Relative Valuation: How to Use Comparable Companies and Precedent Transactions

Relative valuation is the most widely used method in M&A. Investment bankers lead with comparable-company analysis. PE firms underwrite deals against precedent multiples. M&A advisors price sell-side mandates by referencing recent transactions. The reason is simple: relative valuation answers the question every buyer and seller actually asks — ‘What have similar businesses sold for?’

There are two flavors of relative valuation: comparable companies and precedent transactions. Comparable companies (‘public comps’) values the business at the trading multiples of similar publicly traded peers. Precedent transactions values the business at the multiples paid in past M&A deals. Each tells you something different. Public comps reflect how investors price the industry day-to-day. Precedent transactions reflect how acquirers price control of the business — what they actually pay to own it.

Precedent transactions almost always trade at higher multiples than public comps. The difference is the control premium. A buyer of 100% of a company pays for the right to make decisions, set strategy, and capture all the synergies. A passive equity investor in a public-company share pays only for fractional economic exposure. The control premium typically runs 15-30%, which means precedent multiples are 15-30% above the same companies’ trading multiples.

Good relative valuation is harder than it looks. Choosing the right comps is a craft. You can’t use a public-company multiple from a Fortune 500 manufacturer to value a $5M EBITDA shop — the size mismatch is too large. You can’t use a SaaS-company multiple to value a distribution business. You can’t use 2021 data when valuing a 2026 deal — multiples have compressed. The valuation is only as good as the comp set, and the comp set requires real analytical work to assemble.

“Relative valuation isn’t about what your business is worth in some abstract sense. It’s about what other people have actually paid for businesses like yours — recently, in similar markets, for similar reasons. Done well, it’s the most defensible valuation you can produce.”

Key Takeaways

• Relative valuation has two flavors: comparable companies (public-company trading multiples) and precedent transactions (multiples paid in past M&A deals). Most M&A valuations use both.
• Precedent transactions typically trade at 15-30% higher multiples than public comps because they include a control premium — the price acquirers pay for full control and synergies.
• Good comps match on four dimensions: industry, size, growth profile, and business model. Mismatched comps produce wrong valuations.
• Adjustments after comp selection: size discount (smaller = lower multiple), growth premium (higher growth = higher multiple), profitability premium (higher margins = higher multiple), and recurring-revenue premium where applicable.
• Lower-middle-market data sources: PitchBook (fee-based, deepest M&A coverage), BVR DealStats (fee-based, lower-middle-market specialty), BizBuySell (free, smaller deals), IBBA Quarterly Pulse (free, broker survey), SEC filings (free, public-company peers).
• A defensible relative valuation includes: 6-12 well-chosen comps, multiple metrics (EV/EBITDA, EV/Revenue, EV/SDE), size and growth adjustments, and a clear narrative for why the chosen multiple applies.

What is relative valuation?

Relative valuation prices a business by comparing it to similar businesses that have transacted. It is one of the three accepted valuation approaches (alongside the income approach and the asset approach) and is sometimes called the ‘market approach.’ The core logic: if a buyer recently paid 6.5x EBITDA for a similar HVAC services business in the same region, my HVAC services business is probably worth somewhere around 6.5x EBITDA.

It assumes the market sets fair prices. Relative valuation works because M&A markets are reasonably efficient over time. Buyers won’t consistently overpay for an asset class. Sellers won’t consistently sell at fire-sale prices. Across many transactions, the multiples paid reflect real consensus about value. The job of the valuation analyst is to find the right comps and apply the right adjustments.

Two flavors: comparable company analysis and precedent transactions. Comparable company analysis (‘trading comps’ or ‘public comps’) uses the current trading multiples of publicly listed peers. Precedent transaction analysis (‘deal comps’ or ‘M&A comps’) uses the multiples paid in past M&A transactions. Both approaches are used in most professional valuations.

Relative valuation is the most widely used method in lower-middle-market M&A. Sellers and their advisors lead with ‘recent comps in our industry.’ Buyers price their offers against the same data. Lenders underwrite acquisition debt against the multiples observed in their syndicated portfolios. Even the IRS uses comp-based methods in many estate-tax valuations. The data is the language of M&A pricing.

