{{target_company}}
Target Company
Example: Example: Atlas Digital Payments Ltd.
Enter the company being valued.
Build a comparable-company and precedent-transaction matrix with transparent peer selection, normalized metrics, valuation multiples, adjustments, and implied value ranges.
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.
Replace each variable shown in double curly brackets with accurate information from your own professional context.
{{target_company}}
Example: Example: Atlas Digital Payments Ltd.
Enter the company being valued.
{{business_profile}}
Example: Describe products, customers, geographies, growth, margins, capital intensity, and maturity.
The profile determines peer relevance.
{{comparable_companies}}
Example: Provide company names, market data, financials, fiscal periods, and business descriptions.
Use current, sourced, and consistently defined information.
{{precedent_transactions}}
Example: Provide transaction dates, buyers, sellers, enterprise values, financials, premiums, and strategic context.
Label announced, completed, withdrawn, and distressed transactions separately.
{{target_financials}}
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}}
Example: Define valuation date, currency, enterprise value, lease treatment, fiscal periods, and source dates.
Clear definitions are necessary for consistent multiples.
{{output_format}}
Choose the format required for research, transaction work, or model construction.
A transparent relative-valuation matrix containing peer methodology, public and transaction multiples, normalization adjustments, outliers, selected ranges, enterprise-to-equity bridge, and limitations.
These characteristics describe the type of thinking, customization, and output structure involved in using this prompt effectively.
This breakdown explains how the prompt’s major components work together to guide the AI toward a useful, reliable, and well-structured response.
Positions the AI as an investment-banking and equity-research valuation specialist.
Defines the target, business profile, peers, transactions, target financials, and data definitions.
Requires consistent public-comps and precedent-transaction valuation matrices.
Prevents invented market data, transaction terms, premiums, synergies, and fairness opinions.
Requires methodology, matrices, statistics, ranges, bridges, limitations, and questions.
Target, business profile, comparable companies, transactions, target financials, definitions, and output format.
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.
Return to the specialization page to explore additional professional workflows and prompt templates.
Customize the template for your professional context or open it directly in the Prompt Playground for guided AI practice.