Année
2025
Rôle
End-to-end — feature engineering, model, training pipeline
Technologies
- PyTorch
- Transformer
- Time2Vec
- MACD
- RSI
- Bollinger Bands
- ATR
Financial machine learning
Quantitative Trading System
A quantitative trading system built from scratch in PyTorch: a Transformer that predicts BUY/SELL/HOLD signals from financial indicators and historical trading data.
- A quantitative trading system built from scratch in PyTorch using a Transformer model to predict BUY/SELL/HOLD signals from financial indicators and historical trading data, with a processing pipeline of 3.4M training samples and 351K development samples.
- The system incorporates features such as log-volume, technical indicators (MACD, RSI, Bollinger Bands, ATR), and Time2Vec with two-step normalization.
- Achieved Validation Accuracy of 92.75% and Test Accuracy of 92.50%.
- Validation accuracy
- 92.75%
- Test accuracy
- 92.50%
- Training samples
- 3.4M
- plus 351K development samples
