How Efficient Is the Market, Really? Challenging the Chicago Hypotheses
In 2008 Warren Buffett issued a public challenge to the industry he most despised: hedge funds. Charging its clients 2% of assets under management plus 20% of any profits, Buffett wagered none of them could beat the annual return of the S&P 500. That bet was accepted, and ten years later the token wager of one million dollars was duly paid to the charity of Buffett’s choice.
Below is a graph depicting the results of the participating funds against the returns of an S&P 500 Index:
While it is true that the period in question featured an historical bull market, reaching back into the data and the history of major market participants reveals that the same would have been true at almost any point in the last forty years. Only a handful of investors, a literal handful, have been able to beat the market for their clients in the long run after fees and transaction costs are considered. Buffett, himself on that list, is so confident in the superiority of investing in broad-based index funds that he is said to be leaving the majority of his estate in them for his wife.
Other wealthy investors have taken note, with the share of assets under hedge fund management falling over the past five years.
While the commissions and fees hedge funds charge are large, what explains the basic inability of the average fund, staffed by ivy league quants doing cutting edge analysis running state of the art software, to significantly beat the market over the long run?
The answer, at its core, is the Efficient Market Hypothesis.
In the words of its author, Chicago School economist Eugene Fama (1970), the Efficient Market Hypothesis (EMH) is the belief that “prices reflect all available market information.” The implication being that, if they didn’t, arbitrage opportunities would arise, and prices would be corrected by those large investors with the resources to identify and make such corrections. The focus of the theory, therefore, is on information and its impact on prices.
EMH makes four basic assumptions: rationality, risk aversion, responsiveness to new information, and some amount of randomly distributed error (aka Malkiel’s “Random Walk”). Further, it takes three generally accepted forms:
- Weak-Form Efficient: above market returns cannot be gained from past market data (aka: technical analysis), but can be had from some kinds of fundamental analysis.
- Semi-Strong-Form Efficient: prices reflect all publicly available information. Prices will only change with new information, the emergence of which is assumed to be more or less random (thereby negating any prospect of above market returns via fundamental analysis).
- Strong-form Efficient: even with access to insider information an investor cannot beat the market.
Immediately, one can see that the strong-form of the EMH cannot possibly be true. Insider trading is illegal for a reason, and deals like Berkshire’s recent purchase of a large stake in videogame company Activision immediately before it was announced the company would be acquired by Microsoft raise eyebrows.
Between the weak and semi-strong forms, however, there is a lot of gray area. And many economists since the 1980s, including the Yale’s Robert Shiller and Chicago’s Richard Thaler, have made arguably the largest contributions of their careers studying the various ways in which markets apparently misbehave according to the various forms of the EMH.
To take a few examples, seasonal effects defy even the weak form of the EMH. The so-called Santa Clause rally is perhaps the best known of these phenomenon. Regardless of the wider macroeconomic conditions, market momentum, or exogenous risks, investing strictly on the basis of calendar dates, from the last five trading days in December through the first of the new year, has yielded a return 75% of the time. From a statistical standpoint, this is improbable, though several rather mundane facts may explain the anomaly: equities are generally at a cyclically lower level to start December due to tax reasons, professional traders being on vacation makes for lighter volume and fewer short sellers, and purchases in anticipation of another observed historical tendency, the January Effect.
In his analysis of P/E ratios, Shiller provides possibly the strongest evidence against the semi-strong-form EMH:
What he found was that buying and holding companies with relatively lower P/E ratios over the long-term produced the highest returns over those periods – something fundamental analysis and projections of future earnings could contribute to optimizing.
As pioneers in behavioral and narrative economics, both Thaler and Shiller also believe that the stories we tell ourselves about the stock market matter – how much, they can’t quantify. So, too, that systemic biases in thinking, such as the herd effect and hot hand fallacy, can drive market action in ways EMH would not predict – such as the 1990s IPO tech bubble, the rise of the cryptoverse, the implosion of LTCM, or the London Whale.
As far as bubbles go, Shiller correctly forecast both the tech bust in the late 1990s and the ticking time bomb in the housing market in the mid-2000s. But it is worth noting that while in retrospect everyone admits prices of mortgage backed securities were mispriced in accordance with their actual level of risk for several years in the mid-2000s, it was impossible to convince anyone of that at the time. Indeed, Thaler admits that while bubbles exist, we can really only prove they were bubbles after the fact. Afterall, there were plenty of buyers in every case, and who was anyone to say for certain that the future wasn’t going to be radically different from the past? Or that buying equities whose prices were rising wasn’t rational and efficient, value being subjective? Afterall, what is the value of something if not what amount it trades for between informed market participants freely exchanging?
Under such circumstances, an investor who thought they had identified such an inefficiency in the market and sought to profit from it by going short might wind up running out of money before the market ran out of enthusiasm: as with George Soros in the 1990s and tech.
Shorting being both risky and expensive, in such circumstances the great irony is that the rational thing to do for the average participant from a game theoretical standpoint is to ape the market and go along for the ride – hopefully using their self-awareness of actual risk levels to jump ship at some point before the crash.
It seems clear that between a combination of momentum trading, innovative strategies, superior analysis, high frequency trading for momentary and infinitesimal price arbitraging opportunities, and guessing correctly at future trends, can lead some firms to obtain above market returns. However, once fees and expenses are considered, the actual return to investors has been below the market average. Furthermore, virtually no funds or managers are able to sustain above market returns over the long run.
There have, of course, been periods where this was not true. The first decade of the 2000s as well as the ten years between 1965-1975 would have seen buyers of the S&P 500 index suffer a slight loss, while investor at the most successful funds of their time would have shown a positive return.
All things considered, for the average person planning for retirement, assuming they have neither the time or training to do the level of due diligence and analysis required for making superior individual stock selections, they really have been best off buying and holding broad based index funds rather than trusting to expensive, and often wrong, “experts.”
Whether or not this will continue to be true over the next several years, only time will tell.
As George Bragues argued in the QJAE in 2014, the data clearly reveals markets behave irrationally at times with respect to prices, earnings, dividends, acquisitions, et cetera; however, the market is not irrational either in that it is gradually self-correcting, bubbles are difficult to spot, and even more difficult to time.
Building on Shostak’s critique of Markowitz’s Modern Portfolio Theory, what this means for the efficient Austrian portfolio will be the subject of another discussion.