This project performs investment analysis for equities (stocks) using Python and data visualization tools. The analysis helps investors identify potential opportunities, evaluate portfolio performance, and compare historical returns. The dataset is downloaded using the yfinance library.
- Data exploration and preprocessing
- Risk-return analysis
- Correlation between equities
- Portfolio optimization and visualization
The interactive results are stored in the Investment Analysis for Equities.html file, which can be viewed in any web browser.
- Python
- Pandas
- NumPy
- Matplotlib / Seaborn
- Plotly
- Jupyter Notebook
Sahil Rabadiya Master’s in Information Technology, Arizona State University