Comparable company analysis: using public-company peers

Comparable company analysis uses the trading multiples of publicly listed peers as a benchmark. If three public companies in the same industry trade at 8.0x, 8.5x, and 9.2x EV/EBITDA, the median trading multiple is 8.5x. A private company in the same industry would be valued, before adjustments, at roughly 8.5x its EBITDA — subject to discounts for size and illiquidity.

Public-company data is free and abundant. SEC filings (10-K, 10-Q, proxy statements) provide audited financial statements. Bloomberg, Capital IQ, and FactSet provide trading multiples (fee-based). Yahoo Finance, Google Finance, and Stock Analysis (free) provide basic metrics. The challenge isn’t finding data; it’s finding companies that are actually comparable.

The size mismatch is the biggest problem in lower-middle-market work. Most public companies are large — revenue of $100M+ for the smallest, often $1B+. Lower-middle-market businesses are $10-100M of revenue. The size gap between a public-company comp and a private LMM business is often 10-100x. Public-company multiples are not directly applicable without significant size discounts (typically 20-40%).

Apply discounts for lack of marketability and lack of control. Public-company shares are liquid (sellable in seconds at the trading price). Private-company equity is illiquid (months to sell). The discount for lack of marketability (DLOM) is typically 20-35% for control positions in private companies, higher for minority positions. Public-company minority shares also lack control; for a private 100% sale, no control discount applies, but DLOM does.

Public comps are most useful for industry-level multiples and trends. Even with significant adjustments, public comps tell you how the public market is pricing your industry. If the public peers are trading at 12x EBITDA in 2026 vs 8x EBITDA in 2024, that signals a sector tailwind. If they’ve compressed from 14x to 9x, that signals headwinds. The trend matters even when the absolute level isn’t directly applicable.

Precedent transaction analysis: using past M&A deals

Precedent transaction analysis uses the multiples paid in past M&A deals as a benchmark. If three private HVAC services businesses sold at 5.5x, 6.0x, and 6.8x EBITDA in the past 18 months, the median deal multiple is 6.0x. A similar HVAC business today, before adjustments, is worth roughly 6.0x its EBITDA. Precedent transactions are the closest analog to the deal you’re actually doing — same industry, similar size, control sale.

Precedent multiples include a control premium. When a buyer acquires 100% of a private company, they pay for full control and the right to capture synergies. The control premium typically adds 15-30% to the multiple compared to the same company’s public-trading-comp multiple. So if public comps trade at 8x EBITDA, precedent transactions for similar private targets often pay 9.5-10.5x EBITDA.

Precedent data is harder to find than public-company data. Private M&A transactions don’t require public disclosure. Many deals close without any public announcement of price. Of the deals that do get reported, the multiples are sometimes incomplete (revenue or EBITDA undisclosed) or approximate. Specialized databases (PitchBook, BVR DealStats, S&P Capital IQ) compile reported transactions, often supplemented with broker survey data and proxy statement disclosures from public-company acquisitions.

The recency of comps matters. M&A multiples move with the cycle. 2021 saw record-high multiples driven by abundant capital and low rates. 2023-2024 saw multiple compression as rates rose and lender appetite tightened. 2025-2026 is showing partial recovery in some sectors. A 2021 comp may be 2-3 turns above today’s reality. Precedent comps should be no older than 24 months for serious work, and the trend should be analyzed (rising, flat, falling).

Buyer type matters. Strategic buyers often pay higher multiples than financial buyers because they capture cost synergies. PE platforms typically pay near the median. Add-on acquisitions often trade at lower multiples than platform deals (because the add-on doesn’t include the management premium). Search Funders typically pay below median because they’re capital-constrained. Segmenting comps by buyer type produces sharper benchmarks.

How to find comparable companies

Step 1: Define the industry precisely using NAICS or SIC codes. ‘Manufacturing’ is too broad. ‘Precision-machined components for aerospace OEMs’ is more useful. NAICS 332710 (machine shops) is even more specific. Start with the NAICS code, but be willing to deviate — the right comp may have a different NAICS code but the same business model. Conversely, two companies sharing a NAICS code may be very different (e.g., NAICS 561720 covers both janitorial services for office buildings and industrial cleaning of refineries — very different businesses).

