Proof-of-concept AI robo advisor

Welcome to your personal AI-powered investment assistant! This project aims to make professional-grade investment strategies, similar to those used by hedge funds, accessible to everyone through the power of AI.

This is the system workflow:

1. Investment Agent: collects user preferences via questionnaire and produces a structured Strategy.

2. Portfolio Agent: Translates the Strategy into a concrete ETF portfolio.

3. Analyst Agents:

   • Fees Agent: retrievesand analyze TER per holding.
   • Diversification Agent: compares and analyze portfolio vs strategy across asset class, geography, sector.
   • Alignment Agent: evaluates how holdings reflect risk tolerance, time horizon, expected returns embedded in the Strategy.
   • Performance Agent: computes CAGR, Annualized Volatility, Sharpe, Max Drawdown, Alpha, Beta and analyze if portfolio is performant.
   • Analysis Orchestrator: runs the above analyst agents and aggregates their outputs and provides a structured basis for downstream reporting.

Disclaimer: This project is for educational and research purposes only. The information provided should not be considered financial advice. Investing in financial markets involves risk, and you should consult with a qualified professional before making any investment decisions.

• AI-Driven Analysis: Leverages AI to analyze market data and suggest investment strategies.
• Portfolio Management: Helps you build and track your investment portfolio.
• Educational Tool: A great way to learn about both Langgraph and AI applications in finance.

• Installation
• How to Run
• Contributing
• License

Ready to run the project on your local machine? Follow these steps.

Note:

• Portfolios are created with a maximum of 4 ETFs, and the analysis is performed using 2 years of historical data. These limitations are in place to work within the constraints of the free Polygon.io API key. If you have a paid license, you can modify the code to increase these limits.
• The

1. Clone the repository:

   git clone https://github.com/matvix90/ai-robo-advisor.git cd ai-robo-advisor

2. Create a virtual environment (recommended):

   python3 -m venv venv source venv/bin/activate

3. Install the dependencies:

4. Create a .env file for your API keys:

   # Create .env file for your API keys (in the root directory) cp .env.example .env

5. Set up API Keys:

   # For running LLMs OPENAI_API_KEY=your-openai-api-key # For getting financial data to power the robo advisor POLYGON_API_KEY=your-polygon-api-key

   Important:

   • You must set at least one LLM API key (e.g. OPENAI_API_KEY, GOOGLE_API_KEY or ANTHROPIC_API_KEY) for the robo advisor to work.
   • You must set POLYGON_API_KEY for the robo advisor to work.

You can run the AI Robo Advisor directly via terminal. This approach offers more granular control and is useful for automation, scripting, and integration purposes.

You can also specify a --show-reasoning flag to run the AI Robo Advisor seeing agents reasoning.

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag enhancement.

See CONTRIBUTING.md for detailed information.

This project is distributed under the MIT License. See LICENSE.txt for more information.