A portfolio optimization engine to maximize after-tax returns through tax-loss harvesting and goal-based asset allocation. This project was built as a demonstration of financial engineering and software development skills.
- Tax-Loss Harvesting (TLH): Identifies and recommends trades to harvest capital losses, reducing tax liability.
- Goal-Based Rebalancing: Keeps the portfolio aligned with a target asset allocation based on the user's risk profile.
- Wash Sale Rule Compliance: Ensures all recommended sales will not violate the 61-day wash sale rule.
- Simple UI: A Streamlit-based interface to display portfolio state and actionable recommendations.
- Backend: Python
- Data Analysis: Pandas, NumPy
- Frontend/UI: Streamlit
- API Simulation: Data loaded from local CSV files, simulating a Plaid API connection.
-
Clone the repository:
git clone [https://github.com/your-username/project-atlas.git](https://github.com/your-username/project-atlas.git) cd project-atlas -
Create and activate a virtual environment:
python3 -m venv venv source venv/bin/activate -
Install dependencies:
pip install -r requirements.txt pip install -e . -
Run the application:
streamlit run app.py