Common Mistakes in Multiple Comparisons — "Same Numbers, Different Values"

Executive Summary

Comparable Company Analysis (hereinafter "Comps") is the most frequently used relative valuation methodology in investment banking, private equity, and venture capital. It is based on the intuitive logic that "similar companies should receive similar valuations" and, alongside DCF, forms the axis of cross-validation in practice. However, this very intuitiveness can also become a trap. As of 2025, the average EV/EBITDA multiple for the IT sector among U.S. S&P 500 companiesis 27.25x, while the Energy sectorstands at 7.47x—a difference of over 3.6 times. Completely different valuation approaches are being applied under the same name of "multiples." Failure to understand this difference can lead to valuation errors amounting to hundreds of billions of won.¹

This content analyzes the structural limitations of the Comps methodology and seven major recurring mistakes observed in investment organizations (investment teams, Corp Dev, etc.) based on practical experience, and presents a practical framework to correct them.

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1. Structure of Comparable Analysis: Why We Rely on Multiples

1.1) Basic Structure of the Methodology

The core process of Comps consists of five steps²

1. Peer Group Selection: Select 5 to 10 listed companies with similar industry, size, growth potential, and profitability.
2. Financial Data Collection: Securing key metrics such as Enterprise Value, Revenue, EBITDA, and Net Profit
3. Multiple Calculation: Key multiples such as EV/Revenue, EV/EBITDA, PER, etc.
4. Distribution Analysis: Derive Median and Interquartile Range (IQR), Identify Causes of Premium/Discount
5. Target company application: Estimate enterprise value by multiplying the appropriate multiple by the target company's financial metrics.

Enterprise Value Calculation
$$EV=\text{Market capitalization}+\text{net borrowing}+\text{Minority Shareholder Interest}+\text{Preferred stock}-\text{Non-operating assets}$$

1.2) Types of Multiples and Their Appropriate Situations

Multiple	Mountain formula	Suitable Industries	Precautions
EV/Revenue	Enterprise Value ÷ Revenue	Pre-profit SaaS, Bio	Risk of ignoring profitability
EV/EBITDA	Enterprise Value ÷ EBITDA	Manufacturing, distribution, and services	CapEx difference not reflected
PER	Stock Price ÷ EPS	Stable Income Company	Ignoring differences in capital structure
EV/EBIT	Enterprise Value ÷ EBIT	Capital-intensive industries	Impact of Depreciation Policy
P/AFFO	Stock Price ÷ AFFO	REITs, Real Estate	Industry-Specific Metrics

EV/EBITDA is the most commonly used metric in M&A practice because it has the advantage of appropriately reflecting differences in capital structure basedon operating cash generation.

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2. Industry-Specific Multiple Benchmarks: As of 2025

2.1) Trend of EV/EBITDA by Sector for the U.S. S&P 500

Sector	2025	2024	2023	2022	2021	2020
IT	27.25x	27.55x	28.19x	24.40x	23.95x	15.96x
Real Estate	21.27x	19.68x	18.78x	20.15x	18.32x	16.61x
Healthcare	16.79x	20.05x	22.21x	17.63x	16.54x	16.24x
Consumer Goods (Discretionary)	17.41x	19.06x	16.47x	17.03x	18.09x	14.44x
Consumer Goods (Essential)	17.33x	16.81x	15.98x	15.14x	17.67x	16.42x
Industrial goods	16.70x	15.48x	16.46x	15.34x	14.11x	15.06x
Material	14.03x	13.53x	13.95x	12.52x	11.30x	9.14x
Utility	13.05x	13.04x	12.73x	12.42x	13.13x	13.75x
Energy	7.47x	7.19x	7.13x	5.73x	4.49x	5.37x

Source: Siblis Research, based on the S&P 500 (December 2025)³

2.2) Multiple Differences by Buyer Type Based on M&A Deal Criteria

In the 2025 global M&A market,the IT and healthcare sectorsrecorded the highest median EV/EBITDA multiplesat 12.5x and 12.8x, respectively. Financial services stood at 10.3x, while the B2B and B2C sectors ranged from 8.1x to 8.4x.⁴

Industry	When buying PE	Strategic Purchase (Corp)	Difference
IT/Software	11.2x	14.1x	+2.9x
Healthcare	11.5x	13.8x	+2.3x
Manufacturing	6.8x	7.5x	+0.7x
Distribution	5.2x	5.8x	+0.6x

Strategic buyers (corporate) pay multiples that are on average1.5 to 3.0 timeshigher than PE ratios, reflecting synergy premiums. Ignoring this difference and mixing transaction cases leads to significant valuation distortions.

