Trading Comparables

Trading comparables (often called 'trading comps' or simply 'comps') is the most commonly used valuation methodology in finance. The logic is straightforward: if similar public companies trade at a certain multiple of their earnings or revenue, then the company you are valuing should trade at a similar multiple, adjusted for differences in size, growth, and profitability.

In PE, trading comps serve as a reality check and a starting reference point. When a deal team evaluates a potential acquisition, they will almost always run a comps analysis before building a DCF or LBO model. Comps tell you what the market thinks similar businesses are worth right now, which grounds the analysis in observable data rather than assumptions.

Step 2: Select the Right Multiples

Different industries trade on different multiples depending on what best captures value creation in that sector. There is no universal 'best' multiple. The key is to use metrics that are meaningful for the target's business model.

• EV/EBITDA is the workhorse multiple in PE. It works for most mature, profitable businesses and is capital-structure neutral. Typical ranges: 6-8x for industrials, 10-15x for software, 8-12x for healthcare services.
• EV/Revenue is used when the target is pre-profit or has highly variable margins (common in early-stage SaaS and biotech). Revenue multiples are less precise because they ignore profitability, but they are sometimes the only option.
• P/E (Price-to-Earnings) is an equity-level multiple that includes the effects of leverage and taxes. PE firms use it less frequently, but it matters for public-market comparisons and for understanding what public investors will pay at exit.
• EV/EBIT is useful when depreciation and amortization are meaningful and differ significantly across peers (e.g., capital-intensive manufacturing).
• Sector-specific metrics include EV/ARR (annual recurring revenue) for SaaS, EV/beds for hospitals, EV/subscriber for media, and price/AUM for asset managers.

Step 3: Adjust for Differences

Raw multiples from a peer group always show a range, not a single number. The question is where within that range the target should fall. This requires adjusting for systematic differences between the target and its peers.

The most common adjustment factors are:

• Growth — Faster-growing companies deserve higher multiples. If the target grows at 15% and the median peer grows at 8%, the target should trade at a premium.
• Margins — Higher-margin businesses convert more revenue to profit and are valued more richly. A company with 35% EBITDA margins should trade at a higher multiple than one with 20% margins, all else equal.
• Size — Larger companies tend to trade at higher multiples due to lower perceived risk, greater liquidity, and operational diversification. This is called the 'size premium.'
• Recurring vs. one-time revenue — Businesses with recurring, contracted revenue (subscriptions, maintenance contracts) trade at premiums to businesses with project-based or transactional revenue.
• Customer concentration — A company where the top 3 customers represent 60% of revenue is riskier than one with a fragmented customer base.

These adjustments are inherently judgmental. Two analysts looking at the same data may place the target at different points within the range. This is normal and expected. The goal is not false precision but a defensible range.

Interpreting the Output Range

A comps analysis produces a valuation range, not a single number. The typical output includes the 25th percentile, median, mean, and 75th percentile of multiples across the peer group. You then apply these multiples to the target's financial metrics (EBITDA, revenue, etc.) to derive an implied enterprise value range.

Key principles for interpretation:

• The median is your anchor. Start with the median multiple and then argue up or down based on the target's relative strengths and weaknesses.
• Outliers distort the mean. If one peer trades at 25x EBITDA because it is being acquired, the mean will be skewed. Always check for outliers and consider whether to exclude them.
• Forward multiples are more relevant than trailing. NTM (next twelve months) multiples reflect where the market expects the business to go, which matters more than where it has been. Use forward consensus estimates when available.
• Comps reflect current market sentiment. If the market is in a downturn, all multiples will be compressed. Comps tell you what the market will pay today, not what the business is intrinsically worth. This is both a strength (it is market-based) and a limitation (it can be distorted by cycles).