Jack Bogle, Oligopsony, and Capitalism (Part I)

ack Bogle, 89, founder of Vanguard, and creator of the first truly successful index funds, passed away last week. When a daring pioneer passes on to what we wistfully refer to as "the other side", I find it only natural that we engage in a retrospective. Jack's ideas deeply impacted the markets, and tens of millions of investors, making this conversation indispensable. The words I feel obliged to write are not mere pleasantries. Beforehand, I must extend my deepest sympathies to Jack's family. His life's ambition of reducing fees for retail investors was a truly laudable one.

While I admire Jack's spirit, for many years I've descried the unfolding pernicious effects of passivity on market macrostructure. I feel quite the estranged skeptic amongst a cacophony of voices, all avowing in ritualistic cant their righteous attestation, "high investment fees are usury." I am impelled to stand in solemn discord, and thus I'll argue why the panacea of passive investing is illusory. Moreover, I'll explore whether passive strategies and crony capitalism can together achieve "escape velocity", whereby the critical eye of short-sellers and anti-management proxy voters are decimated. In a nutshell, these are my planks:

1. the wisdom of the crowd is the genetic code governing capital allocation
2. passivation centralizes decision making, thereby reducing "crowd" size
3. fewer, larger funds leads toward capital market oligopsony
4. oligopsony tempts collusion/bribery between boards/execs and indexers
5. myopic annual fee minimization denatures proxy voting into rubber stamping
6. a reflexive process of insider enrichment destroys long-term value creation
7. at its core, this is the so-called "agency problem"—little skin in the game
8. ultimately, portfolio homogeneity exacerbates systemic crash risk/extent

In this series of posts, I'll proceed to deal with each of these issues. Finally, I'll wrap up with why I'm ultimately hopeful about the future of the markets. In this first post of the series, we'll cover points one through three.

Emergent Wisdom

That capitalism thrives due to the wisdom of the crowd is a given. We take for granted that companies prosper when demand for their products suffices to generate profit levels commensurate with the risks undertaken by their owners. Millions of consumers voting with their feet (or their voices) form the very grist of evolutionary selection pressure upon firms. Yet, to presume that selection pressure begins and ends with the consumer is to commit a crucial error. Consumers and capital are equally precious to the entrepreneur.

When evaluating business selection pressures, we must appreciate the deep symmetries between consumer demand, and investment demand. The cult of passive investing has a profound cognitive dissonance lurking in its treatments of the consumer versus the capitalist. For the consumer, they assiduously defend the power of the wisdom of the crowd. Whereas, for the capitalist, the passive investor seemingly kneels before the altar of market efficiency.

While I could plummet down a rabbit hole while excoriating passive investors for being so naïve as to embrace market efficiency, I'll refrain. Flaying economists—for their abject disregard of the physics behind information processing—is a delightful past-time, however it's also unnecessary. Rather, let's scrutinize how centralization (via passivity) of buy/sell decisions impacts the wisdom of market price discovery.

Oligopsony, a term seldom encountered (unless you're an economist), is central to my opening argument. First, two analogies:

In other words, a monopsony is a market with a single buyer, and an oligopsony is a market with a handful of buyers. We all know that monopoly can be evil (although, I highly recommend reading the late Albert O. Hirschman's brilliant Exit, Voice, and Loyalty to appreciate the subtle complexities of the relationship between monopoly and the public good).

To understand the potential evils of oligopsony, we need look no further than American agribusiness. That ADM, Bunge, Cargill, and Dreyfus have a near-stranglehold on the purchase of many agricultural commodities is well understood and published. Farmers have long denounced the effects, think tanks have illuminated the perils of our current agricultural market structure in voluminous detail, etc.

When a cartel-like structure forms (either explicitly, or implicitly via emergent self-organization, where the few firms' respective salespeople indirectly determine each others' prices through trial-and-error, and thereby converge on similar prices), the market can skew very far from optimality. In agriculture, this phenomenon unfolded as ridiculously high margins—particularly for bulk commodities—on the part of the so-called ABCD oligopsonists. These windfalls coincide with deeply strained financial conditions for the farmers.

