DNN expression rate analysis of high-dimensional PDEs: application to option pricing

DOI10.1007/s00365-021-09541-6zbMath1500.35009arXiv1809.07669OpenAlexW2890291741WikidataQ114229769 ScholiaQ114229769MaRDI QIDQ2117328

Arnulf Jentzen, Philipp Grohs, Christoph Schwab, Dennis Elbrächter

Publication date: 21 March 2022

Published in: Constructive Approximation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1809.07669

zbMATH Keywords

option pricingneural network approximationlow-rank approximationhigh-dimensional PDEs

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Theoretical approximation in context of PDEs (35A35) Numerical integration (65D30) Second-order parabolic equations (35K10) PDEs in connection with game theory, economics, social and behavioral sciences (35Q91) PDEs on graphs and networks (ramified or polygonal spaces) (35R02) Weighted approximation (41A81)

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Uses Software

• DGM

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