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.

Autorentext

Jiro Akahori is a professor of Graduate School of Mathematical Sciences at Ritsumeikan University.

Syoiti Ninomiya is a professor of Department of Mathematics, Institute of Science Tokyo.

Toshihiro Yamada is a professor of Graduate School of Economics at Hitotsubashi University.