Comparable company analysis: Finding the right Peers
The single most important decision in valuation is not the formula you use. It is the companies you choose to compare. Comparable company analysis (comps) serves as the workhorse valuation method used by Wall Street analysts and investment bankers worldwide. Its apparent simplicity masks a technique that can swing valuations by 50% or more based solely on peer selection. For Indian investors analysing U.S. stocks, mastering comparable company (comps) analysis provides a powerful framework for determining whether your target investment trades at a premium, discount, or fair value relative to similar businesses.
This relative valuation method is a core tool of fundamental analysis for Indian investors building portfolios in the U.S. markets.
Selecting peer companies determines everything in comps analysis
Selecting comparable companies is the most critical step in the analysis. Wrong peer selection directly distorts the implied valuation. No amount of sophisticated multiple analysis can compensate for poorly chosen comparables.
The Global Industry Classification Standard (GICS) serves as the dominant system used by investment professionals. Developed by MSCI and S&P Dow Jones, GICS uses a four-tier hierarchy spanning 11 sectors, 25 industry groups, 74 industries, and 163 sub-industries. Companies receive an 8-digit code based on their principal business activity, primarily determined by revenues.
Critical GICS classifications surprise many investors. Amazon is classified as Consumer Discretionary under retail, not Technology. Tesla falls under Consumer Discretionary, not Technology or Energy. Netflix is classified in the Communication Services industry within the entertainment sector.
Eight criteria guide peer company selection. Industry and sector alignment should match the same or adjacent GICS sub-industry. Business model similarity requires overlap in core operational frameworks, monetisation, and customer types. The geographic mix should reflect similar exposure to developecapitalisation markets. Market capitalisation should fall within plus or minus 20-30% of the target. The revenue scale should match the same order of magnitude. The growth profile should align with similar 3-5-year revenue and earnings growth stages. Profitability margins should show comparable gross, EBITDA, and net margins. Capital structure should reflect similar debt-to-equity and leverage ratios.
The Tesla example perfectly illustrates peer selection challenges. If classified purely as an auto company, peers like GM and Ford trade at 3-7x P/E, but Tesla trades at 90-140x P/E. A blended peer approach, including traditional automakers, pure-play EV companies such as Rivian and Lucid, and autonomous technology firms, provides a clearer context.
The professional consensus centres on 5-10 companies as the optimal peer range, with 5-7 often cited as the sweet spot. Start with 15-20 potential peers in the initial screening, then narrow the list through detailed analysis. Too few peers below 5 create unreliable statistical significance, where a single unusual company can dramatically skew the results. Too many peers above 15 dilutes relevance as broader sets include fewer comparable companies.
SEC filings provide the richest source for finding peers. The 10-K Item 1 Business section describes products, markets, and competitive factors. Item 1A Risk Factors nearly always discusses competition and identifies competitor types. DEF 14A Proxy Statements disclose compensation peer groups used for executive pay benchmarking. These reveal who management considers comparable.
Key multiples to use vary by sector and business model
Understanding valuation multiples requires grasping the fundamental distinction between equity multiples and enterprise value multiples. Equity multiples like P/E, P/B, and P/S measure value to shareholders only, using marketcapitalisationn in the numerator and after-debt metrics in the denominator. They are affected by differences in capital structure.
Enterprise value multiples such as EV/EBITDA, EV/EBIT, and EV/Revenue measure total firm value, including both debt and equity. They are capital-structure-neutral, making them preferred for comparing companies with different levels of leverage.
P/E Ratio equals Stock Price divided by Earnings Per Share, or Market Cap divided by Net Income.
For a deeper dive into understanding the P/E ratio to value stocks, this metric works best when comparing companies within the same industry.
The current S&P 500 forward P/E stands at 22.1x versus a 10-year average of 18.8x, indicating elevated valuations.
EV/EBITDA equals Enterprise Value divided by EBITDA. This is the most widely used multiple across industries because it is capital-structure- and tax-neutral, and less affected by accounting policy differences. Current S&P 500 sector EV/EBITDA ranges from 8.56x for Energy to 27.49x for Information Technology.
EV/Revenue equals Enterprise Value divided by Total Revenue. This works best for early-stage or high-growth companies with negative EBITDA, SaaS businesses, and cross-company comparisons when profitability differs significantly.
