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Financial Analyst Skill
Overview
Production-ready financial analysis toolkit providing ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction. Designed for financial modeling, forecasting & budgeting, management reporting, business performance analysis, and investment analysis.
5-Phase Workflow
Phase 1: Scoping
- Define analysis objectives and stakeholder requirements
- Identify data sources and time periods
- Establish materiality thresholds and accuracy targets
- Select appropriate analytical frameworks
Phase 2: Data Analysis & Modeling
- Collect and validate financial data (income statement, balance sheet, cash flow)
- Validate input data completeness before running ratio calculations (check for missing fields, nulls, or implausible values)
- Calculate financial ratios across 5 categories (profitability, liquidity, leverage, efficiency, valuation)
- Build DCF models with WACC and terminal value calculations; cross-check DCF outputs against sanity bounds (e.g., implied multiples vs. comparables)
- Construct budget variance analyses with favorable/unfavorable classification
- Develop driver-based forecasts with scenario modeling
Phase 3: Insight Generation
- Interpret ratio trends and benchmark against industry standards
- Identify material variances and root causes
- Assess valuation ranges through sensitivity analysis
- Evaluate forecast scenarios (base/bull/bear) for decision support
Phase 4: Reporting
- Generate executive summaries with key findings
- Produce detailed variance reports by department and category
- Deliver DCF valuation reports with sensitivity tables
- Present rolling forecasts with trend analysis
Phase 5: Follow-up
- Track forecast accuracy (target: +/-5% revenue, +/-3% expenses)
- Monitor report delivery timeliness (target: 100% on time)
- Update models with actuals as they become available
- Refine assumptions based on variance analysis
Tools
1. Ratio Calculator (scripts/ratio_calculator.py)
Calculate and interpret financial ratios from financial statement data.
Ratio Categories:
- Profitability: ROE, ROA, Gross Margin, Operating Margin, Net Margin
- Liquidity: Current Ratio, Quick Ratio, Cash Ratio
- Leverage: Debt-to-Equity, Interest Coverage, DSCR
- Efficiency: Asset Turnover, Inventory Turnover, Receivables Turnover, DSO
- Valuation: P/E, P/B, P/S, EV/EBITDA, PEG Ratio
python scripts/ratio_calculator.py sample_financial_data.json
python scripts/ratio_calculator.py sample_financial_data.json --format json
python scripts/ratio_calculator.py sample_financial_data.json --category profitability
2. DCF Valuation (scripts/dcf_valuation.py)
Discounted Cash Flow enterprise and equity valuation with sensitivity analysis.
Features:
- WACC calculation via CAPM
- Revenue and free cash flow projections (5-year default)
- Terminal value via perpetuity growth and exit multiple methods
- Enterprise value and equity value derivation
- Two-way sensitivity analysis (discount rate vs growth rate)
python scripts/dcf_valuation.py valuation_data.json
python scripts/dcf_valuation.py valuation_data.json --format json
python scripts/dcf_valuation.py valuation_data.json --projection-years 7
3. Budget Variance Analyzer (scripts/budget_variance_analyzer.py)
Analyze actual vs budget vs prior year performance with materiality filtering.
Features:
- Dollar and percentage variance calculation
- Materiality threshold filtering (default: 10% or $50K)
- Favorable/unfavorable classification with revenue/expense logic
- Department and category breakdown
- Executive summary generation
python scripts/budget_variance_analyzer.py budget_data.json
python scripts/budget_variance_analyzer.py budget_data.json --format json
python scripts/budget_variance_analyzer.py budget_data.json --threshold-pct 5 --threshold-amt 25000
4. Forecast Builder (scripts/forecast_builder.py)
Driver-based revenue forecasting with rolling cash flow projection and scenario modeling.
