Microcaps’ Factor Spreads, Structural Biases,
and the Institutional Imperative
(Part 1 of 2)

Categories Author: Ehren Stanhope, Investing, Market Cap

The ironic twist to the proliferation of “factor”-based strategies in recent years is that the overwhelming majority of these strategies are1 launching in U.S. Large Cap Equity — the most competitive arena for any financial market in the world. Sure, factors can be effective in large cap but, lately, discerning investors are discovering that the factor research in eclectic corners of the market is much more compelling. This article presents our findings in perhaps the most capacity-constrained of those eclectic corners: microcap. Despite some unique considerations as it relates to liquidity and tradability (see Part 2), the opportunity in Micro is hard to ignore.2

Microcap stocks represent only a fraction of the total U.S. market’s capitalization (about 1.2%). These stocks are under-covered, un-loved, under-owned, and they offer dedicated investors a unique opportunity. Though it was small to begin with, the microcap portion of the total U.S. equity market has been cut in half in the past two decades. A key culprit, the proliferation of passive and “smart beta” investment products has resulted in disproportionate flows into the large cap space and, therefore, away from small and microcap stocks.

This article‘s intent is to reveal microcap’s inefficiency in some other areas beyond just the low institutional ownership and sell-side analyst coverage. We start out by reviewing Russell’s definition of microcap, then refining that definition to hone in on pure microcap stocks. We explore the composition of the microcap universe to shed light on why it is a less competitive space, and then provide a framework for quality assessment and alpha generation. We close with an argument for the persistence of alpha in the space, based on structural barriers to scale.

What is Microcap?

Russell defines the microcap space using an ordinal ranking methodology. Whereas the Russell 1000® (R1000) consists of the 1,000 largest stocks in the U.S., the Russell 2000® (R2000) contains those ranking from 1,001 to 3,000. The Russell Microcap® Index overlaps with the R2000 since it includes the 2,001st to 4,000th ranked stocks. Russell has conveniently created some overlap to prevent index churn — buying and selling constituents frequently crossing over between index thresholds — because there tends to be a lot of movement in the ranking of stocks at the lower end of the market cap spectrum.

Since these indexes are market cap-weighted, owning the Russell Microcap index is much the same as owning a small tail of the R2000 plus a minor allocation to even smaller names. There is an 88% overlap between the Russell Microcap Index with the R2000. Based on monthly observations from 1982–2016, the correlation of return between the two indexes is 0.96.3

A similar picture emerges when reviewing the share of dollar volume in each index. These tables summarize the allocation of the total U.S. market, based on capitalization and dollar volume across the indexes:


by Market Cap

by Dollar Volume

Notice how average dollar volume declines exponentially as you move away from large cap. Also, the small, unique portion of the Russell Microcap index (stocks ranked 3,001st through 4,000th) represents half the dollar volume weight as it does the market cap weight. Low volumes in this corner of the market can lead to significant transaction costs if not managed appropriately. This suggests that the cost of exposure to that small tail is very expensive, and likely a drag on performance of the index. In our own analysis over the period from 1982 through 2016, we found that applying a liquidity floor of $100K average daily volume (inflation-adjusted) improved the index return by 0.8%.

In current form, the performance statistics for microcap certainly do not drive a compelling narrative for adding an allocation to portfolios. The risk-return trade-off is poor enough that commonly used covariance optimization techniques in an institutional asset allocation study would suggest a zero-percent weighing to microcap. In fact, most would suggest little or no weight to the small cap R2000 as well. Given these results, it’s little wonder large cap stocks are all the rage.

Risk-Return Trade-Off (1982–2016, Compustat)

For the rest of this article, we diverge from the Russell index definitions to get a better sense of the composition of microcap and the alpha opportunity available. We define microcap stocks as those trading on U.S. exchanges with an inflation-adjusted market capitalization between $50 million and $200 million.5 Also, because our microcap universe is equal-weighted, not cap-weighted, we believe investors get a more “pure” view of the microcap market — that is, minimal overlap with small cap stocks. This group of about 1,300 stocks represents a disproportionately small 0.4% of total U.S. market capitalization. With average daily volume of just $700K per stock and a cumulative market cap of about $100 billion, the group is a mixture of exciting growth opportunities on the one hand, and the Land of Misfit Toys on the other. Once we screen out companies with unreasonable liquidity and non-U.S. domiciled firms (ADRs), the list dwindles to about 500 investable stocks.

For comparative purposes, we periodically refer to a Large Stocks universe comprising U.S. firms with a market capitalization greater than the average for the total market.6 Large stocks are instructive as they represent the bulk of investor’s U.S. equity allocation. It is analogous to the S&P 500 Index on an equal-weighted basis.

