Graduate School of Economics

YAMADA Toshihiro

Papers

1.	Weak approximation of SDEs for tempered distributions and applications (Peer-reviewed) Yuga Iguchi, Toshihiro Yamada Advances in Computational Mathematics (to appear) 2022.5
2.	A weak approximation method for irregular functionals of hypoelliptic diffusions (Peer-reviewed) Naho Akiyama, Toshihiro Yamada Applied Numerical Mathematics 2022.2
3.	A new efficient approximation scheme for solving high-dimensional semilinear PDEs: control variate method for Deep BSDE solver (Peer-reviewed) Akihiko Takahashi, Yoshifumi Tsuchida, Toshihiro Yamada Journal of Computational Physics 2022.1
4.	A Gaussian Kusuoka-approximation without solving random ODEs (Peer-reviewed) Toshihiro Yamada SIAM Journal on Financial Mathematics 2022.1
5.	A deep learning-based high-order operator splitting method for high-dimensional nonlinear parabolic PDEs via Malliavin calculus: application to CVA computation (Peer-reviewed) Riu Naito, Toshihiro Yamada IEEE CIFEr 2022 2022
6.	Deep weak approximation of SDEs: a spatial approximation scheme for solving Kolmogorov equations (Peer-reviewed) Riu Naito, Toshihiro Yamada International Journal of Computational Methods 2022
7.	Numerical methods for backward stochastic differential equations: a survey Jared Chessari, Reiichiro Kawai, Yuji Shinozaki, Toshihiro Yamada arXiv 2022
8.	A high order weak approximation for jump-diffusions using Malliavin calculus and operator splitting (Peer-reviewed) Naho Akiyama, Toshihiro Yamada Monte Carlo Methods and Applications 2022
9.	Deep Asymptotic Expansion: application to financial mathematics (Peer-reviewed) Yuga Iguchi, Riu Naito, Yusuke Okano, Akihiko Takahashi, Toshihiro Yamada IEEE CSDE 2021 (to appear) 2021.12
10.	A higher order weak approximation of McKean-Vlasov type SDEs (Peer-reviewed) Riu Naito, Toshihiro Yamada BIT Numerical Mathematics 2021.6
11.	High order weak approximation for irregular functionals of time-inhomogeneous SDEs (Peer-reviewed) Toshihiro Yamada Monte Carlo Methods and Applications 2021
12.	Acceleration of automatic differentiation of solutions to parabolic partial differential equations: a higher order discretization (Peer-reviewed) Kimiki Tokutome, Toshihiro Yamada Numerical Algorithms Vol.86,pp.593-635 2021
13.	A second order discretization for degenerate systems of stochastic differential equations (Peer-reviewed) Yuga Iguchi, Toshihiro Yamada IMA Journal of Numerical Analysis 2021
14.	Discrete Bismut formula: Conditional integration by parts and a representation for delta hedging process (Peer-reviewed) Naho Akiyama, Toshihiro Yamada Risk and Decision Analysis 2021
15.	Operator splitting around Euler-Maruyama scheme and high order discretization of heat kernels (Peer-reviewed) Yuga Iguchi, Toshihiro Yamada ESAIM: Mathematical Modelling and Numerical Analysis Vol.55,pp.323-367 2021
16.	An acceleration scheme for deep learning-based BSDE solver using weak expansions (Peer-reviewed) Riu Naito, Toshihiro Yamada International Journal of Financial Engineering 2020
17.	A second order discretization with Malliavin weight and Quasi Monte Carlo method for option pricing (Peer-reviewed) Toshihiro Yamada, Kenta Yamamoto Quantitative Finance Vol.20,No.11 2020
18.	Second order discretization of Bismut-Elworthy-Li formula: application to sensitivity analysis (Peer-reviewed) Toshihiro Yamada, Kenta Yamamoto SIAM/ASA Journal on Uncertainty Quantification Vol.7,No.01,pp.143-173 2019
19.	A control variate method for weak approximation of SDEs via discretization of numerical error of asymptotic expansion (Peer-reviewed) Yusuke Okano, Toshihiro Yamada Monte Carlo Methods and Applications Vol.25,No.3 2019
20.	A second-order discretization for forward-backward SDEs using local approximations with Malliavin calculus (Peer-reviewed) Riu Naito, Toshihiro Yamada Monte Carlo Methods and Applications Vol.25,No.4 2019
