Recent Developments in Stochastic Numerics and Computational Finance / edited by Jiro Akahori, Syoiti Ninomiya, Toshihiro Yamada.

Format:

Book

Author/Creator:

Akahori, Jiro.

Contributor:

Akahori

Series:

ICIAM2023 Springer Series, 3091-3101 ; 6

Language:

English

Subjects (All):

Mathematics--Data processing.

Mathematics.

Probabilities.

Computational Mathematics and Numerical Analysis.

Probability Theory.

Local Subjects:

Computational Mathematics and Numerical Analysis.

Probability Theory.

Physical Description:

1 online resource (209 pages)

Edition:

1st ed. 2025.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2025.

Summary:

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.

Contents:

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.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

981-9506-52-2

9789819506521

OCLC:

1568061395