SKILL.md
Financial Analysis Agent
Build intelligent financial analysis agents that evaluate investments, assess risks, and generate data-driven recommendations.
Financial Data Integration
See [examples/financialdatacollector.py](examples/financialdatacollector.py) for the FinancialDataCollector class that:
- Integrates with yfinance for stock data
- Retrieves financial statements (income, balance sheet, cash flow)
- Fetches key metrics (market cap, PE ratio, dividend yield, etc.)
Financial Analysis Techniques
Technical Analysis
See [examples/technicalanalyzer.py](examples/technicalanalyzer.py) for TechnicalAnalyzer:
- Moving averages calculation
- Relative Strength Index (RSI)
- Support and resistance level identification
Fundamental Analysis
See [examples/fundamentalanalyzer.py](examples/fundamentalanalyzer.py) for FundamentalAnalyzer:
- Profitability ratios (gross margin, operating margin, net margin, ROA, ROE)
- Valuation ratios (PE, PB, PEG, price-to-sales)
- Liquidity ratios (current ratio, quick ratio, debt-to-equity)
Risk Assessment
See [examples/riskanalyzer.py](examples/riskanalyzer.py) for RiskAnalyzer:
- Volatility calculation
- Value at Risk (VaR) assessment
- Sharpe Ratio calculation
- Company risk assessment
Investment Recommendations
See [examples/investmentrecommender.py](examples/investmentrecommender.py) for InvestmentRecommender:
- Generates recommendations (Strong Buy, Buy, Hold, Sell, Strong Sell)
- Calculates investment scores based on technical and fundamental signals
- Provides confidence levels and risk assessments
Portfolio Management
See [examples/portfoliomanager.py](examples/portfoliomanager.py) for PortfolioManager:
- Calculate portfolio total value
- Rebalance portfolio based on target allocations
- Assess portfolio risk and volatility
Market Intelligence
Build market intelligence capabilities by:
- Analyzing overall market trends and sector performance
- Calculating market volatility indices
- Fetching economic indicators
- Identifying undervalued, growth, and dividend opportunities
Best Practices
Analysis Quality
- ✓ Use multiple data sources
- ✓ Cross-validate findings
- ✓ Document assumptions
- ✓ Consider time horizons
- ✓ Account for fees and taxes
Risk Management
- ✓ Assess downside risk
- ✓ Implement stop losses
- ✓ Diversify appropriately
- ✓ Position size accordingly
- ✓ Review regularly
Ethical Considerations
- ✓ Disclose conflicts of interest
- ✓ Avoid market manipulation
- ✓ Base recommendations on analysis
- ✓ Update recommendations regularly
- ✓ Acknowledge limitations
Tools & Data Sources
Data APIs
- yfinance
- Alpha Vantage
- IEX Cloud
- Polygon.io
- Yahoo Finance
Analysis Libraries
- pandas
- NumPy
- scikit-learn
- TA-Lib
- statsmodels
Getting Started
- Collect financial data
- Perform technical analysis
- Analyze fundamentals
- Assess risks
- Generate recommendations
- Monitor positions
- Rebalance periodically