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Comparable Company Analysis Builder

Build institutional-grade comparable company analyses in Excel with operating metrics, valuation multiples, quartile statistics, implied valuation, and professional formatting.

5 minutes
By anthropic
#comparable companies#comps analysis#valuation multiples#equity valuation#investment banking

Building a proper comps analysis means gathering consistent data across 8-15 companies, calculating dozens of multiples, handling outliers, and bridging from enterprise value to implied share price — one inconsistent data point or wrong denominator can throw off the entire valuation range.

Who it's for: investment banking analysts, equity research associates, corporate development teams, private equity analysts, valuation professionals

Example

"Build a comps analysis for Salesforce with 10 SaaS peers" → Excel workbook with market data, operating metrics, growth and margin analysis, EV/Revenue, EV/EBITDA, P/E multiples (LTM and NTM), statistics (mean, median, quartiles), and implied valuation range with football field chart

CLAUDE.md Template

New here? 3-minute setup guide → | Already set up? Copy the template below.

# Comparable Company Analysis Builder

**Important**: This workflow assists with building comparable company analyses but does not constitute financial advice. All analyses should be reviewed by qualified financial professionals before use in valuation decisions.

Build institutional-grade comparable company analyses in Excel with operating metrics, valuation multiples, quartile statistics, and professional formatting.

## Section Structure

A complete comps analysis has the following sections in the output spreadsheet:

| Section | Description |
|---------|-------------|
| Header | Company names, tickers, share prices, dates |
| Market Data | Share price, diluted shares, market cap, enterprise value |
| Operating Metrics | Revenue, EBITDA, EBIT, Net Income (historical + projected) |
| Growth Metrics | Revenue growth, EBITDA growth (historical + projected) |
| Margin Analysis | Gross margin, EBITDA margin, EBIT margin, net margin |
| Valuation Multiples | EV/Revenue, EV/EBITDA, P/E, EV/EBIT (historical + projected) |
| Credit Metrics | Net Debt/EBITDA, Interest Coverage, FCF Yield |
| Statistics | Mean, Median, 25th percentile, 75th percentile, High, Low |
| Implied Valuation | Apply benchmark multiples to the target company |

## Step-by-Step Workflow

### Step 1: Select the Peer Group

Choose 8-15 comparable companies based on:
- **Industry/sub-sector**: Same or adjacent industry classification (GICS, SIC)
- **Business model**: Similar revenue mix (recurring vs one-time, product vs service)
- **Size**: Revenue and market cap within a reasonable range (typically 0.5x to 3x of target)
- **Geography**: Same primary markets or global exposure
- **Growth profile**: Similar historical and projected growth rates
- **Margin profile**: Comparable profitability structure

Document why each comp was included or excluded.

### Step 2: Gather Market Data

For each company, collect as of a consistent date:

| Field | Source | Notes |
|-------|--------|-------|
| Share Price | Market close price | Use same date for all comps |
| Basic Shares Outstanding | Latest filing | From 10-Q/10-K cover page |
| Diluted Shares Outstanding | Latest filing | Include options, warrants, RSUs via treasury method |
| Total Debt | Latest filing | Short-term + long-term debt |
| Cash & Equivalents | Latest filing | Cash + short-term investments |
| Preferred Stock | Latest filing | Liquidation preference if applicable |
| Minority Interest | Latest filing | Non-controlling interest |

**Key calculations:**

```
Market Cap = Share Price × Diluted Shares Outstanding
Enterprise Value = Market Cap + Total Debt − Cash + Preferred Stock + Minority Interest
Net Debt = Total Debt − Cash
```

### Step 3: Gather Operating Metrics

For each company, collect historical (LTM or latest FY) and projected (NTM, FY+1, FY+2) data:

| Metric | Historical Source | Projected Source |
|--------|-------------------|-----------------|
| Revenue | SEC filings | Consensus estimates (FactSet, Bloomberg, Capital IQ) |
| EBITDA | SEC filings (or calculated) | Consensus estimates |
| EBIT | SEC filings | Consensus estimates |
| Net Income | SEC filings | Consensus estimates |
| EPS | SEC filings | Consensus estimates |
| Free Cash Flow | SEC filings (or calculated) | Consensus estimates |
| CapEx | SEC filings | Consensus estimates |

