Micro Caps, Factor Spreads, Structural Biases, and the Institutional Imperative

So far in this series, we’ve covered faulty benchmark construction, the wide array of fundamental drivers, and the critical importance of quality in cutting through the noise among micro cap stocks. Now, we turn to the largest factor spreads I’ve come across in any segment of the market, real world considerations for implementation, and why the dichotomy of scale versus alpha could result in a persistent opportunity for outperformance.

Factor investing is more effective in micro than any other cap range

Though factor investing has rooted itself squarely in large cap equities, it significantly more effective in eclectic corners of the market—small and micro cap. Thus far, we touched on quality themes like financial strength, earnings quality, and earnings growth to screen stocks out. Let’s turn our focus to a broader suite of multi-factor themes by bringing value and momentum into the arena. While value and momentum are also effective in negative screening, they are most effective in identifying which stocks to select.

In an analysis of the performance of each multifactor theme from 1982-2016, shown below, there are enormous differentials in the return spread between high and low-ranking stocks. Spreads serve as a proxy for robustness of a factor. In the academic literature, these are hypothetical long-short portfolios that suggest the size of a systematic return premium.

The table below displays the spread between the return of high and low deciles in Large, Small, and Micro stocks on each theme. Using this lens, it is readily apparent that factors are more robust in micro than large, and even small stocks. Within the micro cap space, the smallest spread (Earnings Quality, 14.5%) is wider than the largest in Large Stocks (Value, 12.5%). This again highlights the importance of quality in microcap. As measured by the spread, quality is 3-4x more important in Micro as Large.


The spreads for value and momentum are greater than twice the spread in Large Stocks. The Value spread in Micro suggests one could go long a portfolio of the cheapest stocks and short the most expensive to earn an eye-popping 28.2% annualized return. Practically, this would be virtually impossible due to the operational challenges and costs of managing the short side of a micro cap portfolio. This real world complexity necessitates a focus on not owning the lowest ranked names—as opposed to shorting, and owning the highest ranked names.

The table below continues our previous analysis of adjusting the microcap universe for quality by eliminating poorly ranked names. To that high quality group of stocks, the two rightmost columns display the results from only owning names falling in the highest ranked decile by Momentum and Value, respectively.

As was the case with quality adjustments, a focus on momentum improves return by 3.6% annualized with 10% lower volatility than the quality adjusted group. The addition of value is even more compelling. A focus on value improves return by 6.1% annualized with 17% lower volatility than the quality adjusted group.

Structural features underpin the persistence of factors in micro cap

While I wish I was the only one aware of the massive spreads available in the micro cap space, the reality is that this information is well known. On a recent Masters in Business podcast, Ed Thorp remarked that "Any edge in the market is limited, small, temporary, and quickly captured by the smartest, or best informed, investors."

It is curious that investors have not arbitraged this clear edge. In practice, real world implementation costs quickly erode theoretical alpha if not managed precisely. Thorp also commented "Every stock market system with an edge is necessarily limited in the amount of money it can use and still produce extra returns." Along these lines, there are three inherent structural constraints to scale that hamper professional money managers, thus, protecting the persistence of alpha for dedicated investors at appropriate scale.

Supply of Transactable Stock

Liquidity can be thought of along a spectrum that ranges from the most liquid U.S. Treasury securities (T-bills) to illiquid private businesses (Private Equity). Moving to the illiquid end of the spectrum, the cost of implementation increases, which magnifies the importance of expertise when transacting in scale. The primary considerations as it relates to implementation on the liquidity spectrum are free float and dollar volume of transactions.


Float is the number of shares that are freely available to trade. While a mega cap firm like Apple has a free float of 96% of its shares outstanding, micro cap stocks tend to have the lowest free float as a percentage of the total shares of any market cap range. As of year-end 2016, their average free float was just 72% of shares outstanding. Because of their stage in the business life cycle, micro caps commonly feature large ownership by founders and insiders, and relative to large stocks, could be considered closely held. This feature is important because it reduces the available supply of stock to transact in by 28%. Given Apple’s 96% free float, $737 of its $767 billion in market cap is freely tradeable. Within the micro cap universe of $50-$200 million, just $72 billion of the $100 billion is freely tradeable. This curtails the size of any individual actor in the space, including large institutional investors and product providers.

Volume of Transactable Stock

Dollar volume gives a sense of transaction velocity, and an investor’s ability to enter and exit the market at will. The chart below details total dollar volumes, adjusted for inflation, for large, small, and micro stocks over the last 20 years. The difference in dollar volume is astounding. Dollar volume in large and small stocks is 245x and 43x greater, respectively, than micro cap. The relatively low $420 million volume for micro cap suggests that an active manager employing strategies similar to the ones discussed in this paper would find it rather difficult to oversee assets of significant size, while still being able to transact.[1]

Transaction Costs

While free float and volume constrain the ability to oversee a large amount of assets in the space, implementation costs erode theoretical factor spreads. At scale, these costs can be material. Real world costs have always been, and will likely continue to be, a barrier to entry at scale in less efficient spaces.

The three costs of implementation investors must grapple with are commissions, market impact, and bid-ask spreads. Fortunately, commissions have a relatively low impact on cost given the highly competitive nature of the brokerage business. Most institutional transactions occur at pennies per share (generally not relevant unless transacting in penny stocks). Commissions are the only true explicit cost. The more relevant and hidden share of costs are market impact and bid-ask spreads. Market impact is effectively how much you move the market when transacting at a certain size.

