Comparable Company Analysis Step by Step

Intermediate | Published: 2025-12-30

Why Comp Analysis Matters

Comparable company analysis (comps) values a target company by examining how the market prices similar businesses. The method is fast, market-grounded, and universally used: over 90% of equity research reports include a comps-based valuation alongside DCF (Damodaran, 2012). The practical antidote to DCF model uncertainty is not more assumptions. It's letting the market tell you what similar companies are worth today.

The point is: DCF tells you what a company should be worth based on your forecasts. Comps tell you what the market actually pays for similar cash flow streams right now.

Step 1: Selecting Comparable Companies (Why This Matters)

A comp set only works if the companies genuinely compete for the same capital. Three filters matter most:

Size: Market cap within 0.5x to 2x of your target. A $500M company is not comparable to a $50B company. Scale creates different margin structures, capital access, and risk profiles.

Geography: Match primary revenue exposure. A U.S.-focused retailer is not comparable to an emerging markets retailer. Currency, regulatory, and growth trajectories diverge materially.

Business model: Same industry is necessary but not sufficient. Within software, a subscription SaaS company (80%+ recurring revenue) is not comparable to a perpetual license vendor (lumpy, one-time sales). Revenue quality matters as much as revenue source.

The durable lesson: Start with 10-15 candidates, then narrow to 5-7 true peers based on these filters. Fewer than 4 comps creates sample noise; more than 10 dilutes signal.

Step 2: Key Multiples and When to Use Each

Three multiples dominate equity comps. Each answers a different question:

P/E (Price to Earnings)

• Formula: Stock Price / Earnings Per Share
• When to use: Mature, profitable companies with stable margins
• Watch out: Distorted by capital structure, one-time items, accounting differences
• Typical ranges: S&P 500 trades at 18-22x in normal rate environments (Shiller data, 1990-2024)

EV/EBITDA (Enterprise Value to EBITDA)

• Formula: (Market Cap + Debt - Cash) / EBITDA
• When to use: Comparing companies with different leverage; M&A analysis
• Why this matters: Removes capital structure noise. Two identical businesses with different debt loads have different P/E but similar EV/EBITDA.
• Typical ranges: Industrials 8-12x, tech 15-25x, utilities 7-10x

EV/Revenue (Enterprise Value to Revenue)

• Formula: (Market Cap + Debt - Cash) / Revenue
• When to use: Unprofitable or early-stage companies; rapid-growth SaaS
• Watch out: Ignores profitability entirely. A 4x revenue company burning cash differs from one generating 25% margins.
• Typical ranges: Mature businesses 1-3x, high-growth SaaS 5-15x (at peak 2021 multiples, some exceeded 30x)

Step 3: Adjusting for Growth Rate Differences

Raw multiples are misleading when growth rates diverge. The PEG ratio (P/E divided by growth rate) and EV/EBITDA-to-growth ratio normalize for this.

If Company A trades at 25x P/E with 20% growth and Company B trades at 15x P/E with 5% growth:

• Company A PEG: 25 / 20 = 1.25x
• Company B PEG: 15 / 5 = 3.00x

The point is: Company A looks expensive on raw P/E but is actually cheaper per unit of growth. A PEG below 1.5x is generally attractive; above 2.5x signals overvaluation unless growth is highly durable.

For EV/EBITDA, divide by expected EBITDA growth rate for the same adjustment.

Step 4: Median vs. Mean Selection (The Decision Rule)

Always use median, not mean. Outliers distort mean calculations asymmetrically.

Example: Five companies with EV/EBITDA of 8x, 9x, 10x, 11x, and 35x:

• Mean: 14.6x
• Median: 10x

The 35x outlier (perhaps a growth darling or acquisition target) pulls the mean up by 46%. The median represents where "most" comparable companies trade.

Why this matters: If you apply the mean to your target, you implicitly assume it deserves the same premium as the outlier. That is usually wrong.

Step 5: Dealing with Outliers

Before calculating the median, ask why outliers exist:

Remove if:

• Company is under strategic review or M&A speculation (takeover premium embedded)
• Recent one-time event distorted financials (asset sale, restructuring charge)
• Business model has fundamentally shifted (pivot in progress)

Keep if:

• Company operates in same end market with similar fundamentals
• Difference reflects genuine quality gap you want to understand

The practical rule: If an outlier is more than 2 standard deviations from the peer group average, investigate before including. Document your decision either way.

Worked Example: Valuing a Mid-Cap Software Company

Target: CloudTech Inc., a $2B market cap enterprise software company growing 15% annually with $200M EBITDA.

Step 1: Build the comp set

Step 2: Identify outlier

CloudBase at 23.6x is an outlier (more than 2 standard deviations above peer mean). Reason: recent analyst upgrade citing AI integration potential. Exclude from median calculation but note for qualitative discussion.

Step 3: Calculate median multiple

Remaining four comps: 11.1x, 12.1x, 13.3x, 14.0x Median EV/EBITDA: (12.1 + 13.3) / 2 = 12.7x

Step 4: Apply to target

CloudTech EBITDA: $200M Implied Enterprise Value: $200M x 12.7x = $2.54B Less: Net Debt of $150M Implied Equity Value: $2.39B Current Market Cap: $2.0B Upside: 20% undervaluation relative to peers

Step 5: Growth adjustment

CloudTech grows at 15%, peer median growth is 14%. Slightly above average growth supports the valuation or modest premium.

The durable lesson: Comps give you a range, not a point estimate. The analysis suggests CloudTech trades at a discount to peers, but verify whether that discount reflects genuine undervaluation or a quality gap you missed.

Common Pitfalls

1. Using stale multiples Multiples change with interest rates and market sentiment. Tech EV/EBITDA compressed from 20x+ in 2021 to 12-15x in 2023 as rates rose. Always use trailing twelve months (TTM) or NTM consensus, not last year's data.

2. Ignoring business model differences A hardware company with 40% gross margins is not comparable to a software company with 80% gross margins, even if both serve the same customers. Higher-margin businesses deserve higher multiples.

3. Applying mean instead of median This single error can swing your valuation by 30-50% in skewed distributions. Always check for outliers first.

Implementation Checklist (Tiered)

Essential (high ROI)

• Filter comps by size (0.5x-2x market cap), geography, and business model
• Collect P/E, EV/EBITDA, and EV/Revenue for all candidates
• Calculate median multiples (not mean)
• Adjust for growth rate differences using PEG or EV/EBITDA-to-growth

High-impact (workflow)

• Document why each company is included or excluded
• Build sensitivity table showing valuation at 25th, 50th, and 75th percentile multiples
• Cross-check comp-based value against DCF for sanity

Optional (for deeper analysis)

• Segment by growth tier (high-growth vs. mature peers)
• Run historical comp trends to see if current multiples are elevated or depressed

Next Step

This week, build a 5-company comp set for your largest equity holding. Pull EV/EBITDA and P/E from a financial data source (Yahoo Finance, Koyfin, or a broker platform). Calculate the median multiple, apply it to your target, and document whether the current price implies a premium or discount to peers. If it is a discount, write down three reasons that might justify it. If you cannot articulate reasons, you may have found an undervaluation.

Related Articles

• Discounted Cash Flow (DCF) Modeling Fundamentals
• Valuation Multiples Overview: P/E, EV/EBITDA, P/S
• Building a Simple Earnings Forecast Model