Overview
A sophisticated machine learning system for predicting stock prices using advanced algorithms and technical analysis indicators.
Key features
- Multiple ML Models: LSTM, GRU, and traditional algorithms
- Technical Indicators: RSI, MACD, Moving Averages, Bollinger Bands
- Data Processing: Real-time data fetching and preprocessing
- Visualization: Interactive charts and performance metrics
- Backtesting: Historical performance validation
- Risk Assessment: Volatility and risk metrics calculation
Technical decisions
- Deep Learning Models: LSTM and GRU for time series prediction
- Feature Engineering: Technical indicators and market sentiment
- Data Sources: Multiple financial APIs for comprehensive data
- Performance Metrics: Accuracy, MSE, MAE, and Sharpe ratio
- Visualization: Matplotlib and Plotly for data representation
- Model Optimization: Hyperparameter tuning and cross-validation
Gallery
Outcome
- Achieved high prediction accuracy on multiple stock indices
- Implemented advanced feature engineering techniques
- Developed comprehensive backtesting framework
- Created intuitive visualization dashboard
