fsi-comps-analysis

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• SKILL.md

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# Comparable Company Analysis

## ⚠️ CRITICAL: Data Source Priority (READ FIRST)

**ALWAYS follow this data source hierarchy:**

1. **FIRST: Check for MCP data sources** - If S&P Kensho MCP, FactSet MCP, or Daloopa MCP are available, use them exclusively for financial and trading information
2. **DO NOT use web search** if the above MCP data sources are available
3. **ONLY if MCPs are unavailable:** Then use Bloomberg Terminal, SEC EDGAR filings, or other institutional sources
4. **NEVER use web search as a primary data source** - it lacks the accuracy, audit trails, and reliability required for institutional-grade analysis

**Why this matters:** MCP sources provide verified, institutional-grade data with proper citations. Web search results can be outdated, inaccurate, or unreliable for financial analysis.

---

## Overview
This skill teaches Claude to build institutional-grade comparable company analyses that combine operating metrics, valuation multiples, and statistical benchmarking. The output is a structured Excel/spreadsheet that enables informed investment decisions through peer comparison.

**Reference Material & Contextualization:**

An example comparable company analysis is provided in `examples/comps_example.xlsx`. When using this or other example files in this skill directory, use them intelligently:

**DO use examples for:**
- Understanding structural hierarchy (how sections flow)
- Grasping the level of rigor expected (statistical depth, documentation standards)
- Learning principles (clear headers, transparent formulas, audit trails)

**DO NOT use examples for:**
- Exact reproduction of format or metrics
- Copying layout without considering context
- Applying the same visual style regardless of audience

**ALWAYS ask yourself first:**
1. **"Do you have a preferred format or should I adapt the template style?"**
2. **"Who is the audience?"** (Investment committee, board presentation, quick reference, detailed memo)
3. **"What's the key question?"** (Valuation, growth analysis, competitive positioning, efficiency)
4. **"What's the context?"** (M&A evaluation, investment decision, sector benchmarking, performance review)

**Adapt based on specifics:**
- **Industry context**: Big tech mega-caps need different metrics than emerging SaaS startups
- **Sector-specific needs**: Add relevant metrics early (e.g., cloud ARR, enterprise customers, developer ecosystem for tech)
- **Company familiarity**: Well-known companies may need less background, more focus on delta analysis
- **Decision type**: M&A requires different emphasis than ongoing portfolio monitoring

**Core principle:** Use template principles (clear structure, statistical rigor, transparent formulas) but vary execution based on context. The goal is institutional-quality analysis, not institutional-looking templates.

User-provided examples and explicit preferences always take precedence over defaults.

## Core Philosophy
**"Build the right structure first, then let the data tell the story."**

Start with headers that force strategic thinking about what matters, input clean data, build transparent formulas, and let statistics emerge automatically. A good comp should be immediately readable by someone who didn't build it.

---

## Section 1: Document Structure & Setup

### Header Block (Rows 1-3)
```
Row 1: [ANALYSIS TITLE] - COMPARABLE COMPANY ANALYSIS
Row 2: [List of Companies with Tickers] • [Company 1 (TICK1)] • [Company 2 (TICK2)] • [Company 3 (TICK3)]
Row 3: As of [Period] | All figures in [USD Millions/Billions] except per-share amounts and ratios
```

**Why this matters:** Establishes context immediately. Anyone opening this file knows what they're looking at, when it was created, and how to interpret the numbers.

### Visual Convention Standards (OPTIONAL - User preferences and uploaded templates always override)

**IMPORTANT: These are suggested defaults only. Always prioritize:**
1. User's explicit formatting preferences
2. Formatting from any uploaded template files
3. Company/team style guides
4. These defaults (only if no other guidance provided)

**Suggested Font & Typography:**
- **Font family**: Times New Roman (professional, readable, industry standard)
- **Font size**: 11pt for data cells, 12pt for headers
- **Bold text**: Section headers, company names, statistic labels

**Suggested Color & Shading:**
- **Section headers** (e.g., "OPERATING STATISTICS & FINANCIAL METRICS"):
  - Dark blue background (#17365D or similar navy)
  - White bold text
  - Full row shading across all columns
- **Column headers** (e.g., "Company", "Revenue", "Margin"):
  - Light blue/gray background (#D9E2F3 or similar pale blue)
  - Black bold text
  - Centered alignment
- **Data rows**:
  - White background for company data
  - Black text for inputs and formulas
- **Statistics rows** (Maximum, 75th Percentile, etc.):
  - Light gray background (#F2F2F2)
  - Black text, left-aligned labels

**Suggested Formatting Conventions:**
- **Decimal precision**:
  - Percentages: 1 decimal (12.3%)
  - Multiples: 1 decimal (13.5x)
  - Dollar amounts: No decimals, thousands separator (69,632)
  - Margins shown as percentages: 1 decimal (68.7%)
- **Borders**: No borders (clean, minimal appearance)
- **Alignment**: All metrics center-aligned for clean, uniform appearance
- **Cell dimensions**: All column widths should be uniform/even, all row heights should be consistent (creates clean, professional grid)

**Note:** If the user provides a template file or specifies different formatting, use that instead.

---

## Section 2: Operating Statistics & Financial Metrics

### Core Columns (Start with these)
1. **Company** - Names with consistent formatting
2. **Revenue** - Size metric (can be LTM, quarterly, or annual depending on context)
3. **Revenue Growth** - Year-over-year percentage change
4. **Gross Profit** - Revenue minus cost of goods sold
5. **Gross Margin** - GP/Revenue (fundamental profitability)
6. **EBITDA** - Earnings before interest, tax, depreciation, amortization
7. **EBITDA Margin** - EBITDA/Revenue (operating efficiency)

From d-wwei/openclaw-financial-services, Apache-2.0.

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