The lens of supply and demand is too seldom utilized to gaze upon the capital markets. I suspect this has its roots in the general perception that capital markets are separate and distinct from the capital formation process. Investment banks' intermediation of new issuance undeniably clouds our understanding of a capital market's raison d'être. Even upon seeing through market microstructure, we're still confronted with capital structures and 10-K footnotes so baroque as to evade all but the most persistent inquisitor. It's a perniciously illusive construct that greatly benefits Wall Street's sell-side machine. Colloquially, it's our market-cum-casino. Yet, brush away the subterfuge, and we encounter an immanently skillful—if stealthy—allocator of capital.

Publicly traded firms are, in effect, machines for transforming the wealth of investors into (hopefully) profitable services, from which some class of people derive benefit via commerce. Ultimately, the profits from the endeavor return to the investors as dividends, coupons, principal payments, etc. The question we must ask is: when a capital market becomes an oligopsony, how is this process altered?

This is a deep question. We're at a pivotal tick in the charts where nearly half of all US equities are owned via passive indexation. To most, this is a crowning triumph of main street over Wall Street. While I'm an outsider with no skin in this game, I'm appalled by the seeming complacency with a few relatively flimsy arguments for why passivity is both safe and desirable. Next, we must undertake a brief survey of market history.

The Road to Oligopsony

In the early days, securities markets were legalized casinos. People bought shares and derivatives from brokers and stock jobbers on the streets, or in coffee shops. Later on, as the markets grew, market structure became more formalized. Exchanges formed, brokerages opened their doors, and eventually investors became accustomed to the presence of intermediaries. Nevertheless, the wisdom—or, insanity—of the crowd was dominant.

Humans are ill adapted to simultaneously analyze data across a multitude of dimensions (one way to "visualize" the market is as a hyper-dimensional space, where time is one dimension, and the price of N securities form N additional dimensions). Our inability to reason about high-dimensional data renders markets indecipherable. There was thus a pressing need for summary statistics to reduce cognitive load, and thereby help humans quickly grok the overall state of the capital markets. Hence, the index was conceived.

Indexation allowed people to track the market as a whole—or, equivalently, an aggregate of all securities within a particular industrial sector—using a single number. This shorthand enabled rapid reasoning about the markets with sole reliance on the fast, associative-heuristic part of the mind, i.e., what Kahneman calls System 1. Simultaneously, though, indexation opened the door to lazy decision processes where hasty generalizations are deduced from the arithmetic mean. While too subtle to be discerned, let alone opposed, this was the first raid on the wisdom of the crowd.

As the twentieth century advanced, industrial complexity mushroomed. Investors grew overwhelmed by the attendant explosion in listed securities, thereby rendering fundamental analysis difficult (particularly as cognitive overload from fundamental analysis forced increasingly difficult trade-offs between examination of the macroeconomic forest versus scrutinizing microeconomic chaparral).

Consequently, we saw the advent of investment trusts and mutual funds. These structures allowed a small group of securities pickers to amortize their costs across a larger capital base than any individual could amass, thereby enabling research otherwise uneconomic. What remained nearly invisible was the launching of a reflexive process whereby cost reduction begets smaller crowds, which begets worse capital allocation decisions, which begets worse returns, which begets increasing demand for low fee structures, which begets worse capital allocations, seemingly ad infinitum.

While, ostensibly, investors have a choice among many mutual funds, that perspective belies Wall Street stock pickers' near-constant social interaction—either directly in their daily lives, or minimally via the FT and Wall Street Journal. This socialization, even at the dawn of the 20th century, led to memes and socio-financial feedback loops, whereby certain industries and individual securities were "hot". In this sense, Ben Hunt's notion of the narrative machine is quite valid.

This inconspicuously manifested as further curtailed wisdom of the crowds. While many thousands of funds were born (and, each of these had the pick of hundreds of thousands of discrete issues of stocks, bonds, funds, and derivatives), the portfolios thereby constructed were bound to have considerable correlation (similarity) to each other due to the small number of plausible investment themes, and the widespread socialization of investment ideas. The small number of themes follows naturally from the constraint that salable investment products must, as with any product, possess a readily digestible pitch.