Step 2: Filter by size. Match revenue or EBITDA range — ideally within 50-200% of the target’s size. A $10M EBITDA business is best compared to $5-30M EBITDA peers. Public companies are usually too large for direct comparison; precedent transactions are the better source for size-matched comps.

Step 3: Filter by growth profile. A 5%-growing business shouldn’t be compared to a 30%-growing business at the same multiple. Group comps into growth tiers: low-growth (under 5%), moderate (5-15%), high (15-30%), and high-growth (over 30%). Apply different multiple ranges to each tier, with the high-growth tier carrying premiums of 1-3 turns of EBITDA over low-growth peers.

Step 4: Filter by business model. Recurring revenue vs project-based revenue. Capital-intensive vs asset-light. B2B vs B2C. Subscription vs transactional. Product vs service. Even within the same industry, business models can diverge enough to warrant different multiples. A managed-services firm with 80% recurring revenue trades at a different multiple than an integration-services firm with 20% recurring.

Step 5: Filter by margin and profitability. Higher-margin businesses earn higher multiples. A 25% EBITDA margin business is more valuable per dollar of EBITDA than a 10% EBITDA margin business — the higher margin signals pricing power, scale, or operational efficiency. Group comps into margin tiers and compare like-for-like.

Adjustments after comp selection: size, growth, profitability

Size discount: smaller businesses trade at lower multiples. A $50M EBITDA business in the same industry as a $5M EBITDA business will trade at 1-3 turns higher EBITDA multiple. The reasons: more buyer demand (more PE firms can underwrite a $50M EBITDA deal), better financing (lender base is broader and more competitive), perceived stability (larger businesses are seen as more diversified and resilient). The size discount applied to lower-middle-market deals vs upper-middle-market comps is typically 20-40%.

Growth premium: higher-growth businesses trade at higher multiples. A 20%-growing business in the same industry as a 5%-growing peer will earn a multiple premium of 1.5-3.0 turns. The growth premium reflects future earnings power — a $5M EBITDA business growing at 20% will have $10M EBITDA in four years, while the 5% grower will have $6M. Buyers pay for that future growth in the entry multiple.

Profitability/margin premium. Higher-margin businesses trade at higher multiples. A 30% EBITDA margin business signals pricing power and operational efficiency. A 10% margin business is more vulnerable to cost pressures and cyclical earnings. The margin premium is typically 0.5-1.5 turns of EBITDA for businesses with 5-10 percentage points of margin advantage over peers.

Recurring revenue premium. Subscription, contract-based, or recurring-service revenue earns a premium because it’s more predictable and easier to underwrite. A managed IT services firm with 80% recurring revenue can trade at 7-8x EBITDA when project-based IT services trade at 4-5x. The recurring-revenue premium can add 1-3 turns. The premium is highest where recurring revenue exceeds 70% of total.

Customer concentration discount. A business with one customer at 40% of revenue trades at 1-2 turns lower multiple than a peer with diversified customers. The concentration risk — loss of the key customer triggers material EBITDA loss — reduces buyer willingness to pay. Concentration over 25% typically triggers discounts; over 50% triggers steep discounts.

Geographic / market discounts. Tier-1 markets (major metros, growing regions) earn higher multiples than tier-3 markets (small towns, declining regions). The geographic premium reflects buyer demand — more PE firms and Strategics chase deals in growing metros. Tier-3 deals can trade 0.5-1.5 turns below tier-1 peers in the same industry.

Where to find comp data: PitchBook, BVR, BizBuySell, IBBA, SEC

PitchBook: the gold standard for M&A data, but expensive. PitchBook covers private-market transactions extensively, including many lower-middle-market deals. Subscription cost runs in the high four to low five figures per seat per year. PitchBook is the standard at investment banks, PE firms, and large corporate development teams. For a one-off valuation, the cost is often prohibitive — consider engaging an M&A advisor who has PitchBook access rather than buying it directly.

BVR DealStats: lower-middle-market M&A specialty. Business Valuation Resources’ DealStats database focuses on small-business and lower-middle-market transactions — deals from $1M to $100M typically. It’s a fee-based service used by business appraisers and small-business advisors. Annual subscription is more affordable than PitchBook — in the low four figures — and the dataset is purpose-built for the LMM space. Often the best resource for LMM precedent transactions.