2.3) Unique Characteristics of the Korean Market

In the domestic unlisted M&A market, the following EV/EBITDA multiples are conventionally applied by industry.

Industry	Multiple Range (Draft)	Note
B2B SaaS	8–12x	Varies depending on the proportion of recurring revenue
Manufacturing	4 to 7x	Separate reflection of equipment asset value is required.
Retail industry	3 to 5 times	Impact of Margin Rate and Inventory Turnover Rate
Content/Media	6–10x	IP value, subscriber base
Bio/Healthcare	Revenue Multiple Applied During Loss Period	Differential Pipeline Stages

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3. Seven Pitfalls of Multiple Comparisons

Pitfall ① Ignoring Industry Characteristics — "The mistake of applying SaaS multiples to manufacturing"

As of 2025, the median EBITDA multiple for unlisted SaaS companiesstands at 22.4x, while listed software companies averagearound 12.7x. Applying these figures to companies with project-based revenue rather than subscription models results in an overvaluation of their enterprise valueby 2 to 3 times.

[Example]Applying the same 10x revenue multiple to domestic B2B SaaS company A (ARR 8 billion KRW, NRR 120%) and SI company B (revenue 8 billion KRW, project-based) results in a valuation of 80 billion KRW for both. However, Company A's recurring revenue structure and Company B's one-off project structure inherently carry different risk profiles.

Pitfall ② Failure to Adjust One-Time Items — "Hidden EBITDA Distortion"

Failure to calculate Adjusted EBITDA distorts the denominator of the multiple. Key adjustment items are as follows:⁵

Adjustment items	Direction	Example
Litigation costs (one-time)	(+) Gasan	Electricity Generation Trademark Litigation Costs
Excessive Owner Compensation	(+) Gasan	Salary and expenses exceeding market levels
Stock-based compensation expense (SBC)	(+/-) Requires judgment	Non-cash expenses or dilution effects exist
Non-recurring income	(-) Deduction	Gain on asset disposal, insurance proceeds received
Restructuring costs	(+) Gasan	One-time costs related to business unit consolidation

Key Principle: Consistency in adjustments is crucial. If SBC is added for one company but ignored for another comparable company, the comparison of multiples itself becomes meaningless. (Comparability is lost.)

Pitfall ③ Ignoring Debt Levels — "Confusing Enterprise Value with Equity Value"

This is the most frequent yet critical error in practice. The figure derived from the EV/EBITDA multiplerepresents Enterprise Value, not shareholder value.

EV → Equity Value Bridge
$$\text{Equity Value}=EV-\text{Net Debt}-\text{Debt-like Items}\pm \text{NWC Adjustment}$$

[Real-World Case]

Item	Amount
EBITDA	15 billion won
Applicable Multiple	8.0x
Enterprise Value	120 billion won
(-) Borrowings	(22 billion won)
(+) Free cash	4 billion won
(-) Net Debt	(18 billion won)
(-) Debt-like Items*	(25 billion won)
(±) NWC Settlement	+600 million won
Equity Value	100.1 billion won

*Debt-like Items: Accrued corporate income tax, accrued retirement benefits liability, accrued product warranty liability, etc.⁶

Failing to account forKRW 18 billion in net borrowings and KRW 2.5 billion in debt-like itemsduring the transition from EV to Equity Value results in anapproximately 17%overvaluation of shareholder value. In mid-sized company M&A, this discrepancy often amounts to tens of billions to hundreds of billions of won.

Pitfall ④ Ignoring Growth Rate Differences — "Same Multiple, Different Future"

It is unreasonable for a company with 30% revenue growth to receive the same EV/EBITDA multiple of 8x as one with 5% growth. Yet applying a simple peer group average leads to this error.

