📊 Financial Dashboard - Market Analyzer

Complete Streamlit application for financial market analysis with technical visualization, portfolio management, and sentiment analysis.

✨ Main features

📈 Individual dashboards

Advanced technical analysis (MA, RSI, Bollinger Bands) with interactive Plotly visualizations

🔍 Multi-asset comparison

Comparative analysis and asynchronous data download

💼 Virtual portfolio

Multi-asset portfolio simulation, performance/risk analysis and geographical mapping

📰 Market analysis

Reddit sentiment (simulated), financial news and macroeconomic context

🎨 Advanced customization

7 unique visual themes to customize the interface

Neon Cyberpunk :

Lava Explosion :

Electric Ocean :

Acid Jungle :

Galactic Purple :

Retro Dark :

Crypto Fever :

Installation

1. Clone the repository :

git clone https://github.com/BuyukHasan/bourse_dashboard
cd bourse_dashboard

2. Create a virtual environment :

python -m venv venv
source venv/bin/activate  # Linux/Mac
venv\Scripts\activate    # Windows

3. Install the dependencies :

pip install -r requirements.txt

4. Launch the application :

streamlit run app.py

🚀 Usage

Available modes

• Individual dashboard : Technical analysis of an asset
• Multi-asset comparison : Comparison of multiple instruments
• Virtual portfolio : Investment strategy simulation
• Unit tests : Module validation

Useful commands

• Rerun : Button r(from the dashboard)
• Clear cache: Button c then confirm the instruction on the page (from the dashboard)
• Stop application: Control + c (from the terminal where you launched streamlit run app.py)

🧩 File structure

financial-dashboard/
├── app.py                # Main entry point
├── requirements.txt      # Dependencies
├── .gitignore
└── src/                  # Folder containing all the project classes
    ├── asset_categories.py   # Asset classification by sector
    ├── css.py                # Visual theme management
    ├── dashboard.py          # Main dashboard module
    ├── data_fetcher.py       # Data retrieval (yfinance)
    ├── geo_data.py           # Geographical data
    ├── macro_data.py         # Macroeconomic data
    ├── news_fetcher.py       # News collection
    ├── portfolio_manager.py  # Portfolio management
    ├── reddit_analyzer.py    # Sentiment analysis (simulated)
    ├── technical_analyzer.py # Technical indicator calculations
    └── visualizer.py         # Graph visualizations

🛠 Main Dependencies

• streamlit==1.47.0 - Web interface
• yfinance==0.2.65 - Financial data
• plotly==6.2.0 - Interactive visualizations
• pandas==2.3.0 - Data manipulation
• numpy==2.2.2 - Scientific calculations

🤝 Contribution

Contributions are welcome! Recommended process:

1. Forker the project
2. Create a branch : git checkout -b feature/new-feature
3. Commit your changes : git commit -m 'Add an awesome feature'
4. Push to the branch : git push origin feature/new-feature
5. Open a Pull Request

📜 Licence

This project is licensed under the MIT License. See the LICENSE file for details.

Note : While the MIT license is permissive, an email notification (buyukh7723@gmail.com) is appreciated for significant reuse. I generally accept as long as I am notified.