Introduction

The market microstructure is undoubtedly a complex structure comprising a wide breadth of investors with varying investment styles, time horizons, and philosophies. This breadth and complexity is one of the reasons we believe that market efficiency can be low in shorter periods of time, but more efficient over medium-to-longer periods of time as investors take advantage of significant dislocation. However, short-term inefficiency in the marketplace has become even more elevated over the last decade (and more notably over the last handful of years), surpassing anything we’ve seen in the past. This change, in our opinion, has largely been driven by the changes in market microstructure over the years where a significant percentage of market assets, volume, and underlying trading strategies have been heavily influenced by participants that do not fundamentally value individual businesses. Rather, many of the participants’ focus has been driven by either a price momentum strategy (i.e., passive investing), individual or group sentiment often driven through social media and other outlets (i.e., meme stock driven demand through pockets of retail investors), investing with a hyper short-term focus or trend, or some other nuanced bias. Regardless, many of these investment and trading strategies invest with little to no fundamental bearing whatsoever. Others, such as many pod-shops or certain hedge funds, tend to consider a plethora of fundamental and technical factors but will leverage anything in their arsenal in an attempt to generate returns for investors. Many of these strategies may be looking at a dislocation over a time horizon that is as short as a quarter or less in duration. There is nothing wrong with this approach, and we commend those who are able to generate relatively consistent returns for their clients. We merely highlight these strategies to underscore how the structure has changed in such a way that puts many fundamentally focused active investors in the minority of what moves the market in any given day.

What is the purpose of this paper?

The intent of this piece is to highlight how the shifts in structure have created significant dislocation in the market over shorter periods of time driven by various market inefficiencies. In our opinion, the impact of increased dislocation is two-fold:

It creates a tremendous amount of opportunity for those who are opportunistic and quick to transact.
It can also, however, create more volatility of relative returns, forcing clients, sponsors, consultants, and other allocators to be more patient with underlying managers.
There is no question this backdrop creates a challenging role from a manager research, or allocator perspective. Regardless, we believe the opportunities that present themselves during these periods of more intense and severe dislocation will ultimately reward clients who conduct the appropriate due diligence work. It will, in our view, continue to be even more imperative for allocators to have a clear understanding of process and performance expectations. Patience is key for those allocators regardless of the timeframe under consideration.

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The Data

One of the challenges with quantifying something as complex as the market microstructure shift in the market is the vast number of investors, trading strategies and overlapping data points. We acknowledge the challenge in reconciling the underlying asset and volume data (along with the alignment of dates), but as we explore some of the figures below and changes over the years, we believe one will have a clear understanding of this shift. Let’s explore some of the more dominant drivers of either assets under management and/or trading volume over the years – both key considerations of what drives the market.

Passive Strategies: Passive investment strategies are expected to reach 56% of total U.S. Fund assets by 2027, according to Institutional Shareholder Services (“ISS”).¹  This figure is relative to 27% about a decade ago, and the effect is clearly more pronounced if you go back further in time.² One interesting point to highlight is that the percentage of passive investing is most severe within core indices, as both value and growth are significantly less, though still material. Regardless, according to a study highlighted in a recent Bloomberg publication, index chasing has resulted in distortion of stock prices and “extreme market moves.” The same article cites a study conducted by a team from Goethe University in Frankfurt. The team found a correlation between greater index ownership and short-term noise trading (i.e., movement in pricing unrelated to fundamental information), ultimately decreasing the relevance of firm specific news.³

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For more recent anecdotal evidence of the distortion passive can play on underlying securities and the market as a whole, one can look at the composition of the S&P 500® Index, as represented by the “Magnificent Seven” (i.e., Microsoft, Amazon, Meta, Apple, Alphabet, Nvidia, and Tesla) as of 12/31/2023, compared to just five years ago. While Tesla was the only security not in the S&P 500® Index five years ago as of 12/31/2018, the Magnificent Seven comprised 14.97% of the Index, whereas now it’s roughly double the concentration at 28.01%.⁵  If one were to look at the more highly concentrated Russell 1000® Growth Index, the shift is even more dramatic. While recent developments in potential Artificial Intelligence capabilities have created a legitimate demand impact for companies likely to benefit, it is hard to argue that the role of passive as a price momentum strategy isn’t playing a substantial role in exacerbating the demand component.