P/B Ratio equals Market Cap divided by Shareholders' Equity. This is essential for banks and financial institutions whose business models depend on leverage. Current money centre bank P/B averages 1.32x while regional banks average 1.13x.
Different sectors require different multiples. Technology high-growth companies use EV/Revenue and EV/Gross Profit because they are often unprofitable, and revenue growth is key. Mature technology companies use EV/EBITDA and P/E because cash generation matters. Banks and financials use P/B, P/TBV, and P/E because leverage is integral to the model, and EV/EBITDA is not meaningful. REITs use P/FFO, P/AFFO, and P/NAV because real estate depreciation does not reflect actual value decline. Retail uses EV/EBITDA, P/E, and EV/EBITDAR for lease-heavy retailers.
Current sector EV/EBITDA benchmarks from January 2025 show Semiconductor at the highest multiple at 34.48xe. Software System and Application trades at 27.98x with a premium for recurring revenue. Healthcare Products shows 21.20x with stable demand. The Total Market benchmark sits at 18.60x. Oil and Gas Integrated trades at the lowest multiple at 6.70x.
The trading multiples method follows a systematic five-step process
Step 1 involves selecting the peer universe. Apply the eight criteria discussed earlier, documenting rationale for both inclusions and exclusions. Start broadly with 15-20 candidates, then narrow to 5-10 final peers.
Step 2 calculates enterprise value using the detailed formula. Enterprise Value equals Market Cap Diluted plus Total Debt, including short-term and long-term, plus Preferred Stock at liquidation value, plus Minority Interest, plus Unfunded Pension Obligations, plus Operating Lease Liability under ASC 842, minus Cash and Cash Equivalents, minus Excess Cash above operating needs.
For diluted shares, use the Treasury Stock Method for in-the-money options. Dilutive Shares equals Options multiplied by Share Price minus Strike Price, then divided by Share Price.
Step 3 spreads multiples in a comp table. The standard investment banking comp table format includes company name and ticker, market cap in millions, enterprise value in millions, revenue LTM and NTM, EBITDA LTM and NTM, EV/Revenue LTM and NTM, EV/EBITDA LTM and NTM, P/E LTM and NTM, revenue growth percentage, and EBITDA margin percentage. Include summary statistics showing minimum, 25th percentile, median, mean, 75th percentile, and maximum.
Step 4 addresses LTM versus NTM multiples. LTM means Last Twelve Months and uses actual historical data. The LTM Metric equals the Latest Fiscal Year plus the Current YTD minus the Prior YTD. This is best suited to stable, mature companies, but is backwards-looking. NTM stands for Next Twelve Months and refers to consensus analyst estimates. This is better suited to high-growth companies and reflects future expectations. Investment banks generally prefcalendarises&A pricing.
Step 5 calendarises financial data when companies have different fiscal year-ends. The Calendarized Metric equals Months in Calendar Year from Fiscal Year 1 divided by 12, multiplied by Fiscal Year 1 Data, plus Months in Calendar Year from Fiscal Year 2 divided by 12, multiplied by Fiscal Year 2 Data.
Mean vs median requires understanding statistical nuances
The median is the most meaningful metric because it naturally screens out outliers. Standard practice in investment banking uses the median when peer groups have 5 or more companies. The mean is preferable when peer groups have fewer than 5 comparable companies, and there are no clear outliers, or when the data are normally distributed.
Outliers distort the analysis significantly. Consider a peer group where Companies A through H have Price-to-Sales multiples ranging from 0.45x to 0.91x. Outlier Company I trades at 5.30x, and Outlier Company J trades at 10.40x. The median equals 0.61x. The mean equals 1.47x. The outliers raise the mean to 2.4 times the median, making it less representative of the central tendency.
Statistical tools for handling outliers include the trimmed mean, where you remove the top and bottom 10-25% before averaging. Interquartile range analysis identifies values outside 1.5x IQR as potential outliers and outside 3x IQR as extreme outliers. Market-cap weighted average gives larger, more liquid companies greater influence. Marking extreme values as NM excludes outliers from the statistics while noting them in the analysis.
Premium and discount justification requires specific factors.
