A collection of AI-powered financial analysis agents inspired by legendary investors and trading strategies. This project provides a framework for conducting comprehensive financial analysis using specialized agents, each implementing the investment philosophy of a different renowned investor or trading approach.
- Python >= 3.10
- uv (for dependency management)
# Clone the repository
git clone https://github.com/aostock/financial-agents
cd financial-agents
# Install dependencies
uv sync
# Activate the virtual environment
source .venv/bin/activate# Start the development server
langgraph dev --allow-blocking --debug-port 5678Alternatively, you can run the FastAPI server directly:
# Run the FastAPI server
python main.pyThe server will start on port 2024 by default (configurable via PORT environment variable).
The frontend UI for this project is available at: agent-chat-ui
Financial data for this project is sourced from: financial-data
This project includes multiple specialized financial analysis agents, each implementing the investment philosophy and methodology of a different renowned investor or trading approach.
Implements Warren Buffett's value investing philosophy:
- Focus on businesses within his "circle of competence"
- Evaluate economic moats and competitive advantages
- Assess management quality and capital allocation skills
- Analyze financial strength and consistency
- Calculate intrinsic value and margin of safety
Applies Charlie Munger's multidisciplinary approach:
- Evaluate management quality and integrity
- Assess moat strength and durability
- Analyze business predictability
- Determine fair valuation
Follows Benjamin Graham's value investing principles:
- Analyze earnings stability
- Evaluate financial strength
- Determine intrinsic valuation
Implements Peter Lynch's growth investing approach:
- Understand the business and its story
- Evaluate earnings quality
- Conduct fundamental analysis
- Analyze growth prospects
- Determine intrinsic value
Applies Phil Fisher's growth stock approach:
- Evaluate growth quality
- Analyze insider activity
- Determine intrinsic value
- Assess management efficiency
- Analyze margins stability
- Conduct sentiment analysis
Implements Aswath Damodaran's valuation framework:
- Conduct growth analysis
- Determine intrinsic value
- Perform relative valuation
- Analyze risk factors
- Develop company narrative
Applies Michael Burry's contrarian investing approach:
- Identify market inefficiencies
- Conduct deep value analysis
- Analyze financial statements
- Assess contrarian opportunities
- Evaluate risk factors
Implements Stanley Druckenmiller's macro approach:
- Analyze global markets
- Conduct macro analysis
- Evaluate adaptive strategies
- Assess flexibility
- Analyze risk factors
Applies Bill Ackman's activist investing approach:
- Analyze balance sheets
- Evaluate business quality
- Assess activism potential
- Determine fair valuation
Implements Cathie Wood's disruptive innovation approach:
- Evaluate disruptive potential
- Analyze innovation growth
- Determine valuation
Applies Rakesh Jhunjhunwala's value investing approach:
- Analyze balance sheets
- Evaluate cash flows
- Conduct fundamental analysis
- Assess growth prospects
- Determine intrinsic value
- Analyze management quality
Comprehensive fundamental analysis:
- Evaluate business consistency
- Conduct fundamental analysis
- Analyze growth metrics
- Assess quality factors
- Determine valuation
Provides detailed company information and key financial metrics analysis.
Manages portfolio analysis and optimization.
Analyzes and manages investment risks.
Analyzes market sentiment from multiple sources:
- News sentiment
- Social media sentiment
- Insider activity sentiment
- Technical analysis sentiment
- Composite sentiment analysis
Applies technical analysis approaches:
- Trend analysis
- Momentum analysis
- Mean reversion analysis
- Volatility analysis
- Statistical arbitrage analysis
Implements trading strategies based on technical analysis.
Specialized valuation methodologies:
- Discounted Cash Flow (DCF) analysis
- EV/EBITDA analysis
- Owner earnings analysis
- Residual income analysis
Each agent follows a modular architecture with specialized analysis components. The agents are built using LangGraph and integrate with various financial data sources through MCP (Model Coordination Protocol) adapters.
This project draws inspiration from:
These projects provided valuable insights into implementing AI-powered financial analysis systems and trading agent frameworks.