Spreading Comps: How to Build and Organize the Output Table

Introduction

"Spreading comps" is one of the most common tasks assigned to first-year investment banking analysts. It refers to the process of calculating valuation multiples for each company in the peer group and organizing them into a clean, structured table that can be dropped into a pitchbook, board presentation, or fairness opinion. While the underlying concept is simple (calculate multiples, present them neatly), the execution requires attention to detail, consistent formatting, and the ability to keep the table current as new financial data becomes available.

A well-built comps table follows a consistent structure that allows any reader (MDs, clients, counterparties) to quickly find the information they need. The standard layout flows from left to right in logical sections:

Section 1: Company Identifiers

The leftmost columns identify each company: name, ticker symbol, and sometimes a brief description or sub-sector classification. The target company is typically shown at the top or bottom of the table, visually separated from the peer group (often highlighted or shaded differently). Companies are ordered either alphabetically or by a relevant metric (market cap, most comparable first).

Section 2: Market Data

This section includes the current share price, diluted shares outstanding, equity value (market cap), net debt, and enterprise value. These are the building blocks for calculating EV-based multiples. Some tables also include the 52-week trading range for context.

Section 3: Financial Metrics

Revenue, EBITDA, EBIT, and net income for LTM and NTM periods. Some tables include two forward years (CY and CY+1) for additional context. Operating metrics like revenue growth rate, EBITDA margin, gross margin, and ROIC provide context for understanding why certain companies trade at premium or discount multiples relative to peers.

Section 4: Valuation Multiples

The core output: EV/EBITDA, EV/Revenue, EV/EBIT, P/E, and any sector-specific multiples, calculated for each time period (LTM, NTM, CY+1). This is what the reader came for. The multiples are derived from the market data and financial metrics in the preceding sections.

Section 5: Summary Statistics

At the bottom of the table, summary rows show the mean, median, high, and low for each multiple across the peer group. The 25th and 75th percentile values are sometimes included. These statistics form the benchmark range that is applied to the target to derive the implied valuation.

Comps Spread (Comps Table)

A structured Excel table that displays the valuation multiples of all companies in the peer group, organized into sections for market data, financial metrics, and derived multiples, with summary statistics at the bottom. The comps spread is the primary analytical output of comparable company analysis and is used in pitchbooks, board presentations, and fairness opinions. Most investment banking groups maintain a "master" comps file that covers their coverage universe and is continuously updated by analysts.

Data Sources

The Update Cycle

Comps are not a build-once-and-forget deliverable. They require regular maintenance:

To make the layout concrete, here is a simplified row from a hypothetical consumer products comps table:

In a real model, this table would include 8-12 peers, both LTM and NTM multiples, and additional metrics like ROIC and net debt/EBITDA. The target company would be highlighted separately for comparison.

Investment banks follow strict formatting standards in Excel models. The universal color conventions are: blue font for hard-coded inputs (share price, shares outstanding, manually entered data), black font for formulas and calculations, and green font for links to other worksheets within the same workbook. Each bank may have slight variations, but these three colors are the industry standard.

Additional conventions include multiples shown to one decimal place (11.2x, not 11.234x), the target company row shaded or visually separated from the peer group, clear header labels specifying both the metric and time period ("NTM EV/EBITDA," not just "EV/EBITDA"), and footnotes explaining any adjustments or data limitations.

The goal is a table that is scannable: an MD should be able to glance at it and immediately find the median NTM EV/EBITDA and identify which peers trade at premiums or discounts.

The raw Excel comps table is typically too detailed for a pitchbook slide. When preparing for a presentation, the analyst creates a summary version that includes only the most relevant multiples (usually NTM EV/EBITDA and one or two supplementary metrics), key operating statistics (growth, margins), and summary statistics. This condensed version appears alongside the football field chart in the valuation section of the pitchbook.