Consequently, a dynamic was activated whereby investment could be funneled through the minds of orders of magnitude fewer investors than was the case when investors individually performed their own due diligence. Since expert investors have the same cognitive constraints as the individual investors they supplanted, in principle this constituted a net reduction in the cognitive load applied to the problem of allocation. Thereby, a trade-off emerged between crowd wisdom input and aggregate resources invested into capital allocation decisions. I.e., what previously were the individual allocation decisions of thousands, or even millions of individual investors, were now delegated to small groups of experts who could supplant millions of distributed decisions with a few orders of magnitude less decisions per year, thereby freeing individual investors from all but a handful of decisions per decade (regarding whom to entrust with their capital).

Fortuitously, this dynamic was counteracted by three negative feedback loops: 1) the advent of middle class retirement, 2) the development of expertise, and 3) the application of systematic information processing to the markets. Whether middle class retirement has been a boon to the markets, or a corrupting force is hotly contested. It's a big enough topic to warrant an entire series of posts, so I'll simply acknowledge the dynamic and move on.

The great miracle—the negative feedback loop that has staved off the regressive dynamic of reduced crowd wisdom—was of course a combination of all three factors I listed above. Let's focus now on the development of expertise (largely an exercise in training Kahneman's System 1), and computerized analysis. This small army of investment advisors dedicated their lives to the analysis of markets and securities. In doing so, they expended untold cognitive energy to two ends: 1) better allocation decisions in the present; and, more subtly, 2) convex future cognitive returns. This second point is cardinal: building on the shoulders of their own past works, their minds adapted. Thereby, imperceptibly-fast System 1 obtained heuristic understanding that previously entailed painstaking System 2 cognitive effort.

When human heuristics were combined with systematic information processing, which humans are ill-suited to perform, the result was pure symbiosis. As computers and computer science advanced, the process self-selected for brilliant minds who could funnel their innate intelligence into coaction with the computers. With time, this small army of traders gained untold advantages in terms of heuristic reasoning abilities—backed by vast new data analysis powers conjured through computerization. That said, heuristics, analysis, and insight must not be conflated. The key point is reducing cognitive load afforded this trading elite an advantage. They could make fast decisions on the basis of heuristics, rather than going through meticulous analysis. Moreover, algorithms previously written to analyze interesting problems could be run repeatedly.

It's worth noting there is a hidden fragility to this structure. By virtue of the human lifespan, a strict limit is placed on how many market cycles can be trained into a trader's System 1 heuristics. This limitation has been partially counteracted by computers. However, deterministic algorithms are not perfectly suited to this task (as answering novel problems is many orders of magnitude more expensive than answering problems for which algorithms were previously developed). There is a corollary to Kahneman's availability heuristic buried here: when given the choice between writing an algorithm to provide an exact answer, and utilizing existing analysis that answers a related question, there is a strong bias towards the existing analysis due to its actionability. Thus, much like Kahneman's System 1, algorithmic analysis is a twin-edged sword that must be utilized with care.

It is undeniable that high salaries and convex risk-reward perennially attract the best and brightest to trading—after all, it is the most vexing game in all the world. Nevertheless, intelligence is not characterized by a power law. The brightest are not exponentially brighter than the average. Thus, replacement of millions of average humans' decisions with those of a small number of highly facile investors is not a recipe by which superior allocation decisions are made in the aggregate. For, it is exceedingly unlikely that reducing aggregate cognitive load—in the name of cost minimization—could ever be advantageous from the perspective of optimal capital allocation. Bayesian learners are by definition always wrong about nearly everything. However, in the aggregate, there are many things about which we are, curiously, correct. The key is to appreciate the direct linkage to the law of large numbers: the smaller the crowd, the greater odds the collective wisdom of said crowd will be unwise.

Before I close out this section, let me stress that the inverse is not necessarily true. Clearly, large crowds can be unwise for long periods of time, as the run-ups to 1837, 1929, 2000, 2008, etc. taught us. Nevertheless, reducing the number of people performing due diligence and subsequently voting with their wallets intrinsically reduces the likelihood that prudent capital allocations will be made.

Myoptimisation

Returning to market history, we have two closely related chapters yet to cover. First, there is the mid-1970s with Jack Bogle's advent of indexed mutual funds. At first, these appeared to be an utter flop. But, Jack was if nothing else a persistent man. Eventually, Vanguard would grow exponentially.

The second major catalyst came quite a few years later with the advent of SPDR. The magical combination of indexation, mutualized ownership of a broad portfolio of underlying securities (along with a dual structure of authorized participants who trade the underlying securities on behalf of the ETF and have the authority adjust the float, and the secondary market where retail investors and institutions can purchase them) truly revolutionized the industry.

