Comparable Company Analysis with AI: Trading Comps and Valuation Multiples (2026)

Comparable Company Analysis and AI

Trading comps is the backbone of equity valuation — every investment banking pitch book, fairness opinion, and equity research initiation includes a comps table. Building it manually means pulling financials from 10-15 annual reports, computing EBITDA adjustments for each peer, calculating enterprise value from market cap and net debt, and normalizing everything to the same fiscal year end. Claude with ClaudeFinLab compresses that work into a structured, conversational workflow.

Peer Group Selection

• "Select the comparable company peer group for a mid-market SaaS company: $85M ARR, 120% net revenue retention, land-and-expand motion, selling to mid-market enterprises (200-2,000 employees), vertical focus in HR/workforce management. Criteria: publicly traded, US-listed, SaaS business model, mid-market focus, $50M-$500M ARR range. Suggest 8-10 peers with rationale for inclusion and any borderline cases."
• "For a specialty chemicals manufacturer (EBITDA $42M, revenue $280M, end markets: automotive 40%, aerospace 35%, industrial 25%), build the comparable universe. Key screening criteria: specialty chemicals or advanced materials, EBITDA margin >10%, US or European listed, revenue $150M-$1.5B. Identify 8 core peers and 4 secondary peers. Flag any peers with business mix that differs materially from the subject."
• "Critique this proposed peer group for a regional bank ($4.2B assets, commercial bank focus, Sun Belt markets): [list 12 peers]. For each, note: (a) asset size alignment, (b) geographic market similarity, (c) business mix comparability, (d) whether the peer has any one-time items distorting multiples. Recommend cutting or adding peers to tighten the group."

Spreading the Comps Table

• "Spread the comps table for these 8 SaaS peers. For each: [paste financials]. Compute LTM ARR, LTM Revenue, LTM Gross Margin %, LTM EBITDA (if positive), LTM FCF. Market cap as of [date]. Net cash/(debt). Enterprise value. Calculate: EV/LTM Revenue, EV/NTM Revenue (using consensus estimates), EV/LTM Gross Profit, EV/NTM ARR. Format as a table with median and mean rows."
• "For each peer in the comps table, compute the EBITDA adjustments: (1) add back stock-based compensation (show SBC as % of revenue), (2) add back restructuring charges if non-recurring, (3) normalize for any R&D capitalization differences. Show adjusted EBITDA and adjusted EBITDA margin alongside reported EBITDA for each peer."
• "Compute enterprise value for each peer: [list with market caps, shares outstanding, debt, cash, preferred stock, minority interest]. Enterprise value = market cap + debt + preferred + minority interest - cash. Show each component. Flag any peers with net cash positions (negative net debt) as they will show lower EV/EBITDA."

Multiple Analysis and Benchmarking

• "Analyze the comps table output: median EV/EBITDA 11.2x, mean 12.1x, range 8.5x-16.3x. Subject company LTM EBITDA $42M, NTM EBITDA (management projection) $51M. Derive the implied enterprise value range using: (1) median LTM multiple, (2) mean LTM multiple, (3) 25th-75th percentile range. Apply NTM multiple to get forward-based range. Build a football field summary."
• "The subject company trades at a discount to peers (implied EV/EBITDA 7.8x vs peer median 11.2x). Analyze the discount: (a) identify which financial metrics are below median (growth, margin, FCF conversion), (b) assess qualitative factors (customer concentration, IP moat, management tenure), (c) estimate a warranted discount or if the company should trade at parity with the right buyer/improvements."
• "Build the sector premium/discount framework: for this industrial peer group, which companies trade at >1.0x premium to median EV/EBITDA? What financial or strategic characteristics correlate with premium multiples? Regression: EV/EBITDA vs EBITDA margin, revenue growth CAGR, and FCF yield. Identify the R-squared for each driver."

Sector-Specific Multiples

• "Build a bank trading comps table using the relevant multiples: P/TBV (price to tangible book value), P/E (NTM), dividend yield, and ROE (return on tangible equity). For each peer bank: [financials]. Calculate: tangible book value per share (total equity less goodwill and intangibles), P/TBV, efficiency ratio, NIM (net interest margin). The appropriate multiple for banks is P/TBV, not EV/EBITDA."
• "For this REIT comps table, use real estate-appropriate metrics: Price/FFO (funds from operations), Price/AFFO (adjusted FFO), EV/NOI (net operating income), implied cap rate (NOI/EV), and dividend yield. [Paste peer data]. Compute FFO by adding back D&A to net income (standard REIT adjustment) and any impairment charges. Format full comps table."

Comps in the Context of a Full Valuation

• "Triangulate the valuation: comps imply EV $380M-$480M (EV/EBITDA 9-11x on $44M LTM EBITDA). DCF implies EV $420M-$510M (WACC 10-12%, terminal growth 2.5%). Precedent transactions imply EV $480M-$560M (transaction multiples 11-13x, typical control premium 20-30%). Build a football field chart showing each methodology's range. What is the appropriate weight to assign each and why?"

Where to Start with Comps Analysis

Connect Claude to ClaudeFinLab's SEC EDGAR MCP server — it pulls financial data directly from 10-K and 10-Q filings for any public company. Describe the subject company's business, revenue profile, and geography. Ask Claude to propose the peer group with rationale. Then ask it to spread the comps table using the pulled financials. The full process — peer selection through implied valuation range — takes a fraction of the time it takes manually.