Financial Analysis Agent

Build financial analysis agents for market data processing, technical and fundamental analysis, portfolio management, and investment recommendations. Code organized in examples: financial_data_collector.py, technical_analyzer.py, fundamental_analyzer.py, risk_analyzer.py, investment_recommender.py, portfolio_manager.py

officialAI/ML
#finance#investment#technical-analysis#trading#data-analysis

Financial Analysis Agent

Build intelligent financial analysis agents that evaluate investments, assess risks, and generate data-driven recommendations.

Financial Data Integration

See examples/financial_data_collector.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/technical_analyzer.py for TechnicalAnalyzer:

  • Moving averages calculation
  • Relative Strength Index (RSI)
  • Support and resistance level identification

Fundamental Analysis

See examples/fundamental_analyzer.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/risk_analyzer.py for RiskAnalyzer:

  • Volatility calculation
  • Value at Risk (VaR) assessment
  • Sharpe Ratio calculation
  • Company risk assessment

Investment Recommendations

See examples/investment_recommender.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/portfolio_manager.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

  1. Collect financial data
  2. Perform technical analysis
  3. Analyze fundamentals
  4. Assess risks
  5. Generate recommendations
  6. Monitor positions
  7. Rebalance periodically