**EBITDA calculation if not reported:**
```
EBITDA = Operating Income + Depreciation + Amortization
  OR
EBITDA = Net Income + Interest + Taxes + D&A
```

**Adjustments to consider:**
- Exclude one-time charges (restructuring, impairments, litigation)
- Exclude stock-based compensation (some analysts include, some exclude — be consistent)
- Normalize for acquisitions or divestitures

### Step 4: Calculate Multiples

#### Enterprise Value Multiples

```
EV / Revenue   = Enterprise Value / Revenue
EV / EBITDA    = Enterprise Value / EBITDA
EV / EBIT      = Enterprise Value / EBIT
```

#### Equity Value Multiples

```
P / E          = Share Price / EPS  (or Market Cap / Net Income)
P / B          = Market Cap / Book Value of Equity
PEG Ratio      = P/E / EPS Growth Rate
```

#### Other Multiples

```
FCF Yield      = Free Cash Flow / Enterprise Value (or Market Cap)
Dividend Yield = Annual Dividend / Share Price
EV / FCF       = Enterprise Value / Free Cash Flow
```

Calculate each multiple for:
- LTM (last twelve months / historical)
- NTM (next twelve months / forward)
- FY+1 and FY+2 (if available)

### Step 5: Industry-Specific Metrics

Include metrics relevant to the target industry:

| Industry | Additional Metrics |
|----------|--------------------|
| SaaS / Software | EV/ARR, EV/Bookings, Rule of 40, NRR, LTV/CAC, CAC Payback |
| Banks / Financial | P/TBV, P/BV, ROE, ROA, NIM, Efficiency Ratio |
| REITs | P/FFO, P/AFFO, Cap Rate, NOI Yield, Occupancy |
| Insurance | P/BV, Combined Ratio, Loss Ratio, ROE |
| Retail / Consumer | EV/Store, Same-Store Sales Growth, Revenue per Sq Ft |
| Healthcare | EV/Bed, EV/Subscriber, Revenue per Member |
| Telecom | EV/Subscriber, ARPU, Churn Rate |
| Oil & Gas | EV/EBITDAX, EV/BOE, EV/Reserves, NAV |
| Mining | EV/Resource, EV/Reserve, All-In Sustaining Cost |

### Step 6: Statistical Analysis

Calculate the following for each multiple across the peer group:

| Statistic | Formula |
|-----------|---------|
| Mean | Average of all comps (consider excluding outliers) |
| Median | Middle value (preferred — less sensitive to outliers) |
| 25th Percentile | PERCENTILE function at 0.25 |
| 75th Percentile | PERCENTILE function at 0.75 |
| High | Maximum value |
| Low | Minimum value |

**Outlier treatment**: If a comp has a multiple more than 2 standard deviations from the mean, flag it. Consider excluding from statistics but keep it in the table (with a footnote).

### Step 7: Implied Valuation

Apply the peer group multiples to the target company:

```
Implied Enterprise Value = Target Metric × Peer Median Multiple
Implied Equity Value = Implied EV − Net Debt − Preferred − Minority Interest
Implied Share Price = Implied Equity Value / Diluted Shares Outstanding
```

Build a valuation range using 25th and 75th percentile multiples:

| Metric | Target Value | 25th %ile Multiple | Median Multiple | 75th %ile Multiple | Implied EV (Low) | Implied EV (Mid) | Implied EV (High) |
|--------|-------------|-------------------|----------------|-------------------|------------------|------------------|-------------------|
| Revenue | $X | Xa | Xb | Xc | | | |
| EBITDA | $X | Xa | Xb | Xc | | | |

### Step 8: Sensitivity and Football Field

Build a summary "football field" chart showing the range of implied valuations from different methodologies:
- Comps (25th to 75th percentile)
- 52-week trading range
- Analyst price targets (low to high)
- DCF (if available)
- Precedent transactions (if available)

## Excel Layout and Formatting

### Column Layout

```
Column A:     Row labels / metrics
Column B:     Target company (highlighted)
Columns C-N:  Peer companies (8-12 comps)
Column O:     Blank spacer
Columns P-U:  Statistics (Mean, Median, 25th, 75th, High, Low)
```

### Formatting Standards

| Element | Format |
|---------|--------|
| Dollar values (millions) | #,##0.0x or #,##0 |
| Multiples | #,##0.0x |
| Percentages | 0.0% |
| Growth rates | 0.0% |
| Share price | $#,##0.00 |
| Market cap / EV | #,##0 (in millions, with header noting "$M") |
| Negative values | Parentheses: (#,##0.0) |

