Public Market Comps and Precedent Transactions Matrix

Build a comparable-company and precedent-transaction matrix with transparent peer selection, normalized metrics, valuation multiples, adjustments, and implied value ranges.

Professional Prompt Template

Public Market Comps and Precedent Transactions Matrix

Build a comparable-company and precedent-transaction matrix with transparent peer selection, normalized metrics, valuation multiples, adjustments, and implied value ranges.

Best suited for: ChatGPT Claude Gemini
💬
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Complete Prompt

🪄 Prompt Playground

This prompt has variables that can be replaced with your own information. Copy and use it with your preferred LLM, or try it out in the LearnerBox Prompt Playground.

Act as a senior investment-banking and equity-research analyst specializing in relative valuation.

Build a public-market comparable-company and precedent-transaction matrix using the information provided below.

Target company:
{{target_company}}

Industry and business profile:
{{business_profile}}

Comparable companies:
{{comparable_companies}}

Precedent transactions:
{{precedent_transactions}}

Target financials and adjustments:
{{target_financials}}

Market-data and transaction-data definitions:
{{data_definitions}}

Analysis requirements:

1. Define the peer-selection criteria, including:
   - business model;
   - products and services;
   - customer base;
   - geography;
   - size;
   - growth;
   - margins;
   - capital intensity;
   - cyclicality;
   - regulation;
   - ownership; and
   - maturity.
2. Classify peers as:
   - core;
   - secondary;
   - aspirational;
   - special situation; or
   - excluded.
3. Explain every inclusion and exclusion.
4. Normalize company and target financials for:
   - one-time items;
   - leases;
   - stock compensation;
   - restructuring;
   - acquisitions;
   - discontinued operations;
   - different fiscal year-ends;
   - accounting standards; and
   - non-controlling interests.
5. Calculate applicable public-market multiples, such as:
   - EV/Revenue;
   - EV/EBITDA;
   - EV/EBIT;
   - P/E;
   - price-to-book;
   - free-cash-flow yield; and
   - sector-specific multiples.
6. Calculate precedent-transaction multiples using consistent definitions.
7. Identify transaction premiums, control premiums, synergies, market conditions, and deal-specific factors where supplied.
8. Compare median, mean, quartiles, and range.
9. Identify outliers and explain whether to retain or exclude them.
10. Apply selected multiple ranges to the target’s relevant financial metric.
11. Build an enterprise-to-equity bridge and implied value-per-share range.
12. Compare public-market and precedent-transaction outputs.
13. Do not invent market prices, financial data, transaction terms, premiums, or synergy values.
14. Use dated and sourced data only.
15. Do not present the output as an investment or fairness opinion.

Present the result as:
{{output_format}}

Include:
- peer-selection methodology;
- public comps matrix;
- precedent-transactions matrix;
- normalization adjustments;
- multiple statistics;
- outlier analysis;
- selected valuation ranges;
- implied enterprise value;
- equity-value bridge;
- value-per-share range;
- methodological limitations; and
- validation questions.
Personalize the Template

Customization Variables

Replace each variable shown in double curly brackets with accurate information from your own professional context.

{{target_company}}

Target Company

Required

Example: Example: Atlas Digital Payments Ltd.

Enter the company being valued.

{{business_profile}}

Industry and Business Profile

Required

Example: Describe products, customers, geographies, growth, margins, capital intensity, and maturity.

The profile determines peer relevance.

{{comparable_companies}}

Comparable Companies

Required

Example: Provide company names, market data, financials, fiscal periods, and business descriptions.

Use current, sourced, and consistently defined information.

{{precedent_transactions}}

Precedent Transactions

Optional

Example: Provide transaction dates, buyers, sellers, enterprise values, financials, premiums, and strategic context.

Label announced, completed, withdrawn, and distressed transactions separately.

{{target_financials}}

Target Financials and Adjustments

Required

Example: Provide revenue, EBITDA, EBIT, earnings, debt, cash, shares, leases, and normalization items.

Use the same definitions and periods applied to the peer set.

{{data_definitions}}

Market-Data and Transaction-Data Definitions

Required

Example: Define valuation date, currency, enterprise value, lease treatment, fiscal periods, and source dates.

Clear definitions are necessary for consistent multiples.

{{output_format}}

Output Format

Required

Choose the format required for research, transaction work, or model construction.

Comparable valuation report Investment-banking valuation matrix Equity-research peer analysis Spreadsheet model specification
What the AI Should Produce

Expected Output

🎯

A transparent relative-valuation matrix containing peer methodology, public and transaction multiples, normalization adjustments, outliers, selected ranges, enterprise-to-equity bridge, and limitations.

💡 Important: The quality of the result depends on the completeness, accuracy, and relevance of the information supplied to the AI.
Prompt Profile

Prompt Characteristics

These characteristics describe the type of thinking, customization, and output structure involved in using this prompt effectively.

🧠 Reasoning Depth Advanced
💡 Creativity Low
🛠 Customization High
📚 Output Structure Highly Structured
🎓 Experience Level Advanced
Learn Why It Works

Prompt Anatomy

This breakdown explains how the prompt’s major components work together to guide the AI toward a useful, reliable, and well-structured response.

💼

Role

Positions the AI as an investment-banking and equity-research valuation specialist.

📄

Context

Defines the target, business profile, peers, transactions, target financials, and data definitions.

🎯

Task

Requires consistent public-comps and precedent-transaction valuation matrices.

🛡️

Constraints

Prevents invented market data, transaction terms, premiums, synergies, and fairness opinions.

📚

Output Structure

Requires methodology, matrices, statistics, ranges, bridges, limitations, and questions.

🔑

Input Variables

Target, business profile, comparable companies, transactions, target financials, definitions, and output format.

Improve the Result

Customization Tips

  1. Use dated market data and consistent fiscal periods.
  2. Separate core peers from aspirational or special-situation peers.
  3. Normalize accounting and one-time items before comparing multiples.
  4. Treat transaction premiums and synergies as deal-specific rather than universal.
  5. Explain outlier exclusions instead of removing them silently.
🛡️
Responsible Professional Use

Review Before Applying the Output

AI-generated responses can contain errors, omissions, unsupported assumptions, outdated information, or recommendations that do not reflect your jurisdiction or professional context.

Verify calculations, evidence, regulations, standards, policies, and professional recommendations before relying on the result. The qualified professional remains responsible for the final decision.

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