Qfinance-analyst — Financial Analysis & Quant Modeling
Role
A skill that provides structured financial analysis and quantitative modeling workflows.
Covers fundamental analysis, valuation, risk modeling, and investment decision support.
Trigger Conditions
- "financial analysis", "valuation", "DCF", "Monte Carlo"
- "quant", "quantitative", "investment analysis"
- "ratio analysis", "sensitivity analysis", "portfolio"
- "budget variance", "forecast", "financial model"
Workflow
Phase 1: Scoping
- Define analysis objective (valuation, risk assessment, portfolio optimization, etc.)
- Identify data sources and required inputs
- Select analytical framework
- Establish materiality thresholds
Phase 2: Analysis Tools
Tool 1: Financial Ratio Analysis
Calculate ratios across 5 categories:
- Profitability: ROE, ROA, gross margin, operating margin, net margin
- Liquidity: current ratio, quick ratio, cash ratio
- Leverage: debt-to-equity, interest coverage, debt-to-EBITDA
- Efficiency: asset turnover, inventory turnover, receivable days
- Valuation: P/E, P/B, EV/EBITDA, dividend yield
Tool 2: DCF Valuation
- Project free cash flows (5-10 year horizon)
- Calculate WACC (cost of equity via CAPM + cost of debt)
- Determine terminal value (Gordon Growth or Exit Multiple)
- Compute enterprise value and equity value per share
- Sanity check: implied growth rate, exit multiple reasonableness
Tool 3: Monte Carlo Simulation
- Define input distributions (revenue growth, margins, discount rate)
- Run 10,000+ iterations
- Generate probability distributions for key outputs
- Calculate confidence intervals (5th, 25th, 50th, 75th, 95th percentile)
- Report probability of achieving target returns
Tool 4: Sensitivity Analysis
- Two-variable data tables (e.g., WACC vs growth rate)
- Tornado chart: rank variables by impact on output
- Identify critical value drivers
- Break-even analysis
Tool 5: Portfolio Analysis
- Mean-variance optimization (Markowitz)
- Sharpe ratio calculation
- Correlation matrix analysis
- Risk decomposition (systematic vs idiosyncratic)
- VaR (Value at Risk) estimation
Phase 3: Output
Generate structured reports:
- Executive summary with key findings
- Detailed analysis with assumptions documented
- Sensitivity tables and scenario comparisons
- Risk assessment and limitations
- Recommendation with confidence level
Phase 4: Validation
- Cross-check valuations against market multiples
- Verify model consistency (balance sheet balances, cash flow reconciles)
- Test edge cases in Monte Carlo inputs
- Document all assumptions explicitly
Output Formats
- Markdown report with tables
- Python scripts for reproducible calculations (standard library + numpy/pandas if available)
- Excel-compatible output via /Qxlsx when needed
Disclaimer
All financial analysis is for educational and research purposes only. Not financial advice.
Will
- Financial ratio analysis and interpretation
- DCF and valuation modeling
- Monte Carlo simulation and risk analysis
- Sensitivity and scenario analysis
- Portfolio optimization
Will Not
- Provide specific investment recommendations as financial advice
- Access real-time market data (use user-provided data)
- Replace professional financial advisors