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Deep Asymptotic Expansion: Application to Financial Mathematics(forthcoming in proceedings of IEEE CSDE 2021)

Yuga Iguchi, Riu Naito, Yusuke Okano, Akihiko Takahashi and Toshihiro Yamada
Additional contact information
Yuga Iguchi: MUFG Bank, Tokyo, Japan & UCL London, UK
Riu Naito: Japan Post Insurance & Hitotsubashi University, Tokyo, Japan
Yusuke Okano: SMBC Nikko Securities, Tokyo, Japan
Akihiko Takahashi: University of Tokyo, Tokyo, Japan
Toshihiro Yamada: Hitotsubashi University & JST, Tokyo, Japan

No CARF-F-523, CARF F-Series from Center for Advanced Research in Finance, Faculty of Economics, The 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 highdimensional 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
Date: 2021-11
New Economics Papers: this item is included in nep-big and nep-cmp
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