MarketMind is a sophisticated LSTM-based prediction system that analyzes historical stock prices, external economic indicators, and tech industry sentiment to forecast stock movements for major technology companies.
- Multi-factor LSTM model incorporating market data and economic indicators
- Sentiment analysis integration from finance news sources
- Interactive visualization dashboard with prediction confidence intervals
- Comprehensive backtesting and model evaluation
- Modular architecture for extensibility and maintenance
# Clone the repository
git clone https://github.com/yourusername/MarketMind.git
cd MarketMind
# Create a virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt# Example code for running a prediction
from marketmind.models.lstm_model import LSTMPredictor
from marketmind.data_acquisition.stock_data import fetch_stock_data
# Fetch data
data = fetch_stock_data(symbol="AAPL", start_date="2020-01-01")
# Initialize and train model
model = LSTMPredictor()
model.train(data)
# Make predictions
predictions = model.predict(days=30)MarketMind/
├── marketmind/ # Main package
│ ├── data_acquisition/ # Data fetching modules
│ ├── preprocessing/ # Data preparation and feature engineering
│ ├── models/ # LSTM and other prediction models
│ ├── visualization/ # Interactive visualization tools
│ ├── evaluation/ # Backtesting and performance metrics
│ └── utils/ # Helper functions
├── data/ # Data directory
│ ├── raw/ # Raw collected data
│ ├── processed/ # Processed and engineered features
│ └── models/ # Saved model states
├── notebooks/ # Jupyter notebooks for analysis
├── tests/ # Unit tests
├── requirements.txt # Project dependencies
├── config.yaml # Configuration parameters
└── README.md # Project documentation
IMPORTANT: MarketMind is an educational project developed for demonstrating machine learning techniques in finance. The predictions made by this system should NOT be considered financial advice. Stock markets are inherently volatile and unpredictable, and no algorithm can consistently predict market movements with high accuracy. Users should exercise their own judgment and consult qualified financial advisors before making investment decisions.
MIT
- Vedant Agarwal