🚀 TradeRewind is an AI-powered trading assistant that helps traders analyze mistakes, predict stock prices, simulate alternative scenarios, and receive expert trading insights. Upload your trade history and let TradeRewind do the rest!
✅ Trading Performance Metrics: Win rate, profit/loss, risk-reward ratio, and more.
✅ AI-Powered Stock Price Forecasting: Predict future stock trends using historical data.
✅ Trading Behavior Analysis: Uses AI clustering to categorize your trading style.
✅ What-If Scenario Simulator: See how different trade decisions could have affected your profits.
✅ Risk & Money Management Insights: Learn best practices for minimizing risk.
✅ AI Trading Coach: Get AI-driven trading advice based on your history.
| Component | Technology/Library |
|---|---|
| Frontend | Streamlit UI |
| Machine Learning | Scikit-learn, Prophet (Forecasting) |
| Data Processing | Pandas, NumPy |
| Stock Data | Yahoo Finance API |
| Backend | Python, Flask (Optional) |
| Hosting | Streamlit Cloud, Hugging Face Spaces |
git clone https://github.com/LlamaWritesCode/TradeRewind.git cd TradeRewind
python -m venv venv source venv/bin/activate # MacOS/Linux venv\Scripts\activate # Windows
pip install -r requirements.txt
1️⃣ Create a .env file in the src/ directory:
touch src/.env
2️⃣ Add your API key inside:
API_KEY=your_secret_api_key_here
streamlit run src/app.py
🎉 The app should now be running at http://localhost:8501
1️⃣ Upload your trade history (CSV).
2️⃣ Analyze mistakes, profits, and trading behavior.
3️⃣ Get AI-powered forecasts for stock trends.
4️⃣ Run "What-If" scenarios to test different trade strategies.
5️⃣ Receive AI Trading Coach insights to improve your decisions.
| Ticker | Buy Date | Sell Date | Buy Price | Sell Price | Allocation |
|---|---|---|---|---|---|
| AAPL | 2024-01-01 | 2024-01-10 | 150 | 165 | 20% |
| GOOGL | 2024-02-05 | 2024-02-15 | 2800 | 2750 | 30% |
📝 MIT License - Feel free to use, modify, and distribute!
LlamaWritesCode
🔗 GitHub