Several factors justify a premium to peer multiples. Superior growth means higher revenue and earnings growth than peers. Higher margins reflect better gross, operating, or net margins. Market leadership indicates a number 1 or number 2 market position. Competitive moat includes brand strength, network effects, and switching costs. A stronger balance sheet means lower leverage and better liquidity. Recurring revenue from SaaS and subscription models commands 10-15x revenue multiples. Higher ROIC and ROE indicate returns that exceed the cost of capital. Better management shows a track record of value creation.
Factors justifying a discount include slower growth, lower margins, higher leverage, regulatory or legal concerns, smaller scale, customer concentration, geographic risk, poor governance, and execution concerns.
Quantifying premiums and discounts follows typical ranges. Control premium in M&A ranges 20-40% and can reach 50-70% in competitive deals. Minority discount ranges 15-30%. The discount for lack of marketability ranges from 20% to 50% for private shares. The small-cap premium adds 3-5% or more to the discount rate. Liquidity discounts range from 20% to 40% for private versus public shares.
Historical M&A data show that 83% of 2016 global deals had premiums between 10% and 50%. Microsoft's acquisition of LinkedIn in 2016 commanded a 49.5% premium. Intel's McAfee acquisition reached 62%.
Adjustments are needed to ensure an apples-to-apples comparison.
Enterprise value adjustments include several items. Underrecognised operating leases are recognised as an operating lease liability in the statement of cash flows, thereby increasing V. Unfunded pension obligations add the unfunded portion calculated as Projected Benefit Obligation minus Plan Assets to EV. Minority interest is added to EV at the market value if available. Convertible debt is treated as equity if in-the-money, otherwise as debt. Excess cash reduces EV, while operating cash of roughly 2-5% of revenue may remain.
EBITDA adjustments address several items. Restructuring charges are added back as non-recurring. Stock-based compensation is controversial and often reversed, but it still represents real dilution. Litigation settlements add back expenses and subtract gains. Asset impairments are added back as non-cash. Acquisition costs are added back as non-recurring.
The tax effect for pre-tax adjustments uses the formula After-Tax Impact equals Pre-Tax Add-back multiplied by 1 minus Marginal Tax Rate. For example, a $10M restructuring charge at a 25% tax rate results in a $7.5M net income add-back.
GAAP versus Non-GAAP considerations matter because 97% of S&P 500 companies report non-GAAP metrics. Best practice is to calculate adjustments independently rather than relying solely on management figures. Large gaps between GAAP and adjusted figures warrant investigation—a visualised football field chart illustrates multiple valuation methodologies.
A football-field chart is a floating bar chart that visualises investment banking data, enabling side-by-side comparison of multiple valuation methodologies. It gets its name from its resemblance to yard lines on a football field.
Standard components include a 52-week trading range showing the stock's high and low over the past year. Trading comps show the 25th-75th percentile of peer multiples. DCF analysis shows a range based on varying WACC and terminal growth. Precedent transactions show historical M&A deal multiples. Analyst price targets show consensus estimates. The current stock price appears as a vertical reference line. LBO analysis is optional and shows what financial sponsors could pay.
An example football-field chart shows different methodologies and their per-share valuation ranges. The 52-week trading range runs from $25.00 to $35.00. Trading comps using EV/EBITDA of 7.5x to 8.5x produce $27.50 to $31.00. DCF with a WACC of 7.8% to 8.8% produces $28.00 to $34.00. Precedent transactions produce $30.00 to $36.00. Analyst price targets show $29.00 to $33.00. The current stock price sits at $29.90.
Interpretation indicates convergence in the $29-33 range, with the current price at $29.90, suggesting a fair valuation with modest upside potential. Wide dispersion indicates higher uncertainty and warrants investigation of assumptions.
Real-world comps examples demonstrate practical application.n
In the Salesforce CRM space, peer selection includes ServiceNow, a direct competitor in enterprise workflow SaaS. Adobe represents a large-cap enterprise SaaS with a similar margin profile. Microsoft competes via Dynamics 365 and cloud services. Workday offers enterprise SaaS with a similar customer base.
