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~subject:"Malliavin calculus"
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Malliavin calculus
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ECONIS (ZBW)
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New asymptotic expansion formula via Malliavin calculus and its application to rough differential equation driven by fractional Brownian motion
Takahashi, Akihiko
;
Yamada, Toshihiro
-
2023
-
This version: July 3, 2023
Persistent link: https://www.econbiz.de/10014383870
Saved in:
2
A general computation scheme for a high-order asymptotic expansion method
Takahashi, Akihiko
;
Takehara, Kohta
;
Toda, Masashi
- In:
International journal of theoretical and applied finance
15
(
2012
)
6
,
pp. 1-25
Persistent link: https://www.econbiz.de/10009672591
Saved in:
3
A remark on approximation of the solutions to partial differential equations in finance
Takahashi, Akihiko
;
Yamada, Toshihiro
- In:
Recent advances in financial engineering 2011: …
,
(pp. 133-181)
.
2012
Persistent link: https://www.econbiz.de/10009573432
Saved in:
4
An asymptotic expansion of forward-backward SDEs with a perturbed driver
Takahashi, Akihiko
;
Yamada, Toshihiro
- In:
International journal of financial engineering
2
(
2015
)
2
,
pp. 1-29
Persistent link: https://www.econbiz.de/10011333428
Saved in:
5
On error estimates for asymptotic expansions with Malliavin weights : application to stochastic volatility model
Takahashi, Akihiko
;
Yamada, Toshihiro
- In:
Mathematics of operations research
40
(
2015
)
3
,
pp. 513-541
Persistent link: https://www.econbiz.de/10011338705
Saved in:
6
An asymptotic expansion for forward-backward SDEs : a malliavin calculus approach
Takahashi, Akihiko
;
Yamada, Toshihiro
- In:
Asia-Pacific financial markets
23
(
2016
)
4
,
pp. 337-373
Persistent link: https://www.econbiz.de/10011619975
Saved in:
7
Portfolio optimization with choice of a probability measure
Saito, Taiga
;
Takahashi, Akihiko
-
2020
-
Revised in December 2021 and March 2022
Persistent link: https://www.econbiz.de/10013336334
Saved in:
8
Asymptotic expansion and deep neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with nonlinear coefficients
Takahashi, Akihiko
;
Yamada, Toshihiro
-
2021
Persistent link: https://www.econbiz.de/10013336341
Saved in:
9
Deep asymptotic expansion with weak approximation
Iguchi, Yuga
;
Naito, Riu
;
Okano, Yusuke
;
Yamada, Toshihiro
-
2021
-
Revised in August 2021
Persistent link: https://www.econbiz.de/10013336343
Saved in:
10
Solving Kolmogorov PDEs without the curse of dimensionality via deep learning and asymptotic expansion with Malliavin calculus
Takahashi, Akihiko
;
Yamada, Toshihiro
-
2023
-
This version: May 9, 2023
Persistent link: https://www.econbiz.de/10014289121
Saved in:
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