Growth Rate-Multiple Relationship Simulation (Example: B2B SaaS Service Company)

Sales growth rate	Appropriate EV/EBITDA Range	Basis
30%+ (High Growth)	15–25x	Companies Meeting the SaaS Rule of 40
15–30% (growth)	10–15x	Scale-up stage companies
5–15% (Stable Growth)	7–10x	Industry average level
0–5% (low growth)	4 to 7x	Mature industry
Negative growth	3 to 5 times	Target for restructuring or turnaround

Pitfall ⑤ LTM vs NTM Mixing — "Past or Future?"

LTM (Last Twelve Months) is based on past performance, while NTM (Next Twelve Months) is based on estimates for the next 12 months.
High-growth companies see a significant drop in their NTM multiple compared to LTM, so the same criteria must be applied to both comparable companies and the target company.⁷

[Example]For a company with a 40% sales growth rate,

• LTM EV/Revenue: 15x
• NTM EV/Revenue: 10.7x (= 15x ÷ 1.4)

Mixing LTM and NTM results inapproximately a 40% valuation error. This mixing, whether intentional or unintentional, is actually found quite frequently during the investment review process.

Pitfall ⑥ Subjectivity in Peer Group Composition — "Comparative Groups Tailored to Desired Conclusions"

⁸​

Criteria for Selecting a Disciplined Peer Group

Standard	Primary filter	Second adjustment
Industry	Same industry classification (based on GICS)	Verification of Business Model Similarity
Scale	Within ±50% of sales and assets	Companies with similar market capitalization
Region	same economic zone	Adjustment for exchange rates and tax rates in global comparisons
growth rate	±10 percentage points	Growth Stage (Early/Mature) Alignment
Profitability	EBITDA Margin ±5 percentage points range	Operating Leverage Comparable Companies

[Experience/Example] The common criteria applied by the internal investment teams at Company O and Company S were:
Composed of a minimum of 5 and a maximum of 10 companies, applying the median and interquartile range (IQR)after removing outliers.⁹

Trap ⑦ Mismatch in Timing of Sequential Deposits — "Whose Balance Sheet Is This?"

When calculating net debt by mechanically using the most recent balance sheet figures, errors occur due to seasonality or temporary cash fluctuations. For example, a retailer's borrowing at the time of year-end inventory expansion or cash holdings immediately before a quarterly dividend do not represent normal levels.¹⁰​

• Correction Method
  • Apply the average net borrowings over 3 to 4 quarters
  • Reflecting Seasonal Adjustment
  • Separation of non-operating cash (e.g., regulatory deposits)

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4. Multiples for Loss-Making Companies: Approach for Biotech and Early-Stage Startups

4.1) Application of Sales-Based Multiples

EV/EBITDA cannot be directly applied to loss-making companies with negative EBITDA. In such cases, theEV/Revenuemultiple is used, or aforward multipleis derived for the point in the next 3 to 5 years when EBITDA is expected to turn positive, and then discounted to present value.¹¹​

Example of S Company Investment Team Internal Review Criteria: Considering the Unique Valuation Characteristics of the Bio Sector¹²

Bio Sub-Sector	Revenue Multiple Range	Core Value Drivers
Biopharmaceuticals/Cell and Gene Therapy	8–20x+	Pipeline stage, FDA approval
Diagnostic/Medical Devices	4–8x	Insurance Benefits, Competitive Intensity
Synthetic Biology	6–15x	Scalability, platform technology
Biological Tools/Equipment	5 to 10 times	Recurring revenue (consumables), predictability

As of Q4 2024, the median EV/Revenue multiple for the biotech and genomics sectorstands at 6.2x, fluctuating within a range of 5.5x to 7.0x.

4.2) Forward Multiple + Discount Approach

[Case Study During S Company's Investment Review: Biotech Firm C]

Item	Present (Y0)	Y3 estimate
Sales	5 billion won	30 billion won
EBITDA	(3 billion won)	4.5 billion won
Applicable Multiple	N/A	12.0x (Peer median)
Future EV	–	54 billion won
Discount rate	–	15% (Biotech WACC)
Current EV	–	35.5 billion won (PV =(1.15)³⁵⁴⁰ = 1.5215⁴⁰ = 35.5 billion won)

This approach is effective for companies currently operating at a loss but possessinga clear path to profitability, and the discount rate must sufficiently reflect technology and regulatory risk premiums.