Current 2025 multiples show Salesforce at approximately 22x forward P/E, 5.7x EV/Revenue, and 28.24x EV/EBITDA. ServiceNow trades at 32.8x forward P/E, 10.3x EV/Revenue, and approximately 50x EV/EBITDA. Adobe trades at approximately 24x forward P/E and approximately 12x EV/Revenue. Microsoft trades at approximately 29.7x forward P/E and approximately 13x EV/Revenue.
For JPMorgan Chase in banking, peer selection includes Bank of America, Wells Fargo, Citigroup, Goldman Sachs, and Morgan Stanley. Current multiples show JPMorgan at 16.1-16.3x trailing P/E, approximately 2.0x P/B, and 16.4% ROE. Goldman Sachs trades at 17.0-18.6x trailing P/E, approximately 1.5x P/B, and approximately 13% ROE. Bank of America trades at approximately 14x trailing P/E, approximately 1.2x P/B, and approximately 11% ROE. The peer average shows 15.6-16.5x trailing P/E, approximately 1.4x P/B, and approximately 12% ROE.
Analysis shows JPM trades at a P/B premium of 2.0x versus the tier average of 1.4x, supported by a superior ROE of 16.4% versus 12%. For banks, P/B is the key metric since EV/EBITDA is not meaningful for financial companies.
Common mistakes to avoid in comparable company analysis
Including too few peers below 5 or too many above 15 dilutes statistical reliability. Ignoring business model differences overlooks the fact that not all software companies are alike. Size mismatches occur when using mega-caps as peers for mid-caps and introduce distortion. Using stale data ignores the fact that peer sets should be refreshed on each valuation date. Not adjusting for non-recurring items means scrubbing financials is essential. Over-relying on a single metric ignores the need to triangulate across 3-4 metrics. Ignoring growth rate differences means a 25% grower should not peer with 5% growers. Cherry-picking peers is problematic because academic research confirms that banks strategically select high-multiple peers. Geographic mismatches arise when comparing U.S. companies to emerging-market peers and introduce tax and regulatory distortions. Using inappropriate multiples means applying P/E to unprofitable companies or EV/EBITDA to banks.
Tools and resources for comparable company analysis
Professional platforms include Bloomberg Terminal, priced at $24K–$32K per year, which offers real-time data, fixed-income coverage, and a chat network. S&P Capital IQ costs $10K–$30K per year for data scrubbing, Excel integration, and M&A data. FactSet starts from approximately $12K per year for portfolio management and pitchbook creation. Refinitiv Eikon costs $36K–$22 K per year and is a lower-cost Bloomberg alternative. PitchBook costs approximately $25K per year for private company data and VC/PE transactions.
Free and low-cost alternatives include Yahoo Finance, which offers 95 metrics and a screener, with a premium at $25-$35 per month. FINVIZ offers 60+ screening criteria and heat maps for free with Elite at $24.96 per month. Koyfin provides pro-grade analytics, 500+ metrics, and 10+ years of data, and offers a free trial. Focus offers guru portfolios, a DCF calculator, and 500+ U.S. stocks for $499 per year, with U.S. data. Morningstar provides fair value estimates and ratings with free basic and premium subscription options. SEC EDGAR offers 10-K filings, proxy statements, and peer disclosures for free. Damodaran at NYU Stern offers an industry-multiples database, updated annually, free of charge. Comparable company analysis remains the most practical valuation tool for investors, but its simplicity masks significant judgment calls that directly impact conclusions. Peer selection is an art, not just a science. GICS codes provide a starting point, but understanding business models, growth profiles, and margin structures separates professional analysis from mechanical comparison.
Use the median rather than the mean for peer groups with 5 or more companies to screen out outliers naturally—Mark extreme values as NM rather than letting them distort your analysis. Match the numerator to the denominator so equity multiples, such as P/E, use equity metrics, while enterprise value multiples, such as EV/EBITDA, use pre-debt metrics. Never mix them.
Current markets are elevated, with the S&P 500 forward P/E at 22.1x, compared with a 10-year average of 18.8x. A stock trading below the sector average may still be expensive historically. Document your rationale because the best analysts can defend both their inclusions and exclusions. Triangulate always because comps provide market-based reality checks, but combining with DCF and precedent transactions provides a valuation range that captures both intrinsic value and market sentiment.
Disclaimer: The views and recommendations made above are those of individual analysts or brokerage companies, and not of Winvesta. We advise investors to check with certified experts before making any investment decisions.
