An AI-powered stock analytics and quantitative trading dashboard for the Nigerian Stock Exchange (NGX).
This project is a full-stack data analytics and quant research system that:
- Processes historical stock data
- Generates trading signals (BUY / SELL / HOLD)
- Builds a ranking engine
- Simulates a dynamic portfolio strategy
- Provides risk and performance analytics
- Includes an AI assistant for market insights
- Top-performing stocks
- BUY signal detection
- Risk classification
- Multi-stock comparison
- Cross-sectional ranking model
- Momentum + volatility + forecast scoring
- Confidence scoring system
- Dynamic equal-weight portfolio
- Weekly rebalancing
- Transaction cost modelling
- Minimum holding period logic
- Turnover control (Step 5A & 5B)
- Ask questions like:
- "Top BUY stocks?"
- "Compare GTCO and DANGSUGAR"
- "What is the riskiest stock?"
- Python
- Pandas / NumPy
- Plotly
- Streamlit
- Quantitative Finance Logic
stock-market-analytics/ │ ├── data/ # Raw stock data ├── outputs/ # Processed outputs & backtests ├── scripts/ # Data processing scripts ├── dashboard.py # Main Streamlit dashboard ├── EDA.py # Exploratory data analysis ├── requirements.txt └── README.md
pip install -r requirements.txt
streamlit run dashboard.py
📌 Project Goal
To build a quantitative trading intelligence system that evolves into:
Portfolio analytics tool
AI-powered trading assistant
NGX quant research platform
📈 Future Improvements
Factor models (Fama-French style)
Walk-forward testing
Sector rotation strategies
ML-based signal prediction
👤 Author
Seun Oseola
Data Analyst | Quant Analytics Enthusiast