### Color Coding

| Color | Usage |
|-------|-------|
| Blue font | Hard-coded inputs |
| Black font | Formulas |
| Light blue background | Target company column |
| Light gray background | Statistics section |
| Bold | Section headers, totals, key outputs |
| Top/bottom borders | Section separators |

### Row Grouping

Group rows by section with spacing:
1. **Header section**: Company name, ticker, share price, date (rows 1-5)
2. *Blank row*
3. **Market data**: Shares, market cap, EV components, EV (rows 7-15)
4. *Blank row*
5. **Operating metrics** (rows 17-30)
6. *Blank row*
7. **Growth & margins** (rows 32-45)
8. *Blank row*
9. **Valuation multiples** (rows 47-60)
10. *Blank row*
11. **Statistics** (rows 62-68)
12. *Blank row*
13. **Implied valuation** (rows 70-80)

## Quality Checklist

Before delivering the comps analysis:

- [ ] All share prices are as of the same date
- [ ] Diluted share counts use treasury stock method consistently
- [ ] Enterprise value calculation is correct (Market Cap + Debt − Cash + Preferred + MI)
- [ ] Historical data matches SEC filings (spot-check 2-3 companies)
- [ ] Projected data matches consensus estimates
- [ ] EBITDA adjustments are applied consistently across all comps
- [ ] Multiples are calculated correctly (no sign errors, correct numerator/denominator)
- [ ] Statistics exclude obvious outliers (negative multiples, NM values)
- [ ] NM (not meaningful) is shown for negative denominators instead of a misleading number
- [ ] Implied valuation bridges correctly from EV to equity value to per-share
- [ ] All sources are documented with "as of" dates
- [ ] Formatting is consistent and professional
- [ ] Print area is set and fits on standard page sizes
README.md

What This Does

Builds institutional-grade comparable company analyses in Excel with a complete workflow: peer group selection, market data gathering, operating metrics, growth and margin analysis, valuation multiples (EV/Revenue, EV/EBITDA, P/E, and more), statistical analysis with quartiles, implied valuation bridging, and a summary football field chart.


Quick Start

Step 1: Create a Project Folder

Create a folder for your comps analysis and place the downloaded template inside as CLAUDE.md.

Step 2: Download the Template

Click Download above, then move the file into your project folder as CLAUDE.md.

Step 3: Start Working

"Build a comps analysis for Snowflake with 10 cloud data peers"
"Create a comparable company analysis for Nike — include athletic wear and footwear companies"
"Comps table for a mid-cap fintech — include implied valuation at median multiples"

Output Sections

Section Description
Header Company names, tickers, share prices, dates
Market Data Diluted shares, market cap, EV bridge
Operating Metrics Revenue, EBITDA, EBIT, Net Income (historical + projected)
Growth & Margins Revenue growth, EBITDA growth, gross/EBITDA/operating margins
Valuation Multiples EV/Revenue, EV/EBITDA, P/E, EV/EBIT (LTM + NTM)
Statistics Mean, Median, 25th/75th percentile, High, Low
Implied Valuation Apply peer multiples to target for EV-to-equity bridge

Industry-Specific Metrics

The template includes guidance for industry-specific multiples: SaaS (EV/ARR, Rule of 40, NRR), Banks (P/TBV, ROE, NIM), REITs (P/FFO, Cap Rate), Retail (EV/Store, Same-Store Sales), Healthcare (EV/Subscriber), and more.

Quality Checklist

  • All share prices as of the same date
  • Diluted share counts use treasury stock method consistently
  • Enterprise value calculation includes all components (Debt, Cash, Preferred, Minority Interest)
  • EBITDA adjustments applied consistently across all comps
  • NM (not meaningful) shown for negative denominators instead of misleading numbers
  • Implied valuation bridges correctly from EV to equity value to per-share

Tips & Best Practices

  • Select 8-15 comparable companies based on industry, business model, size, geography, and growth profile
  • Document inclusion/exclusion rationale for each peer
  • Exclude outliers from statistics (multiples > 2 standard deviations from mean) but keep them in the table with a footnote
  • Use median over mean — it is less sensitive to outliers
  • Calculate multiples for LTM and NTM to show both historical and forward-looking valuations

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