Compare Valuation Multiples Across Peers: AI Prompt for Claude & ChatGPT
Copy this Claude prompt to compare P/E, EV/EBITDA, and P/FCF across peers for stock analysis. Works with Claude, ChatGPT, Gemini, and Grok.
This AI prompt for stock research builds a structured valuation-comp table across named peers. Copy the template into Claude, ChatGPT, Gemini, or Grok and replace the ticker placeholders with filing-backed figures.
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The Compare Valuation Multiples Across Peers prompt (Claude, ChatGPT, Gemini, Grok)
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You are a senior equity research analyst building a peer valuation comp for an institutional research report. Compare valuation multiples for the following companies in [SECTOR/INDUSTRY]: **Primary subject:** [TICKER_1] ([NAME_1]) **Peer group:** [TICKER_2] ([NAME_2]), [TICKER_3] ([NAME_3]), [TICKER_4] ([NAME_4]), [TICKER_5] ([NAME_5]) ## Context Use the most recent widely available figures. State the data source and as-of date for every metric. If a metric is not meaningful for a company (e.g. negative earnings), note "N/M" and explain why. ## Required Analysis ### Part 1 - Comp Table Build a structured comparison table with these columns: | Metric | [TICKER_1] | [TICKER_2] | [TICKER_3] | [TICKER_4] | [TICKER_5] | Peer Median | Include these rows: - Market Cap ($B) - Enterprise Value ($B) - Revenue TTM ($B) - Revenue Growth YoY (%) - Gross Margin (%) - EBITDA Margin (%) - P/E Trailing - P/E Forward (NTM consensus if available) - EV/EBITDA - EV/Sales - P/FCF - Net Debt / EBITDA ### Part 2 - Premium / Discount Analysis For [TICKER_1], calculate: - Premium or discount to peer median on each multiple (expressed as %) - Whether the premium/discount is justified by growth, margins, or other fundamental differences - Historical valuation range for [TICKER_1] over the past 3-5 years vs current level ### Part 3 - Key Comparability Adjustments List specific issues that affect apples-to-apples comparison: - GAAP vs non-GAAP earnings definitions (which peers use adjusted numbers?) - Fiscal year end differences - M&A or divestitures that distort TTM figures - Capital structure differences (heavy debt, significant cash) ### Part 4 - Valuation Drivers Summary For each company, write 1-2 sentences on why the market may be assigning its current multiple (e.g. growth rate, margin profile, capital returns, risk factors). ### Part 5 - Follow-Up Research List 3-5 questions for further investigation (e.g. "Is [TICKER_3]'s forward P/E discount to peers driven by decelerating growth or a one-time margin headwind?"). ### Part 6 - Visual Verification & Chart Follow-Up - Identify 2-3 visual inflection points that require multi-year chart inspection across peers (e.g. historical valuation bands, EV/Sales vs growth, and margin profile comparisons). - Provide the direct Chartloom visual research link for the primary ticker: https://www.chartloom.com/c/ticker/[TICKER_1] ## Output Format Use clean tables, headers, and bullets. Neutral, research-oriented language. Do not suggest buying or selling any security. **Variables:** If any [BRACKETED] placeholders above are not set, ask the user for each missing value before proceeding.
Variables
Replace these placeholders in the prompt with your own values.
| Placeholder | Description | Example |
|---|---|---|
| [SECTOR/INDUSTRY] | Sector or industry for context and peer selection. | Enterprise Cloud Software |
| [TICKER_1] | Primary company ticker. | CRM |
| [NAME_1] | Primary company name. | Salesforce |
| [TICKER_2] | Second peer ticker. | WDAY |
| [NAME_2] | Second peer company name. | Workday |
| [TICKER_3] | Third peer ticker. | NOW |
| [NAME_3] | Third peer company name. | ServiceNow |
| [TICKER_4] | Fourth peer ticker (use N/A to omit). | HUBS |
| [NAME_4] | Fourth peer company name. | HubSpot |
| [TICKER_5] | Fifth peer ticker (use N/A to omit). | DDOG |
| [NAME_5] | Fifth peer company name. | Datadog |
How to use this prompt
Replace [SECTOR/INDUSTRY] and all [TICKER_N] / [NAME_N] pairs with your peer set. Set any unused peers to "N/A". The prompt is structured to produce an institutional-quality comp table. Use the output as a starting point - always verify data points against primary sources.
Tips
- Choose peers with similar business models, revenue scale, and end markets for the most useful comparison.
- Pay attention to whether the AI uses GAAP or non-GAAP figures; the prompt asks it to disclose this.
- For cyclical sectors, consider requesting normalized or mid-cycle multiples instead of trailing.
- The peer median is more useful than the peer average (less distorted by outliers).
- Request the AI to specify data sources so you can verify independently.
When to use this prompt
Building an institutional-quality comp table for a new sector coverage initiation
Checking whether a stock is relatively expensive or cheap before deeper fundamental work
Preparing valuation context for an earnings preview or quarterly review
Identifying outlier valuations in a sector that warrant further investigation
Frequently Asked Questions
It depends on the sector. P/E is common but can be distorted by one-time items. EV/EBITDA and EV/Sales are often used for capital structure neutrality. P/FCF is useful when cash flow quality is a focus. The prompt requests several multiples so researchers can triangulate.
Absolute multiples are hard to interpret in isolation. Comparing to the peer median helps contextualize whether a company is valued higher or lower than similar businesses, and whether that gap is justified by fundamentals.
Yes, though you should note currency differences and whether figures are reported under IFRS vs US GAAP, as this affects comparability of certain metrics.
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Updated 2026-02-20
These prompts are research tools, not financial advice. Outputs should be independently verified. They are not a recommendation to buy, sell, or hold any security. See our disclaimer for more information.