Debunking the Myth of Market Efficiency
Sixty years after it was first formulated, the core tenet of the efficient market hypothesis (EMH) — that stock prices fully reflect all available information — is still considered gospel truth in many quarters: Investors can only expect to earn a normal rate of return because prices adjust before investors can trade on fresh information.
Hypothesizing about Markets
Another key postulate of the EMH is investor rationality. That is, investors will automatically adjust their valuation estimates to every new piece of information. The EMH acknowledges that individuals can independently deviate from rational behavior. But a third assumption of the theory is that irrationally optimistic investors are just as common as irrationally pessimistic ones and thus “prices would likely rise in a manner consistent with market efficiency,” as the authors of Corporate Finance explain.
While arguing that such irrationality is invariably offset may seem a little too tidy and unrealistic, a fourth EMH assumption holds that irrational amateurs will face rational and intuitive professionals who will take advantage of any temporary mispricing through arbitrage.
A fifth fundamental inference is that of perfect competition. No investor can control any segment of the market and extract monopoly profits for lengthy periods.
As a consequence of the above, there are no patterns in share price changes and prices at all times express true value. Prices follow a random walk, and no investor can consistently make money from trend-following, momentum-buying, or any other investment style.
To anyone with experience in the public markets, these axioms — perfect information, investor rationality, an irrationality-offsetting mechanism, systematic arbitrage, and perfect competition — are, at best, farfetched. But as sociologist Raymond Boudon observed, “people often have good reason to believe in dubious or false ideas,” which can be reinforced by flawless arguments based on conjectures. One particular belief Boudon flagged is that of homo economicus as a rational being, “almost God’s equal.”
What makes the EMH so appealing is the premise that markets are optimal capital allocators and wealth creators. That capitalism trumps planned economies does not validate the theory, however. Here, Max Weber’s core research principle applies: “Statements of fact are one thing, statements of value another, and any confusing of the two is impermissible.” This is where the EMH erred.
Deconstructing Market Efficiency
Let’s review why the EMH’s economic interpretation is questionable.
1. Information Accuracy
To start with, the notion of perfect information ignores the fact that information can be manipulated, inaccurate, misleading, fraudulent, or simply difficult or impossible to understand.
Rigging markets is not a new technique. Creative accounting and outright fraud are common, particularly during bubbles and market corrections. The dot-com and telecom manias led to various scandals. The latest euphoria orchestrated by central banks’ zero interest-rate policies brought on Wirecard and FTX, among other excesses.
In the days of fake news and instant messaging, the claim that market prices contain all available data fails to take into consideration the risk of misrepresentation.
2. Information Access
Market prices can only reflect perfect information if all investors access the same data at the same time. In the United Kingdom, for instance, a fifth of public takeovers are preceded by suspicious share price movements. Insider trading is rife and has always been.
In an April 1985 study of all takeovers, mergers, and leveraged buyouts from the year before, BusinessWeek magazine found that the stock price rose in 72% of the cases before the transaction was publicly announced. As Drexel CEO Fred Joseph put it: “the arbs [arbitrageurs] have perfected the technique of obtaining inside information.”
Disparate data access does not solely affect stock and bond exchanges. Four years ago, the Bank of England and US Federal Reserve discovered that some traders and hedge funds received policymakers’ statements up to 10 seconds before they were broadcast.
3. Information Processing
Sophisticated investors analyze information in a methodical, rigorous, and speedy way. Algorithmic tools give institutions an unassailable edge against less experienced investors.
The success of quantitative trading at Jim Simons’s Renaissance Technologies and other hedge funds demonstrates that superior data analysis can help beat the market consistently, even if not all the time.
Mass investor confusion is a real phenomenon. Investors mistook the Chinese company Zoom Technologies with the newly listed Zoom Video in 2019, sending the former’s stock soaring 70000%. A year later, as the world went into lockdown, it happened again. These are isolated anecdotes to be sure, but given such basic mistakes, is it credible to posit that stock prices accurately reflect all available information?
A major shortcoming of the EMH is that it offers a narrow definition of market efficiency, focusing wholly on data availability. This oversimplification fails to acknowledge that the market is more than just a reflection of data flows. Other factors can create friction.