BizBuySell Insight Reports: free, smaller deals. BizBuySell publishes quarterly Insight Reports compiling transaction data from its listing platform. Coverage skews toward deals under $5M — main-street businesses and small lower-middle-market deals. Free to access, valuable for understanding multiples in the smaller end of the market. Less useful for $10M+ EBITDA deals where main-street buyer dynamics don’t apply.

IBBA Quarterly Market Pulse: broker survey data. The International Business Brokers Association (IBBA) publishes quarterly Market Pulse reports based on broker surveys. The data covers deal volume, multiples, time-on-market, and broker sentiment by deal-size segment. Free to download, useful for trend analysis (multiples rising or falling), but less precise than transaction-level data. Best used as a directional sanity check.

SEC filings: free public-company peers. SEC filings (10-K, 10-Q, proxy statements, 8-K) are the best free source of public-company financial data and acquisition disclosures. When a public company acquires a target, the proxy or 8-K often discloses the purchase price — a free precedent transaction with detailed financials. Use EDGAR (sec.gov/edgar) to search filings. Public-company multiples can be calculated directly from market cap, debt, and reported EBITDA.

Industry-specific sources. Some industries have dedicated transaction databases. Healthcare has Capital IQ’s healthcare module and HealthCareBuyersInsider. Construction has The Blue Book. SaaS has SaaS Capital and ChartMogul benchmarks. Industry trade associations sometimes publish member-facing benchmarks. Sector-specific databases often have richer data than the generalist platforms.

Public comps vs precedent transactions: which to weight more

Both are useful; weight depends on purpose. For a fairness opinion (is the offered price fair?), both are typically presented and weighted roughly equally. For a sell-side valuation (what should we ask?), precedent transactions are weighted more heavily because they reflect the actual control transactions you’re trying to replicate. For a buy-side underwriting (what should we pay?), precedent transactions also dominate, with public comps as a secondary check.

Use public comps to set the trend and the floor. Public comps move daily; they reflect current market sentiment about the industry. If public comps are compressing, expect precedent transactions to compress with a 6-12 month lag. If public comps are expanding, M&A multiples will follow. Public comps also set a notional floor: M&A buyers won’t pay multiples wildly above public-comp levels for non-strategic deals.

Use precedent transactions to set the actual price range. Precedent transactions tell you what acquirers actually paid for businesses like yours. The range of precedent multiples (25th to 75th percentile) is your defensible value range. The median is a reasonable starting point. Outliers (top or bottom 10%) usually reflect unique circumstances — high synergies in a strategic deal, distressed sale at the bottom — and shouldn’t drive the central case.

Cross-check public comps against precedent transactions. If public comps trade at 8x EBITDA and precedent transactions in your industry are at 5x EBITDA, something is unusual. Maybe the precedent transactions are old (pre-multiple-expansion). Maybe the precedent deals were distressed. Maybe the public companies are far larger and more diversified. Investigate the gap and document the explanation.

Comp screening framework: a step-by-step example

Target: a $4M EBITDA Texas-based commercial HVAC services business with 60% service contract revenue. We want to value this business using relative valuation. Start with the screening framework: industry, size, growth, business model, margin, geography, recency.

Step 1: Industry filter. NAICS 238220 (plumbing, heating, AC contractors). Filter to HVAC services specifically (excluding plumbing-only and electrical-only). Filter to commercial focus (excluding pure residential). Result: HVAC services businesses with commercial customer base.

Step 2: Size filter. Target: $4M EBITDA. Size range for comps: $2-10M EBITDA. Excludes mega-platforms and small main-street operators. This range generally aligns with PE platform thesis and Strategic add-on activity in HVAC.

Step 3: Growth filter. Target: ~10% organic growth. Comparable growth tier: 5-15%. Filter out high-growth deals (greater than 20%) and slow-growth deals (under 5%) for direct comparison; if needed, separate growth tier comps with appropriate adjustments.

Step 4: Business model filter. Target: 60% service contract / recurring revenue, 40% project. Comparable: 50-70% recurring revenue. Recurring revenue is a key value driver in commercial HVAC; mismatched recurring percentages produce meaningfully different multiples.