For professional investors, this enabled great efficiency in expressing trades against large baskets of related securities (i.e., indices). The capability to transact in significant quantity, and with considerable liquidity (we'll have to defer decoupling risks for another post), without the complexity of structuring dozens or hundreds of trades in individual securities, was transformative.

For retail investors, index mutual funds and ETFs promised extremely low fees by cutting out the active managers—supplanting them with a portfolio constructed from the definition of an index and a weighting function. It was verily another lurch forward on the vexing, interminable course toward the wholesale algorithmization of humanity.

Now, to be fair, I must acknowledge that there are presently more passive mutual funds and ETFs than underlying equities. However, as with active mutual funds, there are far fewer strategies than there are passive funds. Thus, we can agglomerate all of them into at most a few hundred thematic classes: countries, continents, industrial sectors, value/growth, small-/mid-/large-cap, sovereign/IG/junk bonds, major indices, currency pairs, commodity ETNs, popular derivatives, levered/unlevered, etc. Naturally, the entities who define the indices and weighting functions are all deeply embedded within the financial narrative game. Thus, we can rest assured that—a few mavericks aside—most of them are basing decisions on the same common knowledge. Hence, there will be considerable overlap.

Not only has delegating portfolio allocation to ETFs further reduced the size of our proverbial crowd, the funds have themselves—in many cases—delegated a key decision: how to define the index itself. Those that define the indices are consummate insiders. Naturally, groups steeped in the common narrative create thematically related indices of strong correlation.

A tech ETF eschewing Google would strike most as patently absurd (unless it were thematically proscribed, e.g., an Asian tech ETF). Were an individual investor to deem Facebook deeply overvalued, it's nonetheless likely their retirement portfolio would express the opposite position. To the average retirement saver, this cognitive dissonance is obscured by layers of abstraction: a year-targeted retirement fund in turn allocates a percentage of its AUM to an ETF, which, in turn, allocates a market cap weighted share of its AUM to Facebook. In this example, expressing a contrary opinion is seldom considered, because the position is lost beneath the subterfuge of the asset manager's marketing materials. Moreover, when the individual is aware of the divergence, expressing that opinion financially is onerous: either a margin account to outright short, or an options account to express via puts is required. Neither is particularly feasible due to margin restrictions on retirement accounts. And, expression via options is generally excluded due to the need for significant AUM before options-based hedging is possible (not to mention the need for a high degree of conviction on catalyst and timing to make the θ, ε, ν, and ρ risks worthwhile).

The barriers to entry for individual investors to express their idiosyncratic views suffice to promote pack behavior. Most investors thus accede to a closely-hewing ETF or passive mutual fund. It's worth noting the strong parallels to the formation of political parties—and the concomitant "pulling the big lever" effect. Due diligence is hard; deferring to a small troop of experts is easy and superficially "efficient". In politics, cohesion is the catalyst for gaining advantage over a dispersed enemy. However, in contrast, there are few significant advantages to cohesion of investment opinion. To the contrary, cohesion distorts crucial capital allocation feedback loops, which are grounded in the mechanism of price discovery via the performance of a massive distributed poll.

Moreover, the intrinsic passivity of index investing eviscerates the time-sensitive feedback loops that an arbitrageur would rely upon. In recent years, we've witnessed extreme levels of volatility selling that have engendered a sense of unwarranted complacency. When considered under the lens of demographics, to some degree this makes sense. We have a large cohort heading into retirement soon. People nearing retirement age have a strong bias towards maximal portfolio contributions. Until the initial crack in the volatility markets last February, expecting to arb out an imbalance when indexation is a forcing function driving α towards zero, and correlations and β toward 1, was a challenge that many would have been dissuaded from. Approximately half the US equity market is blindly allocating capital based upon an index definition, and a weight function. Unyielding linear behavior is the very antithesis of a reasoned approach to investing. It is dumb money writ large.

In the interest of keeping this series digestible, I will stop here. In the next part of this series, I'll continue the discussion of modern market structure, indexation, and ETFs. The key focus will be on oligopsony, and how it impairs the feedback loop between capital allocation and boardroom decisions.