Deep Asymptotic Expansion: Application to Financial Mathematicsï¼ˆforthcoming in proceedings of IEEE CSDE 2021)
Akihiko Takahashi and
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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
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.
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Persistent link: https://EconPapers.repec.org/RePEc:cfi:fseres:cf523
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