Сопоставимые компании и применение мультипликаторов

Comparable Companies Analysis (Comps) Comparable companies analysis — оценка target company путём сравнения с publicly traded peers. Selecting appropriate comparables и adjusting for differences — critical skills для accurate relative valuation. Selecting comparables Industry: same industry or sub-sector. Consumer staples company shouldn't be compared to tech. Business model: similar operations. Retailer vs e-commerce, even if both «retail», may differ significantly. Size: similar market cap, revenue. Large caps trade differently than small caps. Geography: same или similar markets. Emerging market company vs developed market — different risk profiles. Growth profile: growth companies vs mature. High-growth deserves higher multiple. Profitability: similar margins. Low-margin company shouldn't trade at same EV/Sales as high-margin. Finding comparables Industry classification: GICS (Global Industry Classification Standard), SIC codes. Start point for peer identification. Company filings: management often identifies competitors in 10-K. Useful starting point. Equity research: analysts cover peer groups. Research reports list comparables. Judgment: no perfect match. Use judgment to select most similar companies. Calculating peer multiples For each comparable: calculate chosen multiples (P/E, EV/EBITDA, etc.) using current price и relevant financials. LTM (Last Twelve Months): trailing financials. Actual, reported data. NTM (Next Twelve Months): forward estimates. Consensus analyst forecasts. Calendarization: align fiscal years если comparables have different fiscal year ends. Analyzing peer multiples Range: min, max, median, mean of peer multiples. Shows spread in valuations. Median preferred: less affected by outliers than mean. Single extreme value doesn't skew. Outlier investigation: why is one peer trading at very different multiple? Unique factor, или error? Applying to target Select appropriate multiple: median, mean, или specific peer если very similar. Apply to target's metrics: Target Value = Target Metric × Comparable Multiple. Example: Peers trade at median 10x EV/EBITDA. Target EBITDA = $50M. Target EV = $50M × 10 = $500M. Equity value: EV - Net Debt + Cash = Equity Value. Divide by shares = per share. Adjusting for differences Growth adjustment: if target grows faster than peers, deserves premium. Use PEG ratio (P/E / Growth) for comparison. Margin adjustment: higher margin → higher multiple. Regression analysis can quantify relationship. Risk adjustment: higher risk → lower multiple. Consider leverage, business risk, geographic exposure. Size adjustment: smaller companies often trade at discount (liquidity, risk). Apply small-cap discount if appropriate. Multiple ranges Present range: don't rely on single point estimate. Use 25th-75th percentile of comps for value range. Football field: visual showing valuation ranges from different methods (comps, DCF, transactions). Consensus где ranges overlap. Common pitfalls Wrong comparables: selecting peers that aren't really similar. «Tech» is broad — SaaS vs hardware very different. Ignoring differences: applying median без adjusting for growth, margin, risk differences. Circular reasoning: if market is overvalued, comps will give inflated value. Comps reflect market, не intrinsic value. One-time items: using reported instead of normalized metrics distorts comparison. Normalized multiples Adjust EBITDA: for one-time items, non-recurring costs. Use «adjusted EBITDA» если disclosed. Stock-based compensation: material для tech. Include или exclude consistently across peers. Acquisitions: recent acquirers may have depressed earnings. Normalize for integration costs. Precedent transactions Similar analysis using M&A transactions instead of trading multiples. What acquirers paid for similar companies. Premium: transaction multiples typically higher than trading (control premium). Compare to trading with awareness of premium. Limitations: transactions may be dated, different market conditions. Smaller sample than trading comps. Integration with DCF Cross-check: DCF и comps should give similar values если assumptions consistent. Divergence signals issues. If DCF >> Comps: DCF assumptions too optimistic? Or market undervaluing peers? If DCF Triangulation: use both methods, understand differences, form balanced view.