Features:
- Driver-based revenue forecast model
- 13-week rolling cash flow projection
- Scenario modeling (base/bull/bear cases)
- Trend analysis using simple linear regression (standard library)
python scripts/forecast_builder.py forecast_data.json
python scripts/forecast_builder.py forecast_data.json --format json
python scripts/forecast_builder.py forecast_data.json --scenarios base,bull,bear
Knowledge Bases
| Reference |
Purpose |
references/financial-ratios-guide.md |
Ratio formulas, interpretation, industry benchmarks |
references/valuation-methodology.md |
DCF methodology, WACC, terminal value, comps |
references/forecasting-best-practices.md |
Driver-based forecasting, rolling forecasts, accuracy |
references/industry-adaptations.md |
Sector-specific metrics and considerations (SaaS, Retail, Manufacturing, Financial Services, Healthcare) |
Templates
| Template |
Purpose |
assets/variance_report_template.md |
Budget variance report template |
assets/dcf_analysis_template.md |
DCF valuation analysis template |
assets/forecast_report_template.md |
Revenue forecast report template |
Key Metrics & Targets
| Metric |
Target |
| Forecast accuracy (revenue) |
+/-5% |
| Forecast accuracy (expenses) |
+/-3% |
| Report delivery |
100% on time |
| Model documentation |
Complete for all assumptions |
| Variance explanation |
100% of material variances |
Input Data Format
All scripts accept JSON input files. See assets/sample_financial_data.json for the complete input schema covering all four tools.
Dependencies
None - All scripts use Python standard library only (math, statistics, json, argparse, datetime). No numpy, pandas, or scipy required.
1---2name: financial-analyst3description: Performs financial ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction for strategic decision-making. Use when analyzing financial statements, building valuation models, assessing budget variances, or constructing financial projections and forecasts. Also applicable when users mention financial modeling, cash flow analysis, company valuation, financial projections, or spreadsheet analysis.4---56## Internal Safety Override78- Status: active for local use.9- Keep operation local by default. Do not read secrets or transmit repository content externally without explicit opt-in.10- Audit categories: none detected.1112# Financial Analyst Skill1314## Overview1516Production-ready financial analysis toolkit providing ratio analysis, DCF valuation, budget variance analysis, and rolling forecast construction. Designed for financial modeling, forecasting & budgeting, management reporting, business performance analysis, and investment analysis.1718## 5-Phase Workflow1920### Phase 1: Scoping21- Define analysis objectives and stakeholder requirements22- Identify data sources and time periods23- Establish materiality thresholds and accuracy targets24- Select appropriate analytical frameworks2526### Phase 2: Data Analysis & Modeling27- Collect and validate financial data (income statement, balance sheet, cash flow)28- **Validate input data completeness** before running ratio calculations (check for missing fields, nulls, or implausible values)29- Calculate financial ratios across 5 categories (profitability, liquidity, leverage, efficiency, valuation)30- Build DCF models with WACC and terminal value calculations; **cross-check DCF outputs against sanity bounds** (e.g., implied multiples vs. comparables)31- Construct budget variance analyses with favorable/unfavorable classification32- Develop driver-based forecasts with scenario modeling3334### Phase 3: Insight Generation35- Interpret ratio trends and benchmark against industry standards36- Identify material variances and root causes37- Assess valuation ranges through sensitivity analysis38- Evaluate forecast scenarios (base/bull/bear) for decision support3940### Phase 4: Reporting41- Generate executive summaries with key findings42- Produce detailed variance reports by department and category43- Deliver DCF valuation reports with sensitivity tables44- Present rolling forecasts with trend analysis4546### Phase 5: Follow-up47- Track forecast accuracy (target: +/-5% revenue, +/-3% expenses)48- Monitor report delivery timeliness (target: 100% on time)49- Update