financial-analysis-agent

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Create agents for financial analysis, investment research, and portfolio management. Covers financial data processing, risk analysis, and recommendation generation. Use when building investment analysis tools, robo-advisors, portfolio trackers, or financial intelligence systems.

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Sourceqodex-ai/ai-agent-skills

Added on2026-02-04

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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

Collect financial data
Perform technical analysis
Analyze fundamentals
Assess risks
Generate recommendations
Monitor positions
Rebalance periodically