Step 5: Profitability and geography. Target margin: ~15% EBITDA. Comparable margin: 12-18%. Geography: Texas / sunbelt preferred (similar growth dynamics, similar competitive landscape, similar climate-driven seasonality).

Step 6: Build the comp list and pull multiples. From PitchBook or BVR, identify 8-12 transactions over the past 24 months that match the filters. Pull EBITDA multiples, deal size, buyer type, geography, and growth/margin metrics. Calculate median, 25th percentile, and 75th percentile multiples. Segment by buyer type (Strategic vs PE platform vs PE add-on).

Step 7: Apply adjustments and produce a value range. If the median comp multiple is 6.5x EBITDA and our target has slightly higher recurring revenue (60% vs 55% comp average) and slightly higher growth (10% vs 8% comp average), apply a +0.5x premium. Target multiple: 7.0x EBITDA. Range: 6.0-7.5x. Implied value: $24-30M. Cross-check against public-comp implied value (typically ~15-25% lower than precedent multiples after size discount).

Common pitfalls in relative valuation

Cherry-picking comps to support a desired value. The temptation is real: include the high comps, exclude the low ones, and arrive at the value you wanted. Sophisticated counterparties spot this immediately. A defensible valuation includes all relevant comps, explains exclusions transparently (‘we excluded Comp X because it included a 30% strategic premium for an exclusive technology’), and reports a range, not a single point.

Using stale comps. Multiples move. A 2021 comp at 9x EBITDA may be irrelevant in 2026 if the industry has compressed to 6.5x. Anchoring on stale data leads to mispriced deals. Use comps within 24 months for serious analysis, and weight more recent transactions more heavily. Track the multiple trend explicitly — rising, flat, or compressing.

Mixing public comps and precedent transactions without adjusting for control premium. If you average a 7x public-comp multiple with a 9x precedent-transaction multiple to get 8x, you’ve smushed two different things together incorrectly. Public comps reflect minority trading prices; precedent transactions reflect control prices. Either present them separately or apply a control premium to the public comps before averaging.

Ignoring buyer type. Strategic buyers typically pay 0.5-2.0 turns more than PE buyers because of synergies. PE platform deals trade at higher multiples than PE add-on deals. Search Fund buyers often pay below median due to capital constraints. Failing to segment by buyer type can produce a comp set that’s too generous (if dominated by strategics) or too stingy (if dominated by Search Fund deals).

Not adjusting for size. A $50M EBITDA public company multiple does not directly apply to a $5M EBITDA private business. The size mismatch is too large. Size discounts of 20-40% are typical when applying public-company multiples to LMM private targets. Skipping the size adjustment overstates value, often substantially.

Treating EV/Revenue as interchangeable with EV/EBITDA. EV/Revenue is most useful for high-growth or pre-profit businesses (early-stage SaaS, biotech). For mature, profitable businesses, EV/EBITDA is the right metric — revenue multiples ignore margin differences. A 10% EBITDA-margin business and a 30% EBITDA-margin business in the same industry will have very different EV/EBITDA values even if their EV/Revenue multiples are identical.

Conclusion

Relative valuation is the language of M&A pricing. Buyers, sellers, advisors, and lenders all reference comps when discussing value. The method is intuitive (‘here’s what similar businesses sold for’), defensible (anchored in real transactions), and widely used. Done well, a relative-valuation analysis identifies 6-12 well-matched comps, segments by buyer type, applies size and growth adjustments, and produces a defensible value range. Done poorly, it cherry-picks comps to support a desired number and gets dismantled in the first negotiation. The difference is rigor in comp selection, transparency in adjustments, and a clear narrative for why the chosen multiple applies. Pair the relative valuation with an income approach (EBITDA multiple from comps applied to your forward EBITDA) and an asset approach (floor check), and you have a complete view of value.

Frequently Asked Questions

What is relative valuation?

Relative valuation prices a business by comparing it to similar businesses that have transacted. The two main methods are comparable company analysis (using public-company trading multiples) and precedent transaction analysis (using multiples paid in past M&A deals). It’s the most widely used valuation method in M&A.

What’s the difference between public comps and precedent transactions?

Public comps use the trading multiples of publicly listed peers — what investors pay for minority shares in similar businesses. Precedent transactions use the multiples paid in past M&A deals — what acquirers paid for control of similar businesses. Precedent multiples are typically 15-30% above public comps because of the control premium.