The chart below organizes the U.S. market into liquidity groups sorted from most to least dollar volume to assess the market impact and bid-ask spread of a hypothetical $10 million trade to get exposure to each liquidity group. Overlaid on the chart is the measure of dollar volume across the market. The horizontal axis is the average market cap for each liquidity bucket. From this, one can infer that dollar volume and market cap are highly positively correlated, while cost and dollar volume are clearly inversely correlated. Said another way, the smaller the stock, the lower the dollar volume, the more expensive to trade.

A $10 million trade could be implemented in the most liquid group of U.S. stocks for approximately 5 bps. Sophisticated trading techniques would likely neutralize this impact altogether as smart traders act as liquidity providers when establishing positions. This is made considerably easier with an average $480 million average volume in the most liquid stocks with which to work the trade. Capacity in this part of the market is virtually unlimited. On the other end of the spectrum, stocks in the least liquid bucket bear an all-in cost estimate of 220bps, a 44x increase in cost on 99.97% lower dollar volume with which to trade. Again, sophisticated trading techniques could minimize, but in this case not eliminate, relevant costs. Capacity in this corner of the market is low, but alpha potential remains massive net of transaction costs.

Supply, volume, and cost act as significant barriers to scale in micro cap. Not only do they require a specialized set of skills to implement portfolios in an efficient manner, but they require restraint on the part of money managers as it relates to asset gathering.

Scale Destroys Alpha, Alpha is Expensive to Realize

Objectively, the capacity of a given strategy is a function of supply, volume, and cost of implementation. Subjectively, and most importantly, capacity is determined by the investment manager’s desire for assets under management. Increasing strategy capacity can often lead to conflicts of interest between the business necessity for fee generation and the client necessity for alpha generation. There is a dichotomy in the fact that less liquid micro cap stocks require greater skill in implementation, while also requiring restraint in scale. From a product management perspective, the space is anathema to large money management organizations because asset-based fees on low capacity strategies struggle to support the costs of dedicated teams and infrastructure.

It is not uncommon for micro and small cap managers to creep up the market cap spectrum in order to realize greater capacity. Moving up-market results in smaller factor spreads, and therefore, reduced opportunity for alpha generation. Another alternative is bearing greater market impact costs through larger trade sizes. Both are unappealing options. Pushing the limits of scale could easily detract hundreds of basis points of return. Static, however, are manager fees, which capture a greater proportion of alpha even as the effectiveness of factors are diluted.

Look beyond highly competitive markets for factor exposure

We’ve been conditioned for decades to believe that obvious anomalies will be arbitraged away. Business schools teach the fundamental principles of the efficient market hypothesis even though it clearly does not reflect reality. Most investors readily agree that alpha is scarce. It is hard to find, highly sought after, and requires skill to extract.

Based on this premise and the recent horrendous performance of active managers, many investors establish their beachhead in the most competitive portions of the equity market, large cap, where alpha is scarcest.

I’ll call this the institutional perspective. Though we often mock the Hollywood scene, we are just as guilty of star-gazing. Institutions follow their peers like hawks, and research has shown that herding does occur amongst sophisticated investor asset allocations. For a multi-billion dollar plan, sheer size prevents them from accessing micro cap. A $5 billion plan would probably need to make a $100 million allocation to micro cap to make a difference to overall plan returns. That’s a large allocation to a constrained space. Going larger, a $30 billion plan? Forget about it! So, instead they pay massive fees for coveted, concentrated access to illiquid private equity markets where their edge cannot be arbitraged away—as easily. But, should smaller investors follow suit?

While large allocators face structural constraints, all else equal, this behavior doesn’t make sense for smaller investors. Just as business schools teach the intricacies of the efficient market hypothesis, students cross the courtyard for their next round of classes in…marketing strategy, corporate finance, competitive strategy, game theory, entrepreneurship…all geared toward identifying and exploiting strategic advantage in business. Investors should start building allocations where competition is low and alpha is less scarce—micro cap. Why not approach allocations from the non-institutional perspective?

At a time when the proliferation of factor investing is being driven by asset gatherers in highly-competitive spaces, my guess is that discerning investors find the research on factors in micro cap quite enticing. In this series on micro cap, we began by reviewing the Russell definition of micro cap, finding that the majority (88%) of what Russell considers micro cap to actually be small cap. The inferior construction methodology of the index—simple market cap weighting—omits critical considerations for quality and the cost of implementation in micro cap. The lackluster results of index returns fail to offer a compelling narrative for micro cap allocations. We then explored the composition of the micro cap universe to shed light on why it is a less competitive and lower quality space. A revolving door of new ventures and fallen angels flank a core group of steady state firms, which cause significant variability in the measurement of underlying stock fundamentals—often leading investors to write off the space as a junk yard littered with poor quality stocks. We then homed in on pure micro cap stocks that offer the potential for risk-adjusted return on par with large stocks through a framework for quality assessment. We noted the significantly greater spreads for the multi-factor stock selection themes of value, momentum, earnings quality, financial strength, and earnings growth in micro cap as compared to large and small stocks. We closed with an argument for the persistence of alpha generation in micro cap based on the structural barriers of supply, volume, and implementation costs to scale.

By breaking away from the institutional paradigm that is heavily aligned with the most competitive portions of the market, avoiding low quality, controlling implementation costs, and focusing in on stocks with strong momentum and value characteristics, I believe investors can realize substantial alpha in this capacity-constrained

[1] As of 4/30/2017