Does the most recent stock quote reflect all knowable details? Does fair market value inherently predict a security’s prospects, like a biological gene that contains a compressed DNA code?
To test whether analysis improves predictions, in 1988, The Wall Street Journal sponsored a contest between professional investors and another team who threw darts randomly. The pros beat the dart throwers, but only 51 times out of a hundred, a slim advantage that fades into statistical insignificance. The conundrum persists and the fight goes on.
Battle lines are drawn
Although the discussion dates to 19th-century French mathematicians, the modern opening salvo was fired in 1970 by economist Eugene Fama, who concluded that a lucky investor might enjoy short-term profits but, over a longer period, could not infallibly beat the market. Of course, there will always be outliers in the averages who win and lose big, but the majority will hover near the middle. Yet Fama’s hypothesis assumes that all relevant information is freely and widely available — a very broad assumption indeed!
Burton Malkiel then went on in 1973 to popularize the random walk theory in a still-perennial best-seller. He argued that assets tend to stroll along randomly, a mathematical term for determining the location of a point. It is also known as a drunkard’s walk. Theoretically, each point (or security) must move independently from other points.
Fama, Malkiel, and other colleagues laid out models for three degrees of efficiency and their implications:
- Weak — All past information is known and priced in. Technical analysis is useless, as buying and selling patterns have no meaning.
- Semi-strong — As new public information emerges, prices adjust fast, so both technical and fundamental analyses are useless predictors.
- Strong — All information is incorporated into the price, even private knowledge of insiders. Every sieve has leaks. If insider trading rules operated seamlessly, the strong form would not exist.
Lumping together these various levels, Fama quipped, “I’d compare stock pickers to astrologers, but I don’t want to bad-mouth astrologers.” He meant that ultimately, all that you can predict is that market movements are unpredictable. By the time information is out there, it is too late to exploit it. For example, once COVID-19 revolutionized remote working, Zoom solutions rapidly became old news.
Why does it matter?
If markets are less efficient and ripe for arbitrage, superior information goes a long way toward picking winners. A vast industry of financial advice has been predicated on the concept that better information and more skillful analysis justify the hefty fees active managers charge.
On the other side, a smaller but mushrooming industry of passive investment, including index and exchange-traded funds, has developed out of the rival efficient market theories. A lot of money and marketing are riding on these opposing underlying principles.
The schools of thought have gone beyond the investment industry and permeated economic policy. During the era of deregulation in the 1980s, efficient market theories served to discourage intervention in financial sectors on the basis that the market was already capable of self-correcting.
A spectrum of efficiency
Critics of efficiency theory note that a small handful of star investors, such as Warren Buffett, John Templeton, and Paul Tudor Jones, seem able to beat the averages. Market bubbles are an even more significant anomaly. Investors exhibit behavioral biases, like herding and following one another. Remember that as recently as early 2020, markets were reaching new highs, even as some already realized COVID-19 had started spreading.
It need not be all or nothing. Different markets exhibit different grades of efficiency, driven by degrees of information. For example, large cap stocks and countries with stricter disclosure rules are more widely understood. Information is disseminated and short trading is executed faster, increasing liquidity. Efficiency also increases if a security can be analyzed by a few computer variables, like treasuries or derivatives.
Your investment adviser can explain further how efficiency theories directly impact your choice of investments.
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