1. Trade Execution
Once investors access, process, and analyze information, they must be able to execute trades seamlessly. Market makers and professional traders may have this ability, but individual investors do not. The front-running scandal at Robinhood, when customer order data was shared with high-frequency traders (HFTs), is just one example of the uneven playing field.
This sort of practice is nothing new. In The Man Who Solved the Market, Gregory Zuckerman explains how in the mid-1990s, “shady traders were taking advantage” of Simons’s hard work by “watching [his fund] Medallion’s trades.” Michael Lewis described how HFTs speed up trade execution in Flash Boys. They deploy computer-driven trading robots, access private venues called “dark pools” to hide transactions, move physically closer to public exchanges to trade ahead of other participants, and pay intermediaries for early access to information — all to artfully maintain an unfair advantage.
Superfast connections and algorithmic trading should democratize access to stock exchanges, improve liquidity, and lower spreads not rig markets by enabling front-running.
2. Price Setting
According to the EMH, price changes are statistically independent from one another. They occur as new data emerges; there are no trends for investors to identify. The market’s response to new data includes no investor overreaction or delay. Prices always reflect all available information.
Benoit Mandelbrot’s pre-EMH research demonstrated that stock prices were characterized by concentration and long-range dependence. New information moved markets, but so did momentum and other factors unrelated to data flows. Investors could make money from trend-following, momentum, seasonality, and other strategies. This contradicts the EMH, and further research into persistent return anomalies supports the conclusion.
As Warren Buffett observed in his coin-flipping article about superinvestors in Graham-and-Doddsville, it is possible to consistently beat the market.
3. Investor Behavior
Investor rationality maybe the weakest of the EMH’s assumptions.
Behavioral economists have long maintained that investors are emotional. Robert Shiller demonstrated that stock prices are more volatile than would be expected if investors were strictly rational. Investors tend to overreact to unexpected news.
That the actions of irrational investors are somehow neutralized by arbitrageurs, or by other irrational investors taking opposite positions, has always seemed like wishful thinking. That the price-setting process is devoid of speculation is equally unsound as theory. If speculation may explain price movements in cryptocurrency markets or for meme stocks, with no underlying cash flows or corroborative performance data, why couldn’t it play a role in broader market activity?
Verification and Falsification
Behaviorists and EMH advocates fiercely debate market efficiency. Eugene Fama, one of the EMH’s pioneers, has acknowledged that the theory cannot be fully tested. “It’s not completely true,” he said. “No models are completely true.” Partly for that reason, he defined three types of efficiency: a weak form, based on historical trends; a semi-strong form, which includes all public information; and a strong form whose price trends also include private information.
The strong form has long been discredited, if only due to rampant insider trading and instances of market manipulation by sophisticated investors to the detriment of less experienced punters — witness recent excesses with SPAC structures.
The semi-strong form never looked credible either given Mandelbrot’s research and Buffett’s superinvestors. Market prices do not solely depend on information.
Investor rationality is the core assumption behind many economic theories, but philosopher Karl Popper explained that such “theories . . . are never empirically verifiable.” They cannot be considered true until proven in a universal and unconditional manner, yet they can be falsified at any moment.
For Popper, the most uncertain theories tend, by necessity, to be the most immune to criticism. The iterative process of falsification and verification is endless and leads to intermediate conclusions. The problem is knowing when enough contradictions have accumulated to abandon a theory.
Financial markets are faulty, but just how faulty is not clear. Unless and until it is incontrovertibly falsified, the EMH will continue to prevail. Recognizing its detractors’ weak standing, Fama stated that “there is no behavioral asset pricing model that can be tested front to back.” The same is true, of course, of his own market efficiency model.
Markets are at times efficient, at other times inefficient. They may even be both concurrently. This is what proponents of a hybrid version seek to determine. Andrew Lo’s theory of adaptive markets, for instance, blends aspects of both market efficiency and behaviorism.
If they are neither solely informational nor fully behavioral, markets are also unlikely to be both exclusively. Their complexity transcends disciplines and cannot be entirely modeled out. But this does not contravene the idea that it is possible to beat the market repeatedly through sheer luck — in a sort of coin-flipping contest, with skills and experience — using algorithmic or alternative methods, or through inside information and other criminal means.
