agentleFS
brainbytes-devbrainbytes-dev/everything-claude-finance/skills/investment-banking/comparable-analysis/SKILL.md

comparable-analysis

Skill9 starsChanged 8 months agoMITView on GitHub

name: comparable-analysis description: Comparable company analysis (trading comps) Trading comps derive implied valuation from how the public market values similar companies today. Unlike DCF (intrinsic value) or precedent transactions (transaction value with control premium), comps reflect current market sentiment and minority-stake value. Primary screening criteria: - Industry / sub-sector (SIC/NAICS codes as starting point, then refine) - Business model similarity (asset-light vs asset-heavy, recurring vs transactional revenue) - Geographic exposure (domestic vs international revenue mix) - Size (enterprise value within…

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

7 rules. About 0 are common, 7 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈7

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Best practice: Start with 15-25 candidates, narrow to 8-12 core peers.

    line 31
  2. Distinctive:

    When peers have different fiscal year-ends, calendarize to a common period:

    line 55
  3. Distinctive:

    Always calendarize to the target's fiscal year-end or calendar year.

    line 65
  4. Distinctive:

    Use "adjusted EBITDA" as reported by company, but verify adjustments are legitimate

    line 74
  5. Distinctive:

    Add unfunded pension obligations to enterprise value

    line 85
  6. Distinctive:

    Ensure consistency across peer group

    line 86
  7. Distinctive:

    Before finalizing a comparable analysis, verify:

    line 189

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Comparable Company Analysis

name: comparable-analysis description: Comparable company analysis (trading comps)

When to Activate

  • User needs to value a company using market-based relative valuation
  • Selecting peer groups or relevant trading multiples
  • Calendarizing financials for peer comparison
  • Applying multiples to derive an implied valuation range
  • Benchmarking a company's valuation against its sector

Core Concepts

What Trading Comps Measure

Trading comps derive implied valuation from how the public market values similar companies today. Unlike DCF (intrinsic value) or precedent transactions (transaction value with control premium), comps reflect current market sentiment and minority-stake value.

Peer Group Selection

Primary screening criteria:

  • Industry / sub-sector (SIC/NAICS codes as starting point, then refine)
  • Business model similarity (asset-light vs asset-heavy, recurring vs transactional revenue)
  • Geographic exposure (domestic vs international revenue mix)
  • Size (enterprise value within 0.5x-2.0x of target, or revenue-based)
  • Growth profile (revenue growth rate within similar band)
  • Margin profile (EBITDA margin within comparable range)
  • Capital structure (leverage ratios)

Best practice: Start with 15-25 candidates, narrow to 8-12 core peers. Include a "broader universe" for context.

Common pitfalls:

  • Including conglomerates where the comparable segment is a small fraction
  • Mixing high-growth SaaS companies with mature software businesses
  • Ignoring geographic or regulatory differences that drive margin divergence

Relevant Multiples by Sector

SectorPrimary MultiplesSecondary Multiples
Technology / SaaSEV/Revenue, EV/ARREV/EBITDA, P/E, Rule of 40
IndustrialsEV/EBITDAP/E, EV/EBIT
Financial ServicesP/E, P/BookROE-adjusted P/B
Real Estate / REITsP/FFO, P/AFFOEV/EBITDA, NAV
Healthcare / PharmaEV/EBITDAEV/Revenue (pre-revenue biotech)
Retail / ConsumerEV/EBITDAEV/Revenue, P/E
Energy / MiningEV/EBITDAEV/DACF, EV/2P reserves
BanksP/E, P/TBVNet interest margin, ROE
InsuranceP/E, P/BookCombined ratio
TelecomEV/EBITDAEV/Subscriber, EV/Revenue

Calendarization

When peers have different fiscal year-ends, calendarize to a common period:

Calendarized Metric = (Stub Months / 12) × Next FY Estimate
                    + (Remaining Months / 12) × Current FY Estimate

Example: Target has Dec year-end. Peer has Mar year-end.

  • For CY2025: 3/12 of FY Mar-2025 + 9/12 of FY Mar-2026

Always calendarize to the target's fiscal year-end or calendar year.

