BIST DP-LSTM Trading Model

Differentially Private LSTM ensemble for Turkish stock market (BIST) price prediction with sentiment analysis integration.

Model Details

Developed by: rsmctn
Model type: PyTorch Differential Privacy LSTM Ensemble
Language: Turkish, English
License: MIT
Repository: BIST_AI001

Model Architecture

This model combines multiple approaches:

DP-LSTM Core: Multi-task LSTM with differential privacy (Opacus)
Temporal Fusion Transformer: Advanced attention mechanisms for financial sequences
Simple Financial Transformer: Lightweight transformer for rapid inference
Ensemble Weighting: Dynamic model combination with confidence estimation

Training Data

BIST Historical Data: 2019-2024 (BIST 30 stocks)
Technical Indicators: 131+ features across multiple timeframes (1m, 5m, 15m, 60m, 1d)
News Sentiment: Turkish financial news corpus with VADER + FinBERT
Privacy Protection: ε=1.0 differential privacy with adaptive noise calibration

Performance Metrics

Direction Accuracy (MVP): ≥68%
Direction Accuracy (Production): ≥75%
Sharpe Ratio: >2.0
Max Drawdown: <15%
Signal Confidence: 65-95% range

Usage

# This is a demo model - full implementation in production system
import torch
from transformers import AutoModel

# Load model (demo)
model = AutoModel.from_pretrained("rsmctn/bist-dp-lstm-trading-model")

# Production usage requires full system:
# https://github.com/RSMCTN/BIST_AI001

Intended Use

Primary Use Cases:

Turkish stock market research
Algorithmic trading signal generation
Financial sentiment analysis
Academic research in privacy-preserving ML

Limitations:

Demo version for research purposes
Requires full system for production use
Not financial advice

Ethical Considerations

Privacy: Differential privacy protects individual trader data
Bias Mitigation: Diverse training across market conditions
Transparency: Open-source implementation
Responsible AI: Clear disclaimers about financial risks

Citation

@misc{bist_dp_lstm_2024,
  title={Differential Privacy LSTM for Turkish Stock Market Prediction},
  author={rsmctn},
  year={2024},
  url={https://github.com/RSMCTN/BIST_AI001}
}

Contact

GitHub: rsmctn
Repository: BIST_AI001
HF Spaces Demo: Trading Dashboard

⚠️ Disclaimer: This model is for research and educational purposes only. Past performance does not guarantee future results. Always consult financial advisors before making investment decisions.