Predicting the Nikkei: A NumPy-Powered Deep Learning Journey

research #deep learning 📝 Blog|Analyzed: Feb 12, 2026 06:15•

Published: Feb 12, 2026 06:12

•

1 min read

Analysis

This article details an exciting project using only Python and NumPy to build a Deep Neural Network (DNN) for predicting the Nikkei 225 index based on USD/JPY exchange rates. The innovative approach uses percentage changes rather than absolute values to improve model accuracy and generalizability, promising a more robust financial prediction model.

Key Takeaways

•The project aims to build a DNN from scratch using only Python and NumPy.
•It leverages percentage changes of financial data for improved model performance.
•The ultimate goal is to run the model on an STM32 microcontroller.

Reference / Citation

View Original

"Instead of absolute values (price itself), "percentage change (rate of change)" or "logarithmic return" is used for input and output, making it a more versatile model."

Qiita DLFeb 12, 2026 06:12

* Cited for critical analysis under Article 32.

Older

Microsoft Pioneers AI Self-Sufficiency: Focusing on Enterprise and Healthcare

Newer

Effortlessly Switch Your Generative AI Connections with CC Switch