How many comps do I need for a defensible valuation?

6-12 well-chosen comps is the typical range. Fewer than 6 is statistically thin; more than 12 often dilutes the comp set with weaker matches. Within the comp set, segment by buyer type (Strategic, PE platform, PE add-on, Search Fund) and report median + 25th and 75th percentiles.

What if I can’t find good comps in my industry?

If precise industry comps are unavailable, broaden gradually: same NAICS code -> adjacent NAICS code -> same business model in a different industry. Document each step and the rationale. As a fallback, use industry-level multiple ranges from broker reports (IBBA Market Pulse, BizBuySell Insight Reports). Lean more heavily on the income approach when relative-valuation comps are weak.

How recent should comps be?

For serious analysis, within 24 months. Within 12 months is even better. Multiples move with the cycle — 2021 comps were materially higher than 2024 comps. If forced to use older comps, explicitly trend-adjust: if the industry has compressed 1.5 turns since the comp date, subtract 1.5 turns from the comp multiple.

What’s a control premium and how big is it?

The control premium is the additional value paid for 100% ownership vs minority shares. Acquirers paying for control get to set strategy, capture synergies, and take dividends. Public-market minority shares confer none of these. Empirical control premiums in completed acquisitions typically run 15-30% above the trading price before announcement, varying by industry and deal type.

How do I adjust for size?

Smaller businesses trade at lower multiples. The size discount applied when using larger-company comps to value smaller businesses is typically 20-40%, or 1-3 turns of EBITDA. The discount reflects narrower buyer demand, weaker financing, and perceived concentration/key-person risks in smaller targets. Apply the size discount transparently and document the rationale.

What’s a recurring-revenue premium?

Businesses with high recurring revenue (subscription, contract-based, or repeat-customer revenue) trade at higher multiples because their cash flows are more predictable and easier to underwrite. The premium is typically 1-3 turns of EBITDA when recurring revenue exceeds 70% of total. Most pronounced in SaaS, managed services, and contract-based service businesses.

Where can I get free comp data?

BizBuySell Insight Reports (quarterly, smaller deals). IBBA Quarterly Market Pulse (broker survey, all sizes). SEC filings via EDGAR (free public-company financials and acquisition disclosures). Industry trade associations sometimes publish benchmark reports. Free sources are useful for trend analysis but typically thinner on individual transaction detail than fee-based databases.

Should I buy a PitchBook subscription for one valuation?

Probably not. PitchBook subscriptions run in the high four to low five figures per seat per year. For a one-off valuation, the cost is hard to justify. Better options: engage an M&A advisor who has PitchBook access, hire a business appraiser who pulls comp data as part of their engagement, or use a combination of free sources (BizBuySell, IBBA, SEC) plus industry-specific data.

How do I know if my comp set is biased?

Check buyer-type mix: dominated by Strategic deals will skew high; dominated by Search Fund deals will skew low. Check size mix: dominated by upper-middle-market deals will overstate LMM value. Check vintage mix: heavy 2021 weighting will overstate current value. Check geography: tier-1 metros run higher than tier-3. A balanced comp set covers multiple buyer types, sizes, vintages, and geographies; if your set is concentrated in one segment, document the bias and apply corrective adjustments.

Can I use revenue multiples instead of EBITDA multiples?

For mature profitable businesses, EV/EBITDA is the right metric — revenue multiples ignore margin differences. EV/Revenue is most useful for high-growth, pre-profit businesses (early-stage SaaS, biotech) or for cross-checking when EBITDA is volatile or distorted. In LMM transactions, EBITDA multiples dominate; revenue multiples are secondary. Always cross-check with EV/SDE for smaller deals where seller’s discretionary earnings is the operative metric.

About the Author

Christoph Totter is the founder of CT Acquisitions, a buy-side deal origination firm headquartered in Sheridan, Wyoming. CT Acquisitions sources founder-led businesses for 75+ private equity firms, family offices, and search funds across the U.S. lower middle market ($1M–$25M EBITDA). Christoph writes about M&A from the perspective of someone on the phone with both sides of the deal table every week. Connect on LinkedIn · Get in touch