Scholarlink

The paper proposes a new pricing algorithm for high-dimensional Bermudan options based on an expansion method of Wiener functionals and deep learning which is a version of weak approximation scheme of Naito and Yamada, Journal of Computational Finance (2024). The proposed method gives efficient and accurate approximations for Bermudan option prices even in a high-dimensional setting. The theoretical rate of convergence of the proposed method is provided. Numerical experiments including a 100-dimensional stochastic volatility model confirm the validity of the proposed method.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Expansion of Bermudan Option Price Using Deep Learning

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Riu Naito,
  • Toshihiro Yamada

摘要

The paper proposes a new pricing algorithm for high-dimensional Bermudan options based on an expansion method of Wiener functionals and deep learning which is a version of weak approximation scheme of Naito and Yamada, Journal of Computational Finance (2024). The proposed method gives efficient and accurate approximations for Bermudan option prices even in a high-dimensional setting. The theoretical rate of convergence of the proposed method is provided. Numerical experiments including a 100-dimensional stochastic volatility model confirm the validity of the proposed method.