Microcaps’ Uniqueness 

It’s hard for investors to fully appreciate the microcap space without understanding how stocks have come to fall on the microcap spectrum. Whereas most large stocks have succeeded in attempts to grow their businesses, as recognized by their multi-billion-dollar valuations, microcap stocks are on a completely different playing field. These businesses range from biotech startups to failing businesses that have depreciated to their current middling market cap. From an empirical perspective, the result is a lot of noise in the data.

To demonstrate, let’s look at one of a firm’s most fundamental metrics: sales growth. Though its efficacy as an investment factor is marginal, sales are the lifeblood of any firm and have a cascading effect on all other elements of their financial statements. This chart compares the distribution of 3-year sales growth across large and microcap stocks:

Range of Positive 3-Year Sales Growth (CAGR)
line graph

Notice the significantly fatter tails for microcap relative to large stocks. If growth in sales is the most basic way to assess the status of a firm, then this suggests much greater dispersion in the underlying microcap metrics. Popular rhetoric decries small and microcap stocks as being junkier than their large cap counterparts. While this is true on average, a wide dispersion in fundamental metrics means that many phenomenal businesses get hidden behind a wall of meaningless averages.

A deeper dive reveals a disparate group of continually evolving —
and devolving — businesses

Investors have widely accepted that there exist many different types of private equity: Angel Investing, Venture, Early Stage, Late Stage, Mezzanine, LBOs, and Distressed. Interestingly, in the private space, these labels represent the need of the firm receiving the investment. Just as there are many sub-classes of venture capital and private equity, such is the case with microcap stocks, but for whatever reason, we do not view these businesses with the same categorical lens as we do private investments.

The microcap universe can be divided into three broad categories: (1) New Ventures that have become revenue-generating within the past 3 years, (2) distressed Fallen Angels that have descended into the microcap universe from small cap — and sometimes large cap — and (3) those in a Steady State (microcaps for at least 3 years).

To contextualize microcap, think of a revolving door where firms are constantly entering and leaving for different reasons, as diagrammed here:7

”The Transitory Microcap Universe”


This simplistic perspective on the universe is relevant because it sheds light on the strong inherent biases that skew the underlying fundamental characteristics. Below is the same distribution of Sales Growth for microcap, broken down into those three categories.8 These disparate groups possess fundamentally different metrics that obscure a lot of noise in microcap stocks when averaged together.

Range of Positive 3-Year Sales Growth (CAGR) — Microcap

line graph

New Ventures, with their small sales bases, are highly skewed towards positive sales growth. Unsurprisingly, New Ventures tend to be comprised of Information Technology and Health Care stocks — most notably biotech, software, and pharmaceuticals. Currently, those industries represent a rather large 20% of the microcap universe. The average annualized return of this group from 1982–2016 is 4.7%, woefully short of the microcap universe average of 8.9%. Adding insult to injury, annualized volatility for this group is 27.8% (likely a result of the nature of outcomes in the space). Biotech firms generally succeed or fail — binary outcomes — giving investors strong gains or staggering losses.

Steady State firms are more centered in the distribution, but still positively skewed. At 60% of the overall universe, a good proportion of Steady State firms are Commercial Banks and Thrifts. These two industries represent 20% of the universe currently. Banks are the least volatile microcap industry and one of the top performers. The remainder of firms in this category tend to be widely dispersed across industries. Steady State firms are the highest performing of the three categories with an annualized return of 10.1% and volatility of 22.8%.

Fallen Angels skew significantly in the negative growth direction. This is a group of firms ranging across industries. Currently, the oil & gas industry has the highest representation in this category. It tends to offer representative groups of stocks that suffered in the previous cyclical business downturn. Fallen Angels gave investors an annualized return of 8.0% from 1982–2016, with volatility of 27.4%.

Our task as factor investors is to develop empirical criteria that enable us to cut through the noise to separate the good from the bad. Given the perspective above, we know there are reasonable fundamental explanations for the “junk-ish” nature of microcap stocks. Quite simply, a lot of microcap stocks possess poor business characteristics, whether weak cash flow generation, too much leverage, or dwindling and unprofitable revenues. By codifying firms and removing those with poor characteristics, we can improve investors’ base rates9 for success.

Leveling the playing field

We’ve established that the fundamental drivers of microcap businesses are widely varied, at least in part, due to their state of being — New Venture, Steady State, and Fallen Angel. Let’s take a step back to build intuition for stock selection regardless of category. In our research, we have found several quality metrics to be indicative of good businesses. Generally, businesses should be profitable, growing at a reasonable pace, and appropriately capitalized. Individually, these metrics are effective, but when used together thematically, they provide a powerful framework for eliminating poor-quality stocks. The table on the previous page compares several characteristics for Large and Microcap stocks.