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Table of Contents
The single most important decision in valuation is not the formula you use. It is the companies you choose to compare. Comparable company analysis (comps) serves as the workhorse valuation method used by Wall Street analysts and investment bankers worldwide. Its apparent simplicity masks a technique that can swing valuations by 50% or more based solely on peer selection. For Indian investors analysing U.S. stocks, mastering comparable company (comps) analysis provides a powerful framework for determining whether your target investment trades at a premium, discount, or fair value relative to similar businesses.
This relative valuation method is a core tool of fundamental analysis for Indian investors building portfolios in the U.S. markets.
Selecting peer companies determines everything in comps analysis
Selecting comparable companies is the most critical step in the analysis. Wrong peer selection directly distorts the implied valuation. No amount of sophisticated multiple analysis can compensate for poorly chosen comparables.
The Global Industry Classification Standard (GICS) serves as the dominant system used by investment professionals. Developed by MSCI and S&P Dow Jones, GICS uses a four-tier hierarchy spanning 11 sectors, 25 industry groups, 74 industries, and 163 sub-industries. Companies receive an 8-digit code based on their principal business activity, primarily determined by revenues.
Critical GICS classifications surprise many investors. Amazon is classified as Consumer Discretionary under retail, not Technology. Tesla falls under Consumer Discretionary, not Technology or Energy. Netflix is classified in the Communication Services industry within the entertainment sector.
Eight criteria guide peer company selection. Industry and sector alignment should match the same or adjacent GICS sub-industry. Business model similarity requires overlap in core operational frameworks, monetisation, and customer types. The geographic mix should reflect similar exposure to developecapitalisation markets. Market capitalisation should fall within plus or minus 20-30% of the target. The revenue scale should match the same order of magnitude. The growth profile should align with similar 3-5-year revenue and earnings growth stages. Profitability margins should show comparable gross, EBITDA, and net margins. Capital structure should reflect similar debt-to-equity and leverage ratios.
The Tesla example perfectly illustrates peer selection challenges. If classified purely as an auto company, peers like GM and Ford trade at 3-7x P/E, but Tesla trades at 90-140x P/E. A blended peer approach, including traditional automakers, pure-play EV companies such as Rivian and Lucid, and autonomous technology firms, provides a clearer context.
The professional consensus centres on 5-10 companies as the optimal peer range, with 5-7 often cited as the sweet spot. Start with 15-20 potential peers in the initial screening, then narrow the list through detailed analysis. Too few peers below 5 create unreliable statistical significance, where a single unusual company can dramatically skew the results. Too many peers above 15 dilutes relevance as broader sets include fewer comparable companies.
SEC filings provide the richest source for finding peers. The 10-K Item 1 Business section describes products, markets, and competitive factors. Item 1A Risk Factors nearly always discusses competition and identifies competitor types. DEF 14A Proxy Statements disclose compensation peer groups used for executive pay benchmarking. These reveal who management considers comparable.
Key multiples to use vary by sector and business model
Understanding valuation multiples requires grasping the fundamental distinction between equity multiples and enterprise value multiples. Equity multiples like P/E, P/B, and P/S measure value to shareholders only, using marketcapitalisationn in the numerator and after-debt metrics in the denominator. They are affected by differences in capital structure.
Enterprise value multiples such as EV/EBITDA, EV/EBIT, and EV/Revenue measure total firm value, including both debt and equity. They are capital-structure-neutral, making them preferred for comparing companies with different levels of leverage.
P/E Ratio equals Stock Price divided by Earnings Per Share, or Market Cap divided by Net Income.
For a deeper dive into understanding the P/E ratio to value stocks, this metric works best when comparing companies within the same industry.
The current S&P 500 forward P/E stands at 22.1x versus a 10-year average of 18.8x, indicating elevated valuations.
EV/EBITDA equals Enterprise Value divided by EBITDA. This is the most widely used multiple across industries because it is capital-structure- and tax-neutral, and less affected by accounting policy differences. Current S&P 500 sector EV/EBITDA ranges from 8.56x for Energy to 27.49x for Information Technology.
EV/Revenue equals Enterprise Value divided by Total Revenue. This works best for early-stage or high-growth companies with negative EBITDA, SaaS businesses, and cross-company comparisons when profitability differs significantly.
