risks
Subjects:
backward stochastic differential equations
semilinear elliptic partial differential equations
stochastic optimal control
unbounded random terminal time
machine learning
deep neural networks
Online Access:https://www.mdpi.com/2227-9091/8/4/136

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https://www.mdpi.com/2227-9091/8/4/136

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