financial-analysis

# Financial Analysis Suite A comprehensive financial analysis toolkit combining ratio analysis, valuation modeling, and risk assessment using industry-standard methodologies. ## Core Capabilities ### 1. Financial Ratio Analysis Calculate and interpret key financial metrics: - **Profitability**: ROE, ROA, Gross Margin, Operating Margin, Net Margin - **Liquidity**: Current Ratio, Quick Ratio, Cash Ratio - **Leverage**: Debt-to-Equity, Interest Coverage, Debt Service Coverage - **Efficiency**: Asset Turnover, Inventory Turnover, Receivables Turnover - **Valuation**: P/E, P/B, P/S, EV/EBITDA, PEG - **Per-Share**: EPS, Book Value per Share, Dividend per Share ### 2. Valuation Models #### Discounted Cash Flow (DCF) - Build complete DCF models with multiple growth scenarios - Calculate terminal values using perpetuity growth and exit multiple methods - Determine weighted average cost of capital (WACC) - Generate enterprise and equity valuations #### Comparable Company Analysis - Identify peer companies - Analyze trading multiples (P/E, EV/EBITDA, P/S) - Calculate valuation ranges #### Precedent Transactions - Review similar deals for valuation benchmarks - Analyze transaction premiums ### 3. Sensitivity & Scenario Analysis - One-way and two-way sensitivity testing - Tornado charts for sensitivity ranking - Best/Base/Worst case scenario planning - Monte Carlo simulation with probability distributions - Breakeven analysis ### 4. Risk Assessment - Identify and quantify key risks - Calculate confidence intervals - Stress test extreme cases - Consider correlation effects ## Methodology ### Data Collection 1. Gather historical financial statements (income statement, balance sheet, cash flow) 2. Verify data sources for accuracy and completeness 3. Identify anomalies or missing data points ### Analysis Workflow 1. Calculate financial ratios with industry benchmarking 2. Build appropriate valuation models 3. Perform sensitivity analysis on key assumptions 4. Generate comprehensive report with recommendations ## Input Formats - CSV with financial line items - JSON with structured financial statements - Text description of key financial figures - Excel files with financial statements ## Key Outputs 1. **Executive Summary**: High-level findings and recommendations 2. **Financial Model**: Detailed projections with documented assumptions 3. **Valuation Range**: Multiple methods with sensitivity analysis 4. **Risk Assessment**: Key risks and mitigation factors 5. **Visualizations**: Charts, tornado diagrams, scenario comparisons ## Scripts Located in `scripts/` directory: - `calculate_ratios.py`: Financial ratio calculation engine - `interpret_ratios.py`: Industry benchmarking and interpretation - `dcf_model.py`: Complete DCF valuation engine - `sensitivity_analysis.py`: Sensitivity and scenario testing framework ## Example Usage **Ratio Analysis:** ``` "Calculate key financial ratios for this company based on the attached financial statements" "Analyze the liquidity position using the balance sheet data" ``` **Valuation:** ``` "Analyze Tesla's financials and provide a DCF valuation" "Evaluate this startup's unit economics and runway" ``` **Sensitivity:** ``` "Run sensitivity analysis showing impact of growth rate and WACC on valuation" "Create tornado chart ranking key value drivers" ``` **Scenario Planning:** ``` "Develop three scenarios for this expansion project with probability weights" "Run Monte Carlo simulation with 5,000 iterations" ``` ## Best Practices ### Modeling Standards - Consistent formatting and structure - Clear assumption documentation - Separation of inputs, calculations, outputs - Error checking and validation ### Valuation Principles - Use multiple methods for triangulation - Apply appropriate risk adjustments - Validate against trading multiples - Consider both quantitative and qualitative factors ### Risk Management - Use conservative assumptions when uncertain - Include probability-weighted scenarios - Clearly document all assumptions and rationale - Present results with appropriate caveats ## Limitations - Models are only as good as their assumptions - Past performance doesn't guarantee future results - Industry benchmarks are general guidelines - Not a substitute for professional financial advice