Key Adjustments

One-time / non-recurring items:

  • Restructuring charges
  • Litigation settlements
  • Asset impairments
  • Gain/loss on asset sales
  • Use "adjusted EBITDA" as reported by company, but verify adjustments are legitimate

Stock-based compensation:

  • SBC is a real economic cost; preferred to use EBITDA less SBC for tech companies
  • At minimum, show multiples both with and without SBC adjustment

Operating lease adjustments (pre-IFRS 16):

  • Capitalize operating leases: add PV of lease commitments to EV, add back rent to EBITDA
  • Post-IFRS 16/ASC 842: already on balance sheet, but be consistent across peers

Pension adjustments:

  • Add unfunded pension obligations to enterprise value
  • Ensure consistency across peer group

Net debt calculation:

Net Debt = Short-term Debt + Long-term Debt + Capital Leases
         + Preferred Stock + Minority Interest
         - Cash & Cash Equivalents
         - Short-term Investments (if liquid)

Methodology

Step-by-Step Trading Comps Process

  1. Select peer universe — use criteria above, document rationale for inclusion/exclusion
  2. Gather financial data — historical (LTM) and consensus estimates (NTM, NTM+1)
  3. Calendarize — align all peers to common fiscal period
  4. Calculate enterprise value — market cap + net debt + minority interest + preferred
  5. Compute multiples — EV-based (EV/Revenue, EV/EBITDA, EV/EBIT) and equity-based (P/E, P/Book)
  6. Apply adjustments — normalize for one-time items, SBC, lease treatment
  7. Analyze distribution — mean, median, 25th/75th percentile
  8. Apply to target — multiply target's metrics by selected multiple range
  9. Derive implied valuation range — present as range, not point estimate

Applying Multiples to Derive Valuation

Implied Enterprise Value = Target Metric × Selected Multiple

Example:
Target NTM EBITDA:     $150m
Peer Median EV/EBITDA: 12.0x
Peer 25th-75th:        10.5x - 13.5x

Implied EV Range:      $1,575m - $2,025m (median: $1,800m)

Then apply equity bridge (subtract net debt, minority interest, etc.) to arrive at equity value.

Premium / Discount Considerations

Apply a premium or discount to peer multiples when target differs materially:

  • Growth premium: Target grows faster than peers → justify higher multiple
  • Margin premium: Target has structurally higher margins → higher multiple
  • Size discount: Target is meaningfully smaller → lower multiple (illiquidity)
  • Geographic discount: Target operates in higher-risk jurisdictions
  • Customer concentration discount: Revenue concentrated in few customers

Templates

Trading Comps Table

=== COMPARABLE COMPANY ANALYSIS ===

Valuation Date: [Date]
Target Company: [Name]

--- Peer Group ---
Company          | EV ($m) | Rev ($m) | EBITDA ($m) | NTM Rev Gr | EBITDA Margin
Peer A           |  ____   |  ____    |    ____     |    ___%    |    ___%
Peer B           |  ____   |  ____    |    ____     |    ___%    |    ___%
Peer C           |  ____   |  ____    |    ____     |    ___%    |    ___%
...              |         |          |             |            |

--- Trading Multiples ---
Company          | EV/Rev LTM | EV/Rev NTM | EV/EBITDA LTM | EV/EBITDA NTM | P/E NTM
Peer A           |    ___x    |    ___x    |     ___x      |     ___x      |  ___x
Peer B           |    ___x    |    ___x    |     ___x      |     ___x      |  ___x
Peer C           |    ___x    |    ___x    |     ___x      |     ___x      |  ___x

Mean             |    ___x    |    ___x    |     ___x      |     ___x      |  ___x
Median           |    ___x    |    ___x    |     ___x      |     ___x      |  ___x
25th Percentile  |    ___x    |    ___x    |     ___x      |     ___x      |  ___x
75th Percentile  |    ___x    |    ___x    |     ___x      |     ___x      |  ___x

--- Implied Valuation ---
Metric Applied       | Target Value | Low Multiple | High Multiple | Low EV   | High EV
EV/EBITDA NTM        |    $____m    |    ___x      |     ___x      | $____m   | $____m
EV/Revenue NTM       |    $____m    |    ___x      |     ___x      | $____m   | $____m

Implied EV Range:    $____m - $____m
Less: Net Debt       ($____m)
Implied Equity:      $____m - $____m
Per Share:           $____ - $____

Peer Selection Documentation

=== PEER GROUP RATIONALE ===

Included:
- [Peer A]: [Rationale — similar business model, size, geography]
- [Peer B]: [Rationale]

Excluded:
- [Company X]: [Reason — conglomerate, different growth profile, etc.]
- [Company Y]: [Reason]

Quality Gate

Before finalizing a comparable analysis, verify:

  • Peer group contains 8-12 companies with genuine business model similarity
  • Financials are calendarized to a common period
  • Enterprise value includes all non-equity claims (debt, minorities, preferred, pensions)
  • Multiples are calculated on both LTM and NTM basis
  • One-time items are adjusted consistently across all peers
  • SBC treatment is consistent (either included or excluded for all peers)
  • Outliers are identified and explained (do not silently exclude)
  • NTM estimates use consensus from a reliable source (FactSet, Bloomberg, Capital IQ)
  • Implied valuation is presented as a range, not a single point
  • Premium/discount to peers is justified with specific operational differences
  • Multiples are cross-checked for reasonableness given sector norms
  • Diluted share count uses treasury stock method for target

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.