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5. EV to Equity Bridge: Precision Adjustment Case Study

5.1) Overall Structure of the Bridge

The transition from Enterprise Value to Equity Value is not a simple subtraction but the core mechanism for value settlement at deal closing.¹³

[Case Study During S Company's Investment Review: Biotech Firm C]

Category	Item	Adjustment Direction
Enterprise Value	Comps/DCF Calculation Results	Reference value
(-) Interest-bearing borrowings	Bank loans, private loans, lease liabilities	deduction
(+) Free cash	Cash and short-term financial instruments unrelated to operations	Gasan
(-) Debt-like Items	Accrued taxes, retirement benefits, litigation reserves	deduction
(-) Minority interest	External equity in affiliated companies	deduction
(-) Preferred stock	Residual Preferred Shareholder Claim	deduction
(±) Working Capital Settlement	Actual NWC vs Peg NWC Difference	Addition and subtraction
Equity Value	Value attributable to shareholders	Final value

5.2) NWC Peg and Collar Mechanism

In M&A contracts, an NWC Peg (based on normal working capital) is established, and the difference between this and the actual NWC at closing is settled.

• [Example]
  • NWC Peg: 10.5 billion won
  • Actual India NWC: 11.1 billion won
  • Collar (Allowable Range): ±300 million won
  • Settlement Amount: +300 million won (111 – 105 = 600 million won, but only 300 million won within the Collar is recognized)

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6. Scenario Validation: Applying the 3P Framework

The investment teams at Company O and Company S also validate the core assumptions of their multiple analysis methodology usinga Possibility,Plausibility, andProbabilityframework.

6.1) Home Verification Matrix (Draft)

Situational Hypothetical Assumptions	Possibility	Plausibility	Probability	Verification results
IT sector EV/EBITDA 25x+ sustained	✅ Possible	🔶 Conditional	🔶 Midpoint	Downside risk in the event of slowing AI growth
Energy sector maintains 7-8x	✅ Possible	✅ Valid	✅ High	Structurally low-multiple sector
PE vs. Corp Purchase Price Gap of 2-3x	✅ Possible	✅ Valid	✅ High	Synergy Premium Historical Consistency
Unlisted SaaS at 22x EBITDA	✅ Possible	🔶 Conditional	🔶 Midpoint	Assuming ARR $10M+ & NRR 110%+
Forward Multiple Bio Application	✅ Possible	✅ Valid	🔶 Midpoint	Uncertainty regarding the timing of monetization persists

6.2) Cross-Check: Comparing Two Scenarios

[Case Study During Company O's Investment Review: Asian SaaS Company D]

Item	Bull Case	Base Case	Bear Case
ARR	12 billion won	12 billion won	12 billion won
Applied Revenue Multiple	12.0x	8.0x	5.0x
Enterprise Value	144 billion won	96 billion won	60 billion won
(-) Net Debt	(5 billion won)	(5 billion won)	(5 billion won)
Equity Value	139 billion won	91 billion won	55 billion won
Basis	NRR 130%, Rule of 40 satisfied	Median Application by Industry	Slowing growth, rising churn rate

[Opinion on the above case]
The fact that the equity value gapbetween the Bull Case and Bear Case reaches 84 billion won (2.5 times)demonstrates how decisive the choice of multiples can be.
This is the fundamental limitation of comps and why they must be cross-validated with DCF.

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7. Checklist Based on Experience: 10 Considerations Based on Comparable Analysis

#	Principle	Details
1	Peer Group consists of a minimum of 5 and a maximum of 10 members.	After removing outliers, use the median and IQR.
2	Unify LTM/NTM standards	Apply the same criteria to both the comparable company and the target company.
3	Consistently calculate Adjusted EBITDA	SBC, Specifying Criteria for One-Time Item Processing
4	Never confuse EV with Equity Value.	Net Debt Bridge execution/analysis required
5	Applying premium/discount reflecting growth rate differences	Consideration of prohibiting the application of simple averages
6	Distinguishing PE Deals from Strategic M&A Deals	Synergy premium perceived as 2-3x difference
7	Seasonal and Timing Effect Adjustment	Average Net Debt for Q3-Q4
8	Loss-making companies use the Revenue Multiple or Forward Multiple	Apply alternatives when current EBITDA is negative
9	Distinguishing Precedent Transactions and Trading Comparables	Reflecting the Control Premium
10	Must perform DCF and cross-validation	The overlapping range between the multiple calculation range and the DCF results constitutes the reasonable range.

