This project demonstrates portfolio analysis using Python. It includes data collection, performance measurement, risk assessment, optimization, and visualization.
- data/: Contains data files.
- notebooks/: Jupyter Notebooks for analysis.
- scripts/: These scripts involve automating portfolio analysis tasks such as performing calculations and statistical analysis, and generating visualizations.
Data Collection and Portfolio Sample Creation Performance Measurement Risk Assessment Portfolio Optimization Data Visualization
numpy pandas matplotlib seaborn scipy jupyter
- data_collection scripts load and pre-process the stock data.
- performance measurement calculates the performance metrics of the porfolio.
- risk_assessment measures the risk on the portfolio.
- optimization performs porfolio optimazation
Usage
- Place your stock data in the data/ directory as stock_data.csv.
- Run the main script to execute the complete analysis:
python main.py
This structure allows for a modular and organized approach to portfolio analysis, making each aspect of the analysis reusable and easier to maintain.