Making the Case for the Size Effect

In recent years, some well-regarded academics have argued that the size effect for small companies has disappeared — and that valuators, therefore, shouldn’t include a size premium when valuing a small business. If you’ll be testifying in a case where the opposing expert makes this argument, Carla Nunes, CFA, ABV[1], says you’ll need to be prepared to address it with rigorous, empirically grounded analysis.

According to Nunes, a rigorous analysis of the relevant data makes clear that the size premium remains appropriate. She and colleague James Harrington, a Director at Kroll, recently shared emerging research that demonstrates the continued existence of the size effect in a NACVA webinar. While the effect waxes and wanes over time, it does persist.

Read on to learn some of the webinar highlights that you can wield when an opposing expert disputes the use of a size premium.

The Debate in a Nutshell

The size effect is supported by numerous empirical studies showing that smaller companies tend to generate higher returns, reflecting their greater risk. As a result, smaller companies typically have a higher cost of capital than large companies. Therefore, proponents say, a size premium must be added when calculating the cost of equity for a small company under the capital asset pricing model (CAPM) or build-up method.

Critics in the academic arena increasingly say that the size effect, which was initially identified in the early 1980s, has vanished. As evidence, they often point to the relative underperformance of U.S. small cap stocks since either the 1980s or the 2008 Great Financial Crisis. One prominent critic advises valuators to account for small firm risk by adjusting expected cash flow, rather than the discount rate.

[1] Carla Nunes is a former Managing Director and head of the Cost of Capital Team at Kroll. For any future cost of capital inquiries, please contact costofcapital.support@kroll.com.

The Reality on the Ground

Nunes pointed out that many of the academic papers that reject or question the size effect do so in the context of multi-factor models, which include other potential risk factors besides size. The greater the number of factors, the smaller the effect of each will be — and academics theorize that the relatively small contribution of the size effect in this context means it has evaporated. But, Nunes said, very few practitioners use a multi-factor model when estimating a company’s cost of equity.

Rather, valuators generally employ either the traditional textbook CAPM or a build-up method − essentially a CAPM variant in which systematic risk is captured through an additive “industry risk premium” rather than a beta.

To illustrate, here’s an example of using the build-up method to calculate the cost of equity for a restaurant (GICS 25301040) in the United States, with a valuation date of Dec. 31, 2022, with (based on a company with a market value of common equity less than $200M) and without a size premium.

Build-up WITHOUT the size premium

Cost of equity =	Risk-free rate	+ ERP	+ IRP	+ Company-specific risk premium	+ Size premium
13.25%	4.14%	7.17%	1.94%	0%	N/A

Compare that to the result WITH the size premium.

Cost of equity =	Risk-free rate	+ ERP	+ IRP	+ Company-specific risk premium	+ Size premium
18.08%	4.14%	7.17%	1.94%	0%	4.83%

The difference in the cost of equity of 4.83% (18.08% – 13.25%) is highly significant. It materially affects value and implies a substantial adjustment to projected cash flow if the lower discount rate is used. Nunes said, however, that making an equivalent adjustment directly to cash flows is difficult to do in a reliable, quantitative manner. What specific assumptions should be used? How are those assumptions supported? How are they quantified and defended?

By contrast, incorporating the size premium directly into the cost of capital provides a structured, empirically supported mechanism for addressing size-related risk. It avoids the need for speculative or subjective cash flow adjustments and results in a more defensible and methodologically sound valuation.

If valuators use neither a multi-factor model nor a size premium, how can they account for the higher risk of smaller companies? Some may opt to put everything into a company-specific risk premium adjustment, Nunes said, with little support for it. The risk related to size isn’t specific to that company, after all — it applies to all small companies and therefore demands a separate size premium.

The Impact of the Rise of Private Capital Markets

Nunes spent a segment of the webinar digging into the effect of private capital markets on the alleged disappearance of the size effect.

Kroll analysis of data from the University of Chicago’s Center for Research in Security Prices (CRSP) found a 53% decline in the number of U.S. public companies from December 1997 to December 2024 (from 6,366 to 2,978). And private equity giant Apollo Global Management has reported that the number of private equity-backed companies now exceeds the number of publicly listed companies (approximately 8,000 vs. 4,000) in the United States.