21.	An arbitrary high order weak approximation of SDE and Malliavin Monte Carlo: analysis of probability distribution functions (Peer-reviewed) Toshihiro Yamada SIAM Journal on Numerical Analysis Vol.57,No.2,pp.563-591 2019
22.	A third-order weak approximation of multidimensional Ito stochastic differential equations (Peer-reviewed) Riu Naito, Toshihiro Yamada Monte Carlo Methods and Applications Vol.25,No.2,pp.97-120 2019
23.	Weak Milstein scheme without commutativity condition and its error bound (Peer-reviewed) Toshihiro Yamada Applied Numerical Mathematics Vol.131,No.2018 (September),pp.95-108 2018.9
24.	A second order weak approximation of SDEs using Markov chain without Levy area simulation (Peer-reviewed) Toshihiro Yamada, Kenta Yamamoto Monte Carlo Methods and Applications Vol.24,No.04,pp.289-308 2018
25.	A weak approximation with Malliavin weights for local stochastic volatility model (Peer-reviewed) Toshihiro Yamada International Journal of Financial Engineering Vol.04,No.01 2017
26.	A higher order weak approximation scheme of multidimensional stochastic differential equations using Malliavin weights (Peer-reviewed) Toshihiro Yamada Journal of Computational and Applied Mathematics Vol.321,No.September 2017,pp.427-447 2017
27.	A weak approximation with asymptotic expansion and multidimensional Malliavin weights (Peer-reviewed) Akihiko Takahashi, Toshihiro Yamada Annals of Applied Probability Vol.26,No.2,pp.818-856 2016
28.	An asymptotic expansion for forward–backward SDEs: a Malliavin calculus approach (Peer-reviewed) Akihiko Takahashi, Toshihiro Yamada Asia-Pacific Financial Markets Vol.23,No.4,pp.337-373 2016
29.	A formula of small time expansion for Young SDE driven by fractional Brownian motion (Peer-reviewed) Toshihiro Yamada Statistics and Probability Letters Vol.101,pp.64-72 2015
30.	On error estimates for asymptotic expansions with Malliavin weights: Application to stochastic volatility model (Peer-reviewed) Akihiko Takahashi, Toshihiro Yamada Mathematics of Operations Research Vol.40,No.3,pp.513-451 2015
31.	A small noise asymptotic expansion for Young SDE driven by fractional Brownian motion: A sharp error estimate with Malliavin calculus (Peer-reviewed) Toshihiro Yamada Stochastic Analysis and Applications Vol.33,No.5,pp.882-902 2015
32.	A Malliavin calculus approach with asymptotic expansion in computational finance (Peer-reviewed) Toshihiro Yamada Ph.D. Thesis, The University of Tokyo 2015
33.	An asymptotic expansion of forward-backward SDEs with a perturbed driver (Peer-reviewed) Akihiko Takahashi, Toshihiro Yamada International Journal of Financial Engineering Vol.2,No.2 2015
34.	A semigroup expansion for pricing barrier options (Peer-reviewed) Takashi Kato, Akihiko Takahashi, Toshihiro Yamada International Journal of Stochastic Analysis Vol.2014,pp.1-15 2014
35.	Strong convergence for Euler-Maruyama and Milstein schemes with asymptotic method (Peer-reviewed) Hideyuki Tanaka, Toshihiro Yamada International Journal of Theoretical and Applied Finance Vol.17,No.2,pp.1450014-1-1450014-22 2014
36.	An asymptotic expansion formula for up-and-out barrier option price under stochastic volatility model (Peer-reviewed) Takashi Kato, Akihiko Takahashi, Toshihiro Yamada JSIAM Letters Vol.5,pp.17-20 2013
37.	Pricing discrete barrier options under stochastic volatility (Peer-reviewed) Kenichiro Shiraya, Akihiko Takahashi, Toshihiro Yamada Asia-Pacific Financial Markets Vol.19,No.3,pp.205-232 2012.9
38.	A remark on approximation of the solutions to partial differential equations in finance (Peer-reviewed) Akihiko Takahashi, Toshihiro Yamada Recent Advances in Financial Engineering 2011 2012.6
39.	An asymptotic expansion with push-down of Malliavin weights (Peer-reviewed) Akihiko Takahashi, Toshihiro Yamada SIAM Journal on Financial Mathematics Vol.3,No.1,pp.95-136 2012.1

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Awards

Research Projects

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