Although it appears purely random, there is order within the chaos of financial markets. The main challenge for investors remains how to devise an investment style that consistently, even if not constantly, outperforms.
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5 thoughts on “Debunking the Myth of Market Efficiency”
The collapse of SVB seems like another example of how markets really aren’t as efficient as some academic claim. After all, the unrealized loss on the HTM portfolio was right there in the 10-K of the publicly-held holdco.
So many holes in this argument. Bottom line: 95% of active funds underperform indices. Whoever has some seeming edge can’t exploit it for a long term record.
Fusion Analysis has enabled the average investor to beat the active funds with indexing. Yes, there is the Fusion book for the seasoned pro, but it is not recommended for the vast majority. Why? Indexing is effortless and low cost
Thanks for your comment, John.
Unfortunately, just because the majority of active fund managers underperform indices in no way proves that markets are efficient.
There are many reasons that could explain underperformance: negligence, incompetence, arrogance, emotional behavior, lack of effective analytical tools, failure to come up with an adequate investment style, failure to adapt one’s investment style once markets have caught on, etc.
As I wrote in the very last sentence, just because markets are inefficient does not mean that all investors will be able to devise an investment style that consistently, even if not constantly, outperforms. Most will fail. In that sense, we seem partly to be in agreement.
Great article showing the sorry state of finance as religious battle between rationalists and behaviorists. Actually, they are just representing the two sides of the same coin. Thus, they should stop confusing the world and start collaborating constructively on the unifying Adaptive Markets Hypothesis (AMH). What is hindering them? Probably the opposite, a total lack of adaptive capabilities. From history the future of the extremists is predestined: “It is not the strongest of the species nor the most intelligent that survives. It is the one that is most adaptable to change.”
“The main challenge for investors remains how to devise an investment style that consistently, even if not constantly, outperforms.”
How about trend following managed futures CTAs, systematically exploiting the “order within the chaos of financial markets” in the long-term, mixed with passive indexing? Isn’t this one of the best solutions, consistently outperforming long-term at least risk-adjusted and science-based on both main parts of the AMH, EMH and Behavioural Finance?
Trend following has been providing exactly that already for decades on average of its benchmark index SG Trend after costs. And is available for all retail investors through mutual funds and ETFs. Mixed with passive equity index ETFs, trend followers significantly reduces their volatility risk, particularly in crashes, due to non- or negative correlation, respectively, without reducing returns.
This was researched well and stated by the Harvard finance professor John Lintner already in 1983 and holds until today. And simple pure trend following is at the core of the realistic Adaptive Markets Hypothesis by Andrew Lo. Therefore, he democratises this approach already since 2010 through AlphaSimplex at low flatfees for ethical reasons.
Thus, even John Bogle – as a dyed-in-the-wool indexer – recognised this investment approach as promising financial innovation, following his own one. Also Eugene Fama confirmed this in his view in the conversation, linked here, as being his “biggest problem of all”.
Therefore, I expect this to be the next major investment story after index ETFs, supplementing them well for increasingly volatile times going forward for a long time to come after the turn around of interest rates. Accordingly, the last year was already one of the best years for trend following with the SG Trend gaining 27 percent. This was due to many exploitable trends all over in commodities, bonds, interest rates and currencies. In times of rising interest rates such volatile trends may prevail for decades.
What do you think about it, and why didn’t you mention this as an obvious solution to current theoretical and practical challenges? Actually, I am successfully investing in it for 25 years. Even a few years earlier than in index funds/ETFs, which became available in Germany only after trend following. You can find more details on this in my whitepaper with all references: https://www.democratic-alpha.com/whitepaper
You are right to point out that trend-following is a popular technique to derive anomaly returns. I did briefly refer to it in the article, in particular when referring to Mandelbrot’s research and with the link to Baltussen et al’s paper on Global Factor Premiums.
Apologies for not expanding on it further. Bear in mind that the purpose of the article was primarily to debunk the EMH rather than suggest investment strategies to active investors. And, in fewer than 1800 words, it was quite a challenge!