AgentSkillsCN

financial-analysis

提供全方位的财务分析解决方案，涵盖DCF模型构建、比率分析、敏感性测试、蒙特卡洛模拟，以及针对企业与投资机会的财务报表评估。

SKILL.md
--- frontmatter
name: financial-analysis
description: Comprehensive financial analysis suite including DCF modeling, ratio analysis, sensitivity testing, Monte Carlo simulations, and financial statement evaluation for companies and investment opportunities

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:

code
"Calculate key financial ratios for this company based on the attached financial statements"
"Analyze the liquidity position using the balance sheet data"

Valuation:

code
"Analyze Tesla's financials and provide a DCF valuation"
"Evaluate this startup's unit economics and runway"

Sensitivity:

code
"Run sensitivity analysis showing impact of growth rate and WACC on valuation"
"Create tornado chart ranking key value drivers"

Scenario Planning:

code
"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