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Recent developments in stochastic nu...
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Akahori, Jiro.
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Recent developments in stochastic numerics and computational finance
Record Type:
Electronic resources : Monograph/item
Title/Author:
Recent developments in stochastic numerics and computational finance/ edited by Jiro Akahori, Syoiti Ninomiya, Toshihiro Yamada.
other author:
Akahori, Jiro.
Published:
Singapore :Springer Nature Singapore : : 2025.,
Description:
vii, 124 p. :ill., digital ;24 cm.
[NT 15003449]:
Chapter 1 Policy improvement algorithm for an optimal consumption and investment problem under a certain nonlinear stochastic factor model -- Chapter 2 An extended Milstein scheme for effective weak approximation of diffusions -- Chapter 3 Expansion of Bermudan option price using deep learning -- Chapter 4 Approximation for stochastic PDES and the HJM Model -- Chapter 5 On a Prolongation of the Nonlinear Stochastic Asymptotic Expansion of the Solution of a Semilinear PDE.
Contained By:
Springer Nature eBook
Subject:
Stochastic processes - Congresses. -
Online resource:
https://doi.org/10.1007/978-981-95-0652-1
ISBN:
9789819506521
Recent developments in stochastic numerics and computational finance
Recent developments in stochastic numerics and computational finance
[electronic resource] /edited by Jiro Akahori, Syoiti Ninomiya, Toshihiro Yamada. - Singapore :Springer Nature Singapore :2025. - vii, 124 p. :ill., digital ;24 cm. - ICIAM2023 springer series,v. 63091-3101 ;. - ICIAM2023 springer series ;v. 6..
Chapter 1 Policy improvement algorithm for an optimal consumption and investment problem under a certain nonlinear stochastic factor model -- Chapter 2 An extended Milstein scheme for effective weak approximation of diffusions -- Chapter 3 Expansion of Bermudan option price using deep learning -- Chapter 4 Approximation for stochastic PDES and the HJM Model -- Chapter 5 On a Prolongation of the Nonlinear Stochastic Asymptotic Expansion of the Solution of a Semilinear PDE.
This book presents a collection of recent advances in stochastic numerical analysis and computational finance. Stochastic numerical methods have played a pivotal role in probability theory, statistics, and applied mathematics, particularly in the rapidly evolving fields of machine learning and data science. They have also achieved significant success in computational finance. The volume highlights cutting-edge developments in numerical techniques for stochastic differential equations and stochastic models in finance. This collection offers valuable insights for researchers and practitioners seeking to deepen their understanding of stochastic modeling and its applications in finance and beyond.
ISBN: 9789819506521
Standard No.: 10.1007/978-981-95-0652-1doiSubjects--Topical Terms:
664186
Stochastic processes
--Congresses.
LC Class. No.: QA274.A1
Dewey Class. No.: 519.23
Recent developments in stochastic numerics and computational finance
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Chapter 1 Policy improvement algorithm for an optimal consumption and investment problem under a certain nonlinear stochastic factor model -- Chapter 2 An extended Milstein scheme for effective weak approximation of diffusions -- Chapter 3 Expansion of Bermudan option price using deep learning -- Chapter 4 Approximation for stochastic PDES and the HJM Model -- Chapter 5 On a Prolongation of the Nonlinear Stochastic Asymptotic Expansion of the Solution of a Semilinear PDE.
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This book presents a collection of recent advances in stochastic numerical analysis and computational finance. Stochastic numerical methods have played a pivotal role in probability theory, statistics, and applied mathematics, particularly in the rapidly evolving fields of machine learning and data science. They have also achieved significant success in computational finance. The volume highlights cutting-edge developments in numerical techniques for stochastic differential equations and stochastic models in finance. This collection offers valuable insights for researchers and practitioners seeking to deepen their understanding of stochastic modeling and its applications in finance and beyond.
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