models with actuals as they become available50- Refine assumptions based on variance analysis5152## Tools5354### 1. Ratio Calculator (`scripts/ratio_calculator.py`)5556Calculate and interpret financial ratios from financial statement data.5758**Ratio Categories:**59- **Profitability:** ROE, ROA, Gross Margin, Operating Margin, Net Margin60- **Liquidity:** Current Ratio, Quick Ratio, Cash Ratio61- **Leverage:** Debt-to-Equity, Interest Coverage, DSCR62- **Efficiency:** Asset Turnover, Inventory Turnover, Receivables Turnover, DSO63- **Valuation:** P/E, P/B, P/S, EV/EBITDA, PEG Ratio6465```bash66python scripts/ratio_calculator.py sample_financial_data.json67python scripts/ratio_calculator.py sample_financial_data.json --format json68python scripts/ratio_calculator.py sample_financial_data.json --category profitability69```7071### 2. DCF Valuation (`scripts/dcf_valuation.py`)7273Discounted Cash Flow enterprise and equity valuation with sensitivity analysis.7475**Features:**76- WACC calculation via CAPM77- Revenue and free cash flow projections (5-year default)78- Terminal value via perpetuity growth and exit multiple methods79- Enterprise value and equity value derivation80- Two-way sensitivity analysis (discount rate vs growth rate)8182```bash83python scripts/dcf_valuation.py valuation_data.json84python scripts/dcf_valuation.py valuation_data.json --format json85python scripts/dcf_valuation.py valuation_data.json --projection-years 786```8788### 3. Budget Variance Analyzer (`scripts/budget_variance_analyzer.py`)8990Analyze actual vs budget vs prior year performance with materiality filtering.9192**Features:**93- Dollar and percentage variance calculation94- Materiality threshold filtering (default: 10% or $50K)95- Favorable/unfavorable classification with revenue/expense logic96- Department and category breakdown97- Executive summary generation9899```bash100python scripts/budget_variance_analyzer.py budget_data.json101python scripts/budget_variance_analyzer.py budget_data.json --format json102python scripts/budget_variance_analyzer.py budget_data.json --threshold-pct 5 --threshold-amt 25000103```104105### 4. Forecast Builder (`scripts/forecast_builder.py`)106107Driver-based revenue forecasting with rolling cash flow projection and scenario modeling.108109**Features:**110- Driver-based revenue forecast model111- 13-week rolling cash flow projection112- Scenario modeling (base/bull/bear cases)113- Trend analysis using simple linear regression (standard library)114115```bash116python scripts/forecast_builder.py forecast_data.json117python scripts/forecast_builder.py forecast_data.json --format json118python scripts/forecast_builder.py forecast_data.json --scenarios base,bull,bear119```120121## Knowledge Bases122123| Reference | Purpose |124|-----------|---------|125| `references/financial-ratios-guide.md` | Ratio formulas, interpretation, industry benchmarks |126| `references/valuation-methodology.md` | DCF methodology, WACC, terminal value, comps |127| `references/forecasting-best-practices.md` | Driver-based forecasting, rolling forecasts, accuracy |128| `references/industry-adaptations.md` | Sector-specific metrics and considerations (SaaS, Retail, Manufacturing, Financial Services, Healthcare) |129130## Templates131132| Template | Purpose |133|----------|---------|134| `assets/variance_report_template.md` | Budget variance report template |135| `assets/dcf_analysis_template.md` | DCF valuation analysis template |136| `assets/forecast_report_template.md` | Revenue forecast report template |137138## Key Metrics & Targets139140| Metric | Target |141|--------|--------|142| Forecast accuracy (revenue) | +/-5% |143| Forecast accuracy (expenses) | +/-3% |144| Report delivery | 100% on time |145| Model documentation | Complete for all assumptions |146| Variance explanation | 100% of material variances |147148## Input Data Format149150All scripts accept JSON input files. See `assets/sample_financial_data.json` for the complete input schema covering all four tools.151152## Dependencies153154**None** - All scripts use Python standard library only (`math`, `statistics`, `json`, `argparse`, `datetime`). No numpy, pandas, or scipy required.
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