Comps Valuation Excel
by TopAgent
Build a comparable-company (trading comps) analysis in Excel: pick a peer set, gather operating metrics and valuation multiples like EV/EBITDA and P/E, bucket b
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See it in action
You say
Build a trading comps table for a mid-cap SaaS target with $50M EBITDA. Use 8 public peers, calculate EV/EBITDA and P/E, and give me the implied share price range.
Your agent does
I have structured the Excel model. Peer set includes 8 SaaS companies (Adobe, Salesforce, etc.). Median EV/EBITDA is 14.2x. Target implied EV is $710M. After adjusting for $40M net debt and 20M shares, the 25th-75th percentile range is $31.50 - $36.20 per share.
What you get
About this skill
The problem
Building trading comps in Excel is prone to manual errors, from inconsistent TTM periods to broken EV formulas. Most analysts waste hours formatting peer tables and calculating summary statistics instead of analyzing the valuation gaps.
What it does
- Selects a peer set of 6-10 public companies based on industry and business mix.
- Calculates Enterprise Value by aggregating market cap, total debt, and cash balances.
- Computes standard valuation multiples including EV/EBITDA, EV/Revenue, P/E, and P/B.
- Generates a statistical summary block with Mean, Median, Min, Max, and Quartiles.
- Derives an implied valuation range for the target company based on peer medians and quartiles.
Frameworks & tools
Microsoft Excel, Google Sheets.
Why this beats prompting it yourself
This skill enforces strict financial modeling logic, such as using consistent TTM figures and specific Enterprise Value formulas. It ensures that statistical summaries cover the exact peer range and flags outliers that would otherwise skew your median valuation.
Use cases
- Conducting buy-side screens for potential acquisition targets.
- Sanity-checking a Discounted Cash Flow (DCF) valuation with market-based data.
- Preparing valuation slides for investment pitch books or fairness opinions.
- Analyzing valuation gaps between a target and its peer size buckets.
Known limitations
Not suitable for companies without public peers or startups with no revenue. Requires manual entry or an external data source for peer financial inputs.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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