Comparable Company Analysis (Comps)
Comparable company analysis (comps) is a relative valuation method that determines a company's value by benchmarking its financial multiples — such as EV/EBITDA, P/E, or P/Sales — against a peer group of publicly traded companies with similar business characteristics.
Comps rests on the premise that similar businesses should trade at similar multiples, and any material divergence represents either a mispricing opportunity or a legitimate difference in quality, growth, or risk that needs to be explained. Building a credible comp set is as much an art as a science.
The first step is peer group selection. Ideal peers share the same industry, similar revenue scale, comparable capital structure, overlapping geography, and a similar business model (pure-play vs diversified, B2B vs B2C). In India, finding true comps can be difficult: a listed company may be the only one in its category, forcing analysts to use cross-sectional comps from global markets or broader sector proxies. For instance, a premium paints company might be compared to Indian FMCG companies for the brand premium component and to regional Asian paints companies for the product-specific multiple.
The key multiples used in Indian equity research include: EV/EBITDA (most widely used for capital-intensive businesses, eliminates capital structure differences); P/E (useful for asset-light, profitable businesses); Price/Book (relevant for banks, NBFCs, and asset-heavy commodity businesses); EV/Revenue (used for early-stage or low-margin businesses where EBITDA is small or negative); and PEG Ratio (P/E divided by growth rate, adjusting for different growth expectations).
Adjustments to raw multiples are often necessary. A company growing earnings at 25 percent annually should logically trade at a higher P/E than a peer growing at 8 percent. Analysts normalise for this using PEG ratios or regression-based approaches. Differences in capital structure, accounting policies (particularly around lease capitalisation post Ind AS 116), and one-time items also require adjustment before multiples are comparable.
A critical pitfall is circular reasoning: if an entire sector is overvalued, comps analysis will validate that overvaluation by treating the elevated peer multiples as the benchmark. This is why comps analysis is most powerful when combined with DCF or reverse DCF analysis, which anchors value in absolute cash flow expectations rather than relative sentiment.