Measures of Quality (1982–2016, Compustat)

In each case, a simple average of characteristics for microcap stocks betrays the universe’s lower-quality nature relative to Large Stocks. One would assume from looking at the microcap column that these businesses are rapidly growing their asset base, not particularly profitable, taking on tremendous debt, and generating negative free cash flow. Each one of these signals seem to indicate a hunger for cash.

Change in Net Operating Assets (NOA) measures the growth in assets required to run the business. If a small consumer products company, for example, hit the jackpot with a new contract at a huge retailer and then had to ramp up production to fulfill the order, this metric would increase. Sales growth requires large investment for raw materials, inventory, delivery of finished goods, and equipment for ongoing production. The challenge with growth is that it requires huge cash outlays. This cash is all outlaid before revenue occurs. Dramatic growth in operating assets can be indicative of stress, as it leaves the business in a tenuous cash position. This state of affairs seems to be the norm for microcap stocks with an average change in NOA of 44.3% — almost double the rate for large stocks.

Few small firms have enough internal capital to fund such large investments. They then turn to capital providers to fund growth — issuing equity offerings, or taking on debt. Keep in mind that many microcap stocks have no analyst coverage, so the ability to tap equity capital markets is limited and expensive.10 Debt becomes the default source of capital. The average 1-year change in debt for the universe is 32.6%, and debt-to-equity is on par with Large Stocks. The ROIC of just 13.2% indicates that capital, of which debt is a part, is not being as efficiently invested as with Large Stocks. A free cash flow yield of -4.5% suggests economic value is being destroyed, rather than created.

Each of these characteristics are components of multi-factor themes that we use to assess the quality of a firm: Earnings Quality (NOA), Financial Strength (D/E, Change in Debt), and Earnings Growth (ROIC).11 To level the playing field for comparing Micro to Large Stocks, we can rank stocks in the microcap universe based on these multi-factor themes and eliminate the lowest ranking decile. Firms falling into these groups tend to be poorly capitalized and have low profitability and weak earnings quality.

By adjusting the microcap universe, the overall metrics dramatically improve and, in some cases, are actually better than Large Stocks. Quality-adjusted microcap stocks reveal much more moderate growth rates in NOA. An average 13.7% is indicative of businesses that are more likely to handle organic business growth without needing to seek substantial funding from debt or equity issuance. The improvement in the 1-Year Debt Change metric after adjusting for quality supports this logic. A large 32.6% increase in debt decreases to just 12.1% — lower than the average for Large Stocks.

Clearly, the universe quality metrics have improved, but how does this translate into investor returns? It turns out that eliminating poor quality boosts the return of our universe by 5.3% annualized with a 0.7% reduction in annual volatility, as shown in this table:

Quality Matters (1982–2016, Compustat)

Incorporating quality criteria to eliminate stocks from consideration has a dramatic impact on microcap stocks. Performing a quality assessment highlights the importance of a less appreciated aspect of factor investing. While many researchers focus on the outperformance associated with factors, using factors to avoid groups of stocks can be just as positive a contributor to investor returns. After controlling for quality, the risk-adjusted returns available are in-line with large stocks. Earlier we mentioned that the historical return and risk of the Russell Microcap® Index did not merit an allocation according to mean-variance optimization. This simple quality screen alters the space’s characteristics to such an extent that it becomes a viable source of differentiated return for investors.

Go to Part 2 of this 2-part article, which covers factor efficacy in Microcaps, the supply and volume of transactable stocks, structural features, transaction costs, the liquidity continuum, and how scale destroys alpha.

Go to Part 2

  1. …boldly, or blindly…
  2. As factor investors continually seeking alpha, we find that “true microcap” can tilt the probabilities of investment success in the investors’ favor.
  3. Despite the highly-correlated returns of Russell’s 2000 and Microcap indexes, the relevant iShares Russell ETF [IWC] carries a 0.60% expense ratio — three times higher than the fee of its Russell 2000 counterpart [IWD], which costs just 0.20%.
  4. 1982–2016 (Compustat)
  5. The OSAM Microcap Universe would be analogous to the approximately 2,600th to 4,000th stocks using Russell’s ordinal market cap ranking methodology.
  6. At present, this includes stocks above an inflation-adjusted $7 billion market cap.
  7. From 1982 through 2016, New Ventures represented 25% of the microcap universe, while 16% were Fallen Angels, and 59% were Steady State. Effectively, 41% of the universe is in some sort of transition — ranging from startup to established firm, or from established firm to potential liquidation.
  8. An analysis on 3-year earnings growth reveals similar patterns, though with greater noise.
  9. Base Rates are batting averages for how often factors outperform the market in rolling periods.
  10. See “Microcap as an Alternative to Private Equity” (osamlibrary.com)
  11. For a full description of our multi-factor Quality themes, please request a copy of our “OSAM Guide to Factor Alpha” c/o info@osam.com