Scholarlink

In this study, we explored the use of neural networks to predict option prices, in particular European put options. Using a combination of data generation and pre-processing methods, we created a dataset representative of possible market conditions. We then trained a neural network model with advanced regularization and optimization techniques to predict option prices. The results show excellent model performance, with evaluation metrics such as MSE, RMSE, and coefficient of determination (R2) indicating high prediction accuracy. This research demonstrates the potential of neural networks to capture complex relationships between financial variables, offering promising prospects for practical applications in quantitative finance.

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

Pricing European Put Options Using Deep Neural Networks: An Application of the Black-Scholes Model

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Zakaria Elbayed,
  • Abdelmjid Qadi El Idrissi

摘要

In this study, we explored the use of neural networks to predict option prices, in particular European put options. Using a combination of data generation and pre-processing methods, we created a dataset representative of possible market conditions. We then trained a neural network model with advanced regularization and optimization techniques to predict option prices. The results show excellent model performance, with evaluation metrics such as MSE, RMSE, and coefficient of determination (R2) indicating high prediction accuracy. This research demonstrates the potential of neural networks to capture complex relationships between financial variables, offering promising prospects for practical applications in quantitative finance.