Deep Asymptotic Expansion: Application to Financial Mathematics

Yuga Iguchi, Riu Naito, Yusuke Okano, Akihiko Takahashi and Toshihiro Yamada
Additional contact information
Yuga Iguchi: MUFG Bank and UCL London
Riu Naito: Japan Post Insurance and Hitotsubashi University
Yusuke Okano: SMBC Nikko Securities
Akihiko Takahashi: Faculty of Economics, The University of Tokyo
Toshihiro Yamada: Graduate School of Economics, Hitotsubashi University and Japan Science and Technology Agency (JST)

No CIRJE-F-1178, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: The paper proposes a new computational scheme for diffusion semigroups based on an asymptotic expansion with weak approximation and deep learning algorithm to solve high- dimensional Kolmogorov partial differential equations (PDEs). In particular, we give a spatial approximation for the solution of d-dimensional PDEs on a range [a,b]d without suffering from the curse of dimensionality.

Pages: 7 pages
Date: 2021-11
New Economics Papers: this item is included in nep-big and nep-cmp
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:tky:fseres:2021cf1178

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