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8. The Proper Position of Comparables: Their Role Within the Valuation Framework

The multiple is not a self-contained valuation methodology. It serves as a reference point for "how the market values comparable companies." According to Morgan Stanley IM research, the EV/EBITDA multiple varies based on profitability levels and is also influenced by the introduction of debt (tax shield) and changes in tax rates.¹⁴​

Therefore, in practice, valuation should be conducted using the followingtriangulation structure.

[Case Study During Company O's Investment Review: Asian SaaS Company D]

Methodology	Role	Weight (Example)
DCF	Intrinsic Value Calculation	40–50%
Trading Comparisons	Market Value	25–30%
Precedent Transactions	Transaction Value	20–30%

The investment teams at Company O and Company S consider the Overlap Zone—wherethe results of the three methodologies converge—to be the reasonable valuation range. Within this range, they determine the initial offer price and final price by considering the negotiation position, strategic value, and market environment, continuously updating these figures until the negotiation is concluded.

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Closing Remarks

Comparables are appealing. They are intuitive, fast, and provide market-validated figures. Yet behind this convenience lies a fundamental risk: the illusion of comparability. Even within the same industry, business models differ; even with the same multiples, growth rates vary; and even with the same Enterprise Value, the value attributable to shareholders can be entirely different.

The gap between the IT sector's EV/EBITDA of 27.25x and the energy sector's 7.47x as of 2025 reflects not merely a numerical difference, butthe market's varying confidence in each industry's future cash flows.¹⁵
I suggest asking yourself this question whenever you use multiples.

To borrow Professor Aswath Damodaran's expression, multiples belong to the realm of "Myth, Mania, and Alchemy." The only way to avoid becoming an alchemist is to transparently reveal the assumptions behind the numbers, cross-validate them using multiple methodologies, and humbly acknowledge uncertainty.¹⁶

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Endnotes

1. https://ibinterviewquestions.com/blog/how-to-build-comparable-company-analysis
   https://siblisresearch.com/data/ev-ebitda-multiple/ ↩︎
2. https://www.datastudios.org/post/comparable-company-analysis-approach-adjustments-and-interpretation
   https://ibinterviewquestions.com/blog/how-to-build-comparable-company-analysis ↩︎
3. https://siblisresearch.com/data/ev-ebitda-multiple/ ↩︎
4. https://clfi.co.uk/insights/ma-ev-ebitda-multiples-2025-pe-vs-corporate/ ↩︎
5. https://fastercapital.com/topics/pitfalls-to-avoid-when-using-ebitda-ev-multiples-for-valuation.html ↩︎
6. https://auxocapitaladvisors.com/working-capital-peg-ev-to-equity-bridge/ ↩︎
7. https://ibinterviewquestions.com/blog/how-to-build-comparable-company-analysis ↩︎
8. https://www.datastudios.org/post/comparable-company-analysis-approach-adjustments-and-interpretation ↩︎
9. https://www.financial-modeling.com/comparable-company-analysis/
   https://ibinterviewquestions.com/blog/how-to-build-comparable-company-analysis ↩︎
10. https://www.footnotesanalyst.com/net-debt-in-enterprise-value-seasonality-and-fair-values/ ↩︎
11. https://platum.kr/archives/263534 ↩︎
12. https://www.finrofca.com/news/biotech-revenue-multiples-2025 ↩︎
13. https://auxocapitaladvisors.com/working-capital-peg-ev-to-equity-bridge/ ↩︎
14. https://www.morganstanley.com/im/publication/insights/articles/article_valuationmultiples.pdf ↩︎
15. https://siblisresearch.com/data/ev-ebitda-multiple/ ↩︎
16. https://www.ssrn.com/abstract=3680133 ↩︎