P/B Ratio equals Market Cap divided by Shareholders' Equity. This is essential for banks and financial institutions whose business models depend on leverage. Current money centre bank P/B averages 1.32x while regional banks average 1.13x.
Different sectors require different multiples. Technology high-growth companies use EV/Revenue and EV/Gross Profit because they are often unprofitable, and revenue growth is key. Mature technology companies use EV/EBITDA and P/E because cash generation matters. Banks and financials use P/B, P/TBV, and P/E because leverage is integral to the model, and EV/EBITDA is not meaningful. REITs use P/FFO, P/AFFO, and P/NAV because real estate depreciation does not reflect actual value decline. Retail uses EV/EBITDA, P/E, and EV/EBITDAR for lease-heavy retailers.
Current sector EV/EBITDA benchmarks from January 2025 show Semiconductor at the highest multiple at 34.48xe. Software System and Application trades at 27.98x with a premium for recurring revenue. Healthcare Products shows 21.20x with stable demand. The Total Market benchmark sits at 18.60x. Oil and Gas Integrated trades at the lowest multiple at 6.70x.
The trading multiples method follows a systematic five-step process
Step 1 involves selecting the peer universe. Apply the eight criteria discussed earlier, documenting rationale for both inclusions and exclusions. Start broadly with 15-20 candidates, then narrow to 5-10 final peers.
Step 2 calculates enterprise value using the detailed formula. Enterprise Value equals Market Cap Diluted plus Total Debt, including short-term and long-term, plus Preferred Stock at liquidation value, plus Minority Interest, plus Unfunded Pension Obligations, plus Operating Lease Liability under ASC 842, minus Cash and Cash Equivalents, minus Excess Cash above operating needs.
For diluted shares, use the Treasury Stock Method for in-the-money options. Dilutive Shares equals Options multiplied by Share Price minus Strike Price, then divided by Share Price.
Step 3 spreads multiples in a comp table. The standard investment banking comp table format includes company name and ticker, market cap in millions, enterprise value in millions, revenue LTM and NTM, EBITDA LTM and NTM, EV/Revenue LTM and NTM, EV/EBITDA LTM and NTM, P/E LTM and NTM, revenue growth percentage, and EBITDA margin percentage. Include summary statistics showing minimum, 25th percentile, median, mean, 75th percentile, and maximum.
Step 4 addresses LTM versus NTM multiples. LTM means Last Twelve Months and uses actual historical data. The LTM Metric equals the Latest Fiscal Year plus the Current YTD minus the Prior YTD. This is best suited to stable, mature companies, but is backwards-looking. NTM stands for Next Twelve Months and refers to consensus analyst estimates. This is better suited to high-growth companies and reflects future expectations. Investment banks generally prefcalendarises&A pricing.
Step 5 calendarises financial data when companies have different fiscal year-ends. The Calendarized Metric equals Months in Calendar Year from Fiscal Year 1 divided by 12, multiplied by Fiscal Year 1 Data, plus Months in Calendar Year from Fiscal Year 2 divided by 12, multiplied by Fiscal Year 2 Data.
Mean vs median requires understanding statistical nuances
The median is the most meaningful metric because it naturally screens out outliers. Standard practice in investment banking uses the median when peer groups have 5 or more companies. The mean is preferable when peer groups have fewer than 5 comparable companies, and there are no clear outliers, or when the data are normally distributed.
Outliers distort the analysis significantly. Consider a peer group where Companies A through H have Price-to-Sales multiples ranging from 0.45x to 0.91x. Outlier Company I trades at 5.30x, and Outlier Company J trades at 10.40x. The median equals 0.61x. The mean equals 1.47x. The outliers raise the mean to 2.4 times the median, making it less representative of the central tendency.
Statistical tools for handling outliers include the trimmed mean, where you remove the top and bottom 10-25% before averaging. Interquartile range analysis identifies values outside 1.5x IQR as potential outliers and outside 3x IQR as extreme outliers. Market-cap weighted average gives larger, more liquid companies greater influence. Marking extreme values as NM excludes outliers from the statistics while noting them in the analysis.
Premium and discount justification requires specific factors.