Retail Investors: The role of retail investors has also increased dramatically over the years. By some estimates, retail investors represented 10% of U.S. equity trading volume pre-pandemic, but now has reached closer to 20%-30% of all domestic trading volume.⁶ Other sources, such as Bloomberg Intelligence cited through an Economist publication, have retail volume hovering above 30%, and even reaching in excess of 40% of trading volumes in 2021 (image below). At the same time, institutional investors (excluding quantitative investors), went from a peak of 50% of U.S. equity trading volume over the last decade to approximately 30% as of 2021. Aside from the absolute numbers, it is astonishing to see that through this analysis, retail trading volume actually surpassed both institutional and quant strategies.⁷ Clearly, the use of social media to broadly disseminate and even collude on investment ideas, more retail “user friendly” trading platforms from the likes of Robinhood and elsewhere, along with zero commission fees on many platforms, have been catalysts for this transition. Additionally, one could argue the work from home environment and a resilient consumer partially fueled by stimulus provided during the COVID-19 environment, have further fostered an environment and means for greater day trading for many retail investors.

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In our opinion, it is undeniable that the retail investor in aggregate can move the market and create pockets of hyper irrationalism and foster inefficiencies such as witnessed in the first quarter of 2021 or even more recently in pockets of 2023. Equally as important, we would argue that specific observable trends in the marketplace, such as when lower quality meme stocks were in clear demand, can also cause a significant knock-on effect where quantitative investment strategies and algorithms pick up on such a trend and lean their trading models heavily towards a “risk-on” driven model or strategy. In fact, during the early meme stock driven environment in the first quarter of 2021, it was not simply a story of the obvious headline stocks outperforming considerably, such as GameStop, AMC Entertainment, and Bed Bath & Beyond, but quite simply, stocks that were severely distressed and lower quality in nature were in clear demand. As witnessed from the image below where we took the spread between the top and bottom decile of a handful of factors from Ned Davis’s Small Cap universe, stocks exhibiting the following characteristics were meaningful outperformers: high short interest, high beta, less stable earnings, lower return on invested capital and lower sales growth, among others irrational factors.

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From a similar lens, we arbitrarily assessed the top 25 best performing stocks within the Russell 2500™ Value index during this same meme stock driven first quarter of 2021. The composition summary was such that 20 of the 25 best performers (80%) had reported a loss over the trailing 12-months, had an average short interest of 14.8%, an average 3-year beta versus the index of 1.3, with the majority also generating negative free cash flow.⁹ The fourth quarter of 2023 looks eerily similar and likely worse.

It appears clear to us that short periods of complete irrationality have spiked in frequency over time, heavily influenced by these underlying cohorts of market participants and drivers. Even taking calendar year 2023, as an example, we noticed multiple intermittent periods of what we would deem strange activity in the marketplace, such as in June and July where lower quality stocks fell in vogue. To illustrate this point further, the chart below maps the price return of an ETF with the ticker, “MEME”, which unsurprisingly tracks a basket of meme-oriented securities. One can see the dramatic pop in return and volume for the ETF, which returned an incredible 37.7% against the S&P 500® Index’s return of 9.8% in this short two-month time frame before retreating materially over the next few months.

As highlighted earlier, market irrationality is both a positive and a negative. On the positive side, these intermittent and strange periods can create ample buying and selling opportunities for those that are relatively quick to transact and follow a disciplined and consistent process. Given we have noticed many of these periods tend to be shorter in duration, they can help create alpha generating opportunities as the market  re-sets as witnessed in the few months following the June and July period where valuation and fundamental factors such as profitability and balance sheet strength were generally reflected in stock prices before retreating in the fourth quarter, as referenced earlier. The downside of an environment with more frequent dislocations is the potential faulty conclusions that could be drawn by allocators and investors based on short-termism, which can potentially lead to value destructive decision making.