Kroll uses CRSP data to calculate size premium and other valuation statistics. Since 2000, though, the number of companies in the CRSP Decile 10 (the smallest public companies included in the CRSP data) has fallen. That means fewer companies are being used to estimate the size premium. By contrast, the number of companies in the larger deciles has increased in that period.

Part of the explanation for this disparity is that companies are staying private for longer periods before they attempt to go public, backed by private capital sources. Apollo recently reported, for example, that the median age of a U.S. company at the time of its initial public offering (IPO) is 14 years. Morningstar has shared similar findings for global companies, with private companies waiting 11 years to go public, compared with 6.9 years in 2014.

The critical point is that, by the time one of these companies goes public and its growth data starts to become accessible, it’s likely to be much larger than when it began. The growth as a small private company never makes it into Decile 10. In other words, the rise of private capital markets is erasing some of the history — the growth experienced as a small company — that must be available to capture the size effect.

Nunes illustrated this using Meta (Facebook) as an example. The company was established in 2004 and valued at $100 million in 2005. If it had gone public at that point, it would have been included in Decile 10. When it did go public in 2012, the market cap for traded shares at the end of the first day of trading was $24.2 billion, including both traded and untraded shares, landing it in Decile 1 after the IPO. The massive appreciation since 2005 wasn’t captured in public markets because the growth occurred while Meta was private.

The fact that this growth occurred outside of public markets doesn’t mean the underlying risk is absent – only that the data needed to quantify it isn’t accessible to researchers.

Does the Size Effect Still Exist?

Nunes and Harrington acknowledged that the size effect can “go away” or even be negative at times. For example, the Decile 10 size premium was -1.4% for 2008–2023, but Nunes explained that this could be due to several factors. For example, small companies are known to fare worse during a recession; it’s during better economic conditions that small companies outperform large companies. Stretching the time period to 2000–2023 to include years when the economy was stronger results in a size premium of 4.6%.

Moreover, 16 years isn’t a statistically significant period when assessing premia. Appropriate analysis requires at least 30 years of data that covers several business cycles. Consider the equity risk premium (ERP). For the year 2022, Kroll calculated the ERP at -20.8% (yes, it was negative). From 1926–2022, however, it averaged 7%.

The size effect wasn’t identified until 1981 and, over that decade, it fell to -2.77%, It bounced back, however, to 2.84% in 1990–2023. This makes sense considering CRSP data showing that, over a 30-year holding period, Decile 10 small stocks outperform Decile 1 large stocks 92% of the time. Premia of all kinds need time to stabilize and emerge as a real pattern.

Conversely, some critics contend that using too long of a period skews the picture. For example, from the beginning of 1926 through 2023, the smallest stocks in Decile 10 greatly overperformed compared with other deciles (using five-year holding periods), for a CRSP Decile 10 size premium of 4.7%. Critics argue that this is due only to extraordinary outperformance in the early years of this period. Harrington used Kroll analysis of CRSP data to show that excluding those years doesn’t in fact eliminate the size effect. For 1955–2023, the size effect came out to 2.9%. It’s smaller, but it still exists.

The Size Premium in Kroll CRSP vs. Fama-French

Nunes and Harrington also discussed the difference in the strength of the size effect between the Kroll CRSP Deciles Size Study and the Fama-French Portfolios Performed on Size analysis. Many of the authors who write academic papers dismissing the size effect rely on Fama-French data, and the size effect is indeed weaker with that data.

However, Harrington attributed that largely to the fact that Fama-French uses a very different methodology when it comes to the companies it includes in its Decile 10 (both organizations use the same raw data). Fama-French has more companies in its Decile 10 because it includes some marginal companies with lower returns that CRSP excludes. The inclusion of these companies can drag down the decile’s returns, reducing the apparent strength of the size effect. In addition, CRSP rebalances its portfolio four times per year, while Fama-French rebalances only annually.

Stand Your Ground

The debate over the propriety of a size premium is likely to continue, as some opponents dig in their heels. As Nunes and Harrington demonstrated, the empirical record – properly analyzed across full market cycles and with appropriate methodologies – continues to support the inclusion of a size premium. Valuators who understand the evidence and its context are well positioned to defend it.