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Factors to consider when allocating to US small-cap stocks

Multiple authors
18 min read
2026-05-31
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Archived pieces remain available on the site. Please consider the publish date while reading these older pieces.
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The views expressed are those of the authors at the time of writing. Other teams may hold different views and make different investment decisions. The value of your investment may become worth more or less than at the time of original investment. While any third-party data used is considered reliable, its accuracy is not guaranteed. For professional, institutional, or accredited investors only.

In September 2018, our team wrote a paper on market efficiency entitled “Reinventing the Core,” which established a framework for assessing the relative merits of active management in different equity universes. In it, we identified the US small-cap equity universe as one of the more inefficient markets and one where active management has historically generated strong alpha. What our 2018 paper didn’t address was how best to invest in small caps. The purpose of this paper is to pick up where the last one left off, exploring important factors to consider when allocating to US small-cap stocks and devising a framework for overcoming the universe’s unique challenges and pursuing the alpha opportunity.

In particular, we share our research on three key issues: 

  • Why get active: A look at the potential of active management in US small-cap stocks. 
  • How to pursue the alpha opportunities: Thoughts on how active managers can add value by avoiding “junk” and holding on to “graduates.”
  • Ways to build an allocation: Trends in the active small-cap space and key considerations when building an investment program.

Why get active: Exploiting a breadth of opportunities

In their 1999 book Active Portfolio Management, Grinold and Kahn popularized the concept of the Fundamental Law of Active Management. They developed a formula that defines risk-adjusted returns as the product of investor skill and the breadth of the opportunity set (or, said differently, the number of independent bets an investor makes). The implication is that investors can improve their results by either improving the quality of their decision making (skill) or increasing the number of bets they make. With this idea in mind, we believe the US small-cap market is very attractive for alpha generation because of two unique characteristics:

  1. It is relatively inefficient, which can potentially make it easier for active managers to achieve better results.
  2. The breadth of opportunities is high, and therefore there’s a wide opportunity set to which investor skill can be applied. 

There are a variety of ways to measure breadth. Using the S&P 500 and the Russell 2000 indices as proxies for large- and small-cap opportunity sets, the Fundamental Law of Active Management says there is twice as much breadth in small caps as there is in large caps. To complement this, we also looked at several other characteristics to help assess breadth, including return dispersion, index concentration, and the concentration coefficient. 

Return dispersion
While the number of stocks is an input into the Fundamental Law of Active Management, it is a static concept. Therefore, we also looked at the dispersion of returns across the small-, mid-, and large-cap universes, which introduces volatility and the passage of time. Our intuition is that, all else being equal, the more differentiation between the performance of stocks in a universe, the more opportunity there is to beat the benchmark. As shown in Figure 1, there is a clean ranking of dispersion across the cap spectrum, with small cap having the highest dispersion and large cap the lowest.

Figure 1
factors-to-consider-when-allocating-fig1

Index concentration
Since we published our market efficiency paper in 2018, our assessment of breadth in different universes has evolved to incorporate measures of index concentration. In this case, we looked at the weight of the top three names in the index. The intuition here is almost the opposite of dispersion: the more concentration that exists in the top names in an index, the fewer effective bets there are to make and, therefore, the less chance there is for investors to differentiate themselves versus the benchmark. Recently, this concept has been particularly important to the results of active management observed in the US large-cap and US growth universes. When viewed through this lens, breadth is considerably challenged in large caps, while mid and small caps look similarly untroubled by concentration. This is detailed in Figure 2.

Figure 2
factors-to-consider-when-allocating-fig2

Concentration coefficient
Mathematically, the concentration coefficient is defined as “the reciprocal of the sum of the squares of the weights of the holdings in a portfolio.” It expresses portfolio concentration as the equivalent number of equal-weighted holdings. In some ways, this concept is a combination of the number of names and the index concentration measures as it adjusts the number of names in the universe for the concentration level. As shown in Figure 3, small cap is almost double midcap, and midcap is more than seven times large cap. Because of the large concentration in large cap, the “equivalent number of stocks” is just 13% of the number stocks in the index, while for midcap and small cap it’s 57% and 44%, respectively.

Figure 3
factors-to-consider-when-allocating-fig3

Regardless of how we measure breadth, the same pattern emerges: small-cap stocks offer the largest opportunity for applying active management skill in the US (when compared to mid and large cap). We believe that this dynamic creates a favorable backdrop for actively managed strategies to pursue attractive alpha in small caps. 

How to pursue the alpha opportunities: Avoiding bad businesses and participating in prolonged success stories

The hallmarks of our team’s factor research approach are the integration with our manager research efforts and our focus on capturing key performance drivers from the different investment processes used by a diverse group of fundamental stock pickers. Through this approach and our conversations with fundamental managers at Wellington, we have seen that the performance of small-cap strategies can be impacted by investments in lower-quality companies and the forced selling of successful stocks that have graduated out of the universe. A potential benefit of active management within small caps is the ability to combine these fundamental insights and the previously noted breadth of opportunities to generate alpha across some of the best and worst names in the universe. 