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Pods: Pods have become notorious as a growing component in the hedge fund community whereby specific pools of capital are often delegated to small teams with the focus of maximizing potential return, with underlying sleeves aggregated at a fund level for investors. While we acknowledge the generalization in description, many of the underlying pods have become very short-term oriented, trying to isolate any anomaly possible whether that is from a technical trading strategy, or otherwise. According to an article from Bloomberg, as of mid-year 2023, there were 55 pod shops overseeing $368 billion in AUM, up from 29 firms running $149 billion just five years earlier in 2018.¹⁰ From a volume perspective, we would argue the impact is significantly greater than any cited AUM number given they tend to employ a high degree of leverage and turnover. Additionally, given the high concentration of pod shops within the market, some of the top firms can have significant outsized positions, that when accounting for the leverage and turnover, have the ability to move the market in securities in which they transact. This is exacerbated by a higher propensity for crowding of trades across a limited number of firms in this hedge fund sub-set, hence creating potential for further inefficiencies.    

High Frequency Trading/Algorithmic Trading: We would broadly define this combined bucket as trading and investment strategies that look to take advantage of a variety of market driven factors, including specific trends. What this has done, in our opinion, is exacerbate specific periods of heightened market favoritism or otherwise, forcing the market “pendulum” to swing farther in either direction than would be considered efficient or rational. It is estimated that prior to 2006, high frequency trading alone accounted for slightly more than 20% of all U.S. equity trading volume¹¹, before increasing significantly to approximately 50% based on estimates at the end of 2020.¹²

This increase has also, in our opinion, been a contributor to significantly higher trading volume in the market, which can cause greater volatility in short-term security performance and potential “noise.” We would argue such noise is prevalent across the market capitalization spectrum, but most exacerbated as one moves “down-cap” into small and smid stocks. In fact, an article from MarketWatch cited that “Small-cap stocks now experience about 40 times as many price gaps of at least 1% as large-cap stocks do, an eight-fold increase compared to 2009.”¹³

From another vantage point, a somewhat dated 2019 article from the Economist (highlighting work from Deutsche Bank) states that it was estimated that roughly 90% of equity futures trades and 80% of cash-equity trades are done through algorithms without any human interaction or input. The same article cited that just 10% of institutional trading, as of end of 2019, was estimated to be executed by traditional equity fund managers.¹⁴ This would suggest to us that high frequency trading, algorithmic trading, and other electronic trading platforms have a significant influence on the markets and underlying security pricing.

Options Trading: While data on options trading could clearly overlap with other investing cohorts (such as retail investors), it is remarkable that in 2021, the notional value of total shares underlying options in the U.S. exceeded that of cash equity shares transacted for the first time in history.¹⁵ Therefore, the use of leverage through options trading to make directional bets (and for hedging and other risk-management endeavors, of course) has driven this significant milestone that clearly can lead to wider price swings in share prices. The chart below highlights the massive uptick in North American equity options volume over the prior 3-4 years through 2023.

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Concluding Comments

We have cited a variety of varying AUM and volume data points for market participant cohorts, as well as trading strategies employed by both market makers and other participants. Given the significant complexity in the topic of market microstructure, it can be difficult to conceptualize. However, the comments and data provided above are intended to provide a meaningful explanation of why security mispricing and inefficiencies have, in our opinion, appeared significantly more elevated in recent years. As previously cited, this is not necessarily a bad thing. We believe it creates ample opportunities for investors as wide price swings, uncorrelated to underlying fundamentals in the short-term, should lead to price correction over a longer-time frame, driven by many of the same market participants and trading strategies outlined in this paper.

For us, the important message is that because of this wider swing in the so-called “pendulum”, allocators and investors alike are required to be more patient and maintain a longer-term view. In our estimation, it also requires a more thorough understanding of a manager’s process, style, and performance expectations, within the context of the market backdrop. While these are classic pillars in any asset allocation or manager due diligence exercise, we would argue that they become even more important going forward.