Several factors justify a premium to peer multiples. Superior growth means higher revenue and earnings growth than peers. Higher margins reflect better gross, operating, or net margins. Market leadership indicates a number 1 or number 2 market position. Competitive moat includes brand strength, network effects, and switching costs. A stronger balance sheet means lower leverage and better liquidity. Recurring revenue from SaaS and subscription models commands 10-15x revenue multiples. Higher ROIC and ROE indicate returns that exceed the cost of capital. Better management shows a track record of value creation.
Factors justifying a discount include slower growth, lower margins, higher leverage, regulatory or legal concerns, smaller scale, customer concentration, geographic risk, poor governance, and execution concerns.
Quantifying premiums and discounts follows typical ranges. Control premium in M&A ranges 20-40% and can reach 50-70% in competitive deals. Minority discount ranges 15-30%. The discount for lack of marketability ranges from 20% to 50% for private shares. The small-cap premium adds 3-5% or more to the discount rate. Liquidity discounts range from 20% to 40% for private versus public shares.
Historical M&A data show that 83% of 2016 global deals had premiums between 10% and 50%. Microsoft's acquisition of LinkedIn in 2016 commanded a 49.5% premium. Intel's McAfee acquisition reached 62%.
Adjustments are needed to ensure an apples-to-apples comparison.
Enterprise value adjustments include several items. Underrecognised operating leases are recognised as an operating lease liability in the statement of cash flows, thereby increasing V. Unfunded pension obligations add the unfunded portion calculated as Projected Benefit Obligation minus Plan Assets to EV. Minority interest is added to EV at the market value if available. Convertible debt is treated as equity if in-the-money, otherwise as debt. Excess cash reduces EV, while operating cash of roughly 2-5% of revenue may remain.
EBITDA adjustments address several items. Restructuring charges are added back as non-recurring. Stock-based compensation is controversial and often reversed, but it still represents real dilution. Litigation settlements add back expenses and subtract gains. Asset impairments are added back as non-cash. Acquisition costs are added back as non-recurring.
The tax effect for pre-tax adjustments uses the formula After-Tax Impact equals Pre-Tax Add-back multiplied by 1 minus Marginal Tax Rate. For example, a $10M restructuring charge at a 25% tax rate results in a $7.5M net income add-back.
GAAP versus Non-GAAP considerations matter because 97% of S&P 500 companies report non-GAAP metrics. Best practice is to calculate adjustments independently rather than relying solely on management figures. Large gaps between GAAP and adjusted figures warrant investigation—a visualised football field chart illustrates multiple valuation methodologies.
A football-field chart is a floating bar chart that visualises investment banking data, enabling side-by-side comparison of multiple valuation methodologies. It gets its name from its resemblance to yard lines on a football field.
Standard components include a 52-week trading range showing the stock's high and low over the past year. Trading comps show the 25th-75th percentile of peer multiples. DCF analysis shows a range based on varying WACC and terminal growth. Precedent transactions show historical M&A deal multiples. Analyst price targets show consensus estimates. The current stock price appears as a vertical reference line. LBO analysis is optional and shows what financial sponsors could pay.
An example football-field chart shows different methodologies and their per-share valuation ranges. The 52-week trading range runs from $25.00 to $35.00. Trading comps using EV/EBITDA of 7.5x to 8.5x produce $27.50 to $31.00. DCF with a WACC of 7.8% to 8.8% produces $28.00 to $34.00. Precedent transactions produce $30.00 to $36.00. Analyst price targets show $29.00 to $33.00. The current stock price sits at $29.90.
Interpretation indicates convergence in the $29-33 range, with the current price at $29.90, suggesting a fair valuation with modest upside potential. Wide dispersion indicates higher uncertainty and warrants investigation of assumptions.
Real-world comps examples demonstrate practical application.n
In the Salesforce CRM space, peer selection includes ServiceNow, a direct competitor in enterprise workflow SaaS. Adobe represents a large-cap enterprise SaaS with a similar margin profile. Microsoft competes via Dynamics 365 and cloud services. Workday offers enterprise SaaS with a similar customer base.
Current 2025 multiples show Salesforce at approximately 22x forward P/E, 5.7x EV/Revenue, and 28.24x EV/EBITDA. ServiceNow trades at 32.8x forward P/E, 10.3x EV/Revenue, and approximately 50x EV/EBITDA. Adobe trades at approximately 24x forward P/E and approximately 12x EV/Revenue. Microsoft trades at approximately 29.7x forward P/E and approximately 13x EV/Revenue.