Avoiding junk
In his famous 2015 paper on US small-cap stocks, Cliff Asness argued that the “size” factor was historically attractive if you removed the lower quality or “junk” names from the universe. While our focus in this paper isn’t a “case for” small caps in absolute terms, the implications of his findings are no less important for generating alpha within US small caps. We believe there’s alpha to be had in avoiding the junk.

Many small cap companies have yet to prove that they are, in fact, a “going concern.” They may, for example, be early-stage companies with unproven business models that are heavily reliant on external financing to continue operations. To bring this to life, the left chart in Figure 4 shows the percentage of companies in their respective market-cap-related indices that fail to earn a return on invested capital in excess of their cost of capital. These “junkier” companies are wealth destructive to shareholders and other capital providers. On average over the last 20 years, there have been more than twice as many of these companies in the small-cap market as in the large and midcap markets. In fact, almost half of the small-cap universe falls into this group. The right chart in Figure 4 shows the percentage of companies that have a 5% or higher probability of default using a Merton Model of credit default risk. The small-cap universe has substantially more of these companies, and unlike mid and large caps, their representation in the index is above-average relative to the last 20 years. A passive allocation to small caps leaves allocators increasingly exposed to these firms, while active managers can potentially harvest alpha by limiting their exposure to the group.

Figure 4
factors-to-consider-when-allocating-fig4

Owning graduates
One observation from working with small-cap stock pickers over the years is that many lament the fact that at some point they’re forced to sell some of their best ideas because the stocks “graduate” from the small-cap universe. A benefit of active management in smaller-cap stocks is that, more often than not, managers have some flexibility to continue to own some of these high-conviction names that have graduated. 

This has led us to a natural question: Are these graduates a potentially reliable source of alpha for small-cap strategies? To explore this, we examined the performance of graduates versus the Russell 2000 Index (where they graduated from) over the 24 months post-graduation, shown in the left chart in Figure 5 (dark-blue line). The right chart in Figure 5 shows the consistency of that outperformance and, specifically, the percentage of stocks each month with a positive cumulative average excess return. The takeaway is that while the population of graduates did outperform the Russell 2000 as a group, the consistency was not high (less than 50% of graduates outperformed). To simulate the stock-picking process of a fundamental manager, we created an alpha score for each stock based on its valuation, fundamental trend, and quality. We then took the population and sub-divided it into two groups: those with positive and negative alpha scores. Focusing on the graduates that looked attractive fundamentally greatly improved the outperformance as well as the consistency (light-blue line). We read this as confirmation that graduates have historically been a promising source of alpha for active small-cap strategies.

Figure 5
factors-to-consider-when-allocating-fig5

We also investigated how consistent the opportunity set for graduates is, as the volatility of the opportunity set could have implications for implementation. Figure 6 shows the number of stocks that graduated from the Russell 2000 Index each year at the June month-end index reconstitution. The average is 44 stocks and the opportunity set has been fairly consistent since a spike in the early 2000s. As such, we believe that graduates can provide a notable and persistent opportunity for active managers to outperform passive indices in small cap. An active manager can not only gain access to this important opportunity set but also differentiate among these names to pursue stock-selection alpha.

Figure 6
factors-to-consider-when-allocating-fig6

Ways to build an allocation: Key considerations when implementing a small-cap program

Every investment universe has its own unique dynamics and small cap is no different. Figure 7 looks at the peer universe through a standard Barra model and picks out the factors with exposures that approached being significant and/or consistent. The universe appears to have a bias towards owning profitable companies (orange line), which may also be the cause of the slight defensive tilt in beta (light blue line) exposures (or the relationships could be coincident). These results are not surprising given the tail of “junkier” stocks in the small-cap universe discussed above. In addition to this “defensive quality” tilt, we also observe a noticeable value tilt (yellow line) over much of the historical sample.

Figure 7
factors-to-consider-when-allocating-fig7

To see whether this value tilt has been historically justified by returns, we looked at excess returns of the best performing fundamental factor from each of our three broad factor classifications (value, growth, and quality). The results, which are detailed in Figure 8, support the effectiveness of the universe’s value-tilt as this factor has meaningfully outperformed the Russell 2000 and other broad factors over our sample period.

Figure 8
factors-to-consider-when-allocating-fig8

That said, while value was the best performing factor over this period, growth and quality factors did have positive returns. Any small-cap allocation only focusing on attractive valuation strategies ignores the potential benefits of diversification — i.e., the only “free lunch” in financial markets. Figure 9 looks at the risk (tracking error) and excess return of each factor and compares them to a simple equal-weighted blend of the three factors. Our observation is that the equal-weighted blend achieved similar returns to value alone, and considerably lower risk than each stand-alone factor.

