AgentSkillsCN

financial-analysis

综合金融分析工具包,融合比率分析(ROE、ROA、市盈率、流动性、盈利能力)与高级建模(DCF、蒙特卡洛模拟、敏感性测试、情景规划),助力投资决策与公司估值。

SKILL.md
--- frontmatter
name: financial-analysis
description: Comprehensive financial analysis toolkit combining ratio analysis (ROE, ROA, P/E, liquidity, profitability) with advanced modeling (DCF, Monte Carlo, sensitivity testing, scenario planning) for investment decisions and company valuation.

Financial Analysis Skill

Complete financial analysis and modeling toolkit for investment decisions, company valuation, and risk assessment.


Part 1: Financial Ratio Analysis

Capabilities

  • 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

Key Ratio Formulas

RatioFormulaGood Range
ROENet Income / Shareholders' Equity>15%
ROANet Income / Total Assets>5%
Current RatioCurrent Assets / Current Liabilities1.5-3.0
Quick Ratio(Current Assets - Inventory) / Current Liabilities>1.0
Debt-to-EquityTotal Debt / Shareholders' Equity<2.0
P/EPrice / EPSIndustry-dependent
EV/EBITDAEnterprise Value / EBITDA8-12x typical

Input Formats

  • CSV/Excel with financial line items
  • JSON with structured financial statements
  • Text description of key figures

Part 2: Financial Modeling

Core Capabilities

1. Discounted Cash Flow (DCF)

  • Multi-scenario growth projections
  • Terminal value (perpetuity growth + exit multiple)
  • WACC calculation
  • Enterprise and equity valuations

2. Sensitivity Analysis

  • Key assumption impact testing
  • Tornado charts for driver ranking
  • Break-even analysis

3. Monte Carlo Simulation

  • 1,000-10,000 scenario iterations
  • Probability distributions for inputs
  • Confidence intervals (90%, 95%)
  • VaR and risk metrics

4. Scenario Planning

  • Best/Base/Worst cases
  • Probability-weighted expected values
  • Decision tree analysis

DCF Input Requirements

  • Historical financials (3-5 years)
  • Revenue growth assumptions
  • Operating margin projections
  • CapEx forecasts
  • Working capital requirements
  • Terminal growth rate / exit multiple
  • Discount rate (risk-free rate, beta, market premium)

Model Types Supported

  1. Corporate Valuation - Mature, growth, turnaround
  2. Project Finance - Infrastructure, real estate, energy
  3. M&A Analysis - Acquisition valuation, synergy modeling
  4. LBO Models - Leveraged buyout, IRR/MOIC analysis

Output Formats

Ratio Analysis Output

  • Calculated ratios with values
  • Industry benchmark comparisons
  • Trend analysis (multi-period)
  • Interpretation and flags

DCF Model Output

  • Financial projections
  • Free cash flow calculations
  • Terminal value computation
  • Valuation summary
  • Excel workbook

Monte Carlo Output

  • Probability distribution
  • Confidence intervals
  • Statistical summary (mean, median, std dev)
  • Risk metrics (VaR)

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
  • Document key assumptions

Quality Checks

  1. Balance sheet balancing
  2. Cash flow reconciliation
  3. Circular reference resolution
  4. Sensitivity bound checking
  5. Statistical validation

Example Usage

Ratio Analysis:

  • "Calculate key financial ratios for this company"
  • "What's the P/E ratio if price is $50 and EPS is $2.50?"
  • "Analyze liquidity using the balance sheet"

Modeling:

  • "Build a DCF model using the attached financials"
  • "Run Monte Carlo with 5,000 iterations"
  • "Create sensitivity analysis for growth rate and WACC"
  • "Develop three scenarios with probability weights"

Limitations

  • Models are only as good as assumptions
  • Past performance ≠ future results
  • Industry benchmarks are general guidelines
  • Not a substitute for professional financial advice
  • Professional judgment required for interpretation