For JPMorgan Chase in banking, peer selection includes Bank of America, Wells Fargo, Citigroup, Goldman Sachs, and Morgan Stanley. Current multiples show JPMorgan at 16.1-16.3x trailing P/E, approximately 2.0x P/B, and 16.4% ROE. Goldman Sachs trades at 17.0-18.6x trailing P/E, approximately 1.5x P/B, and approximately 13% ROE. Bank of America trades at approximately 14x trailing P/E, approximately 1.2x P/B, and approximately 11% ROE. The peer average shows 15.6-16.5x trailing P/E, approximately 1.4x P/B, and approximately 12% ROE.
Analysis shows JPM trades at a P/B premium of 2.0x versus the tier average of 1.4x, supported by a superior ROE of 16.4% versus 12%. For banks, P/B is the key metric since EV/EBITDA is not meaningful for financial companies.
Common mistakes to avoid in comparable company analysis
Including too few peers below 5 or too many above 15 dilutes statistical reliability. Ignoring business model differences overlooks the fact that not all software companies are alike. Size mismatches occur when using mega-caps as peers for mid-caps and introduce distortion. Using stale data ignores the fact that peer sets should be refreshed on each valuation date. Not adjusting for non-recurring items means scrubbing financials is essential. Over-relying on a single metric ignores the need to triangulate across 3-4 metrics. Ignoring growth rate differences means a 25% grower should not peer with 5% growers. Cherry-picking peers is problematic because academic research confirms that banks strategically select high-multiple peers. Geographic mismatches arise when comparing U.S. companies to emerging-market peers and introduce tax and regulatory distortions. Using inappropriate multiples means applying P/E to unprofitable companies or EV/EBITDA to banks.
Tools and resources for comparable company analysis
Professional platforms include Bloomberg Terminal, priced at $24K–$32K per year, which offers real-time data, fixed-income coverage, and a chat network. S&P Capital IQ costs $10K–$30K per year for data scrubbing, Excel integration, and M&A data. FactSet starts from approximately $12K per year for portfolio management and pitchbook creation. Refinitiv Eikon costs $36K–$22 K per year and is a lower-cost Bloomberg alternative. PitchBook costs approximately $25K per year for private company data and VC/PE transactions.
Free and low-cost alternatives include Yahoo Finance, which offers 95 metrics and a screener, with a premium at $25-$35 per month. FINVIZ offers 60+ screening criteria and heat maps for free with Elite at $24.96 per month. Koyfin provides pro-grade analytics, 500+ metrics, and 10+ years of data, and offers a free trial. Focus offers guru portfolios, a DCF calculator, and 500+ U.S. stocks for $499 per year, with U.S. data. Morningstar provides fair value estimates and ratings with free basic and premium subscription options. SEC EDGAR offers 10-K filings, proxy statements, and peer disclosures for free. Damodaran at NYU Stern offers an industry-multiples database, updated annually, free of charge. Comparable company analysis remains the most practical valuation tool for investors, but its simplicity masks significant judgment calls that directly impact conclusions. Peer selection is an art, not just a science. GICS codes provide a starting point, but understanding business models, growth profiles, and margin structures separates professional analysis from mechanical comparison.
Use the median rather than the mean for peer groups with 5 or more companies to screen out outliers naturally—Mark extreme values as NM rather than letting them distort your analysis. Match the numerator to the denominator so equity multiples, such as P/E, use equity metrics, while enterprise value multiples, such as EV/EBITDA, use pre-debt metrics. Never mix them.
Current markets are elevated, with the S&P 500 forward P/E at 22.1x, compared with a 10-year average of 18.8x. A stock trading below the sector average may still be expensive historically. Document your rationale because the best analysts can defend both their inclusions and exclusions. Triangulate always because comps provide market-based reality checks, but combining with DCF and precedent transactions provides a valuation range that captures both intrinsic value and market sentiment.
Disclaimer: The views and recommendations made above are those of individual analysts or brokerage companies, and not of Winvesta. We advise investors to check with certified experts before making any investment decisions.
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