Figure 9
factors-to-consider-when-allocating-fig9

On a risk-adjusted basis (shown in Figure 10), it becomes clear that a multi-factor approach to investing in small caps may be more risk efficient than focusing simply on a valuation-based program. This could be achieved by allocating to multiple strategies that each specialize in one of the three areas, or by allocating to a single strategy that captures all three. 

Figure 10
factors-to-consider-when-allocating-fig10

Understanding active risk drivers
We’ve talked a lot so far about excess returns in small cap, but less about risk. We believe that the path of returns generated can often be as important as the aggregate level of returns generated (e.g., an investment that outperforms over three years by having one massive quarter and underperforming in the other 11 can be difficult to stomach). Importantly, what a manager doesn’t own can be as meaningful to risk as what is owned. Using holdings-based active manager Lipper indices, Figure 11 looks at the largest average industry underweights relative to the Russell 2000 across active strategies. Some of these big underweights could likely relate back to the prevalent style biases we identified, such as a preference for profitability. This comes through in the underweight to biotech and IT companies, many of which are “pre-profit” companies. Separately, our research also suggests that idiosyncratic opportunities may be less prevalent in real estate, banks, and utilities, making them less attractive to active managers.

Figure 11
factors-to-consider-when-allocating-fig11

To bring this driver of active risk concept to life, let’s focus on biotech stocks. While active strategies tend to be structurally underweight biotech, these names exhibit extremely high volatility and, as such, not owning them or having them be a large underweight can generate a lot of relative volatility over the short term. Figure 12 shows the percentage of predicted tracking risk coming from the underweight to biotech in the active index versus the Russell 2000 Index. At times it’s been as high as two thirds of the risk! 

Figure 12
factors-to-consider-when-allocating-fig12

One explanation for this dynamic could be that active managers think the returns of the biotech space are unattractive and that the relative risk is worth it to avoid the industry. However, over the past 10 years, the Russell 2000 Biotech Index had a rolling 12-month return greater than the aggregate Russell 2000 Index 57% of the time. Rather than just ignoring biotech altogether and accepting the resulting relative volatility, we think a better answer may be to own a diversified basket of biotech stocks that leans into alpha factors, while diversifying across enough names to dampen the volatility impact from any one stock. Owning an aggregate industry weight that’s close to the benchmark may effectively hedge most of the relative risk from the volatile industry. To that end, we believe that an understanding of risk drivers and prudent risk management are paramount to any successful implementation of a small-cap allocation. 

A path forward: Getting attractive active exposure by balancing fundamentals  

In this paper, we’ve built on our previous research to highlight the attractive alpha-generating potential in US small caps. We’ve also explored the unique features of the US small cap market we think investors should take into consideration when building an allocation to the space. We believe that one of the best ways to efficiently harness the excess return potential in US small caps while balancing the unique nuances of the universe is to use a well-diversified and risk-managed approach that can help navigate the long-term nuances of the opportunity set.


IMPORTANT DISCLOSURES

For all data pertaining to the FTSE and/or Russell indices:
Source: London Stock Exchange Group plc and its group undertakings (collectively, the “LSE Group”). © LSE Group 2022. FTSE Russell is a trading name of certain of the LSE Group companies. e.g., “FTSE®” “Russell®”, “FTSE Russell®” is/are a trade mark(s) of the relevant LSE Group companies and is/are used by any other LSE Group company under license. All rights in the FTSE Russell indexes or data vest in the relevant LSE Group company which owns the index or the data. Neither LSE Group nor its licensors accept any liability for any errors or omissions in the indexes or data and no party may rely on any indexes or data contained in this communication. No further distribution of data from the LSE Group is permitted without the relevant LSE Group company’s express written consent. The LSE Group does not promote, sponsor or endorse the content of this communication.

For all data pertaining to the S&P 500 Index:
Source: Standard and Poor’s. The “S&P 500 Index” is a product of S&P Dow Jones Indices LLC or its affiliates (“SPDJI”) and has been licensed for use by Wellington Management Company. Standard & Poor’s® and S&P® are registered trademarks of Standard & Poor’s Financial Services LLC (“S&P”); Dow Jones® is a registered trademark of Dow Jones Trademark Holdings LLC (“Dow Jones”); this research is not sponsored, endorsed, sold or promoted by SPDJI, Dow Jones, S&P, or their respective affiliates, and none of such parties make any representation regarding the advisability of investing in such product(s) nor do they have any liability for any errors, omissions, or interruptions of the index.

For all data pertaining to Refintiv Data (Lipper):
Source: Refintiv (Lipper). Select data provided and copyrighted by Refinitiv. Republication or redistribution of Refinitiv content, including by framing or similar means, is prohibited without the prior written consent of Refinitiv. Refinitiv is not liable for any errors or delays in Refinitiv content, or for any actions taken in reliance on such content.

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