Eugene Fama: efficient markets, factors and why our site is a public experiment
Fama argued that prices already contain all information, then found the exceptions himself. The idea, the factors, the critics, and how a live public scoreboard of sixty bots tests it.
Who he is
Eugene Fama (born 1939) is an economist at the University of Chicago and a winner of the Nobel Prize in 2013, which he shared with Robert Shiller and Lars Peter Hansen. It is a notable choice: Fama and Shiller reached almost opposite conclusions about how rational prices are, and were honoured together for their work on how asset prices behave.
Fama's name is attached to two ideas that pull in different directions: the efficient market hypothesis and the three-factor model, which describes patterns that the first idea would not expect.
The core ideas
In a 1970 review Fama set out the efficient market hypothesis. If many informed people compete to profit from new information, prices will move to reflect it very quickly, and so the price at any time already includes what is known. In its weak form, past prices carry no information that can be used to make a profit. In the strong form, even private information is already in the price. The practical consequence is that it is very hard to beat the market consistently, after costs, by picking stocks or timing the market.
The statement is not that prices are always right, but that you cannot easily tell when they are wrong. Fama also stressed that the hypothesis cannot be tested alone: any test also needs a model of what return is fair for the risk taken.
The factors
In the early 1990s Fama and Kenneth French showed that average returns of US stocks could not be explained by market risk alone. Small companies had earned more than large ones, and cheap companies, with a high ratio of book value to price, had earned more than expensive ones. These became two factors added to the market: size and value. Later work added profitability and investment, and others, such as Carhart, added momentum, the tendency of recent winners to keep winning for some months.
Fama and French explained the extra returns as compensation for risk: small and cheap companies are more likely to be in trouble. Other economists, including Shiller, argued that the same patterns are signs of human error: investors overpay for exciting growth and underprice dull companies. The data cannot settle the argument, and both sides agree that the patterns have been real over long periods and can disappear for a decade.
What six current portfolios show
The table tests the idea in a modest way. If markets were perfectly efficient and difficult to beat, we would expect professionals to hold many stocks and to trade little. Some do: Bridgewater has 990 positions, 30% of them in index funds. But the rest are far from that: Ackman and Pabrai hold 10 and 4 stocks, Berkshire's ten largest holdings are 91.0% of its book, and Duquesne opens or closes about a quarter of its book every quarter. These investors act as if they can find mispriced assets.
Whether they do is a separate question that a filing cannot answer, because it shows what they hold and not what they earn. The famous investors who are studied are a selected group, those who succeeded, and for each there are many who did not.
Six real portfolios side by side, from the latest filing of each investor (Form 13F, US-listed stocks only). Effective positions is the number of equal-sized positions that would be as concentrated as the real portfolio: one divided by the sum of the squared shares. Opened or closed is the average over the four quarters of half the combined share of positions that were opened or closed.
| Investor | Reported stocks | Positions | Effective positions | Largest position | Ten largest | Opened or closed per quarter |
|---|---|---|---|---|---|---|
| Warren Buffett | $299.3 billion | 26 | 8.1 | 22.0% | 91.0% | 1.0% |
| Ray Dalio | $24.4 billion | 990 | 23.9 | 16.3% | 42.1% | 5.8% |
| Bill Ackman | $13.7 billion | 10 | 6.9 | 17.6% | 100.0% | 7.0% |
| Stanley Druckenmiller | $5.2 billion | 94 | 22.2 | 16.6% | 46.3% | 23.8% |
| Seth Klarman | $5.4 billion | 23 | 13.4 | 16.5% | 74.9% | 9.5% |
| Mohnish Pabrai | $0.3 billion | 4 | 2.9 | 43.3% | 100.0% | 4.4% |
Where it is challenged
Behavioural economists point to bubbles, such as the technology boom of 1999 and 2000, as evidence that prices can be far from reasonable value for years. Fama replies that no one can reliably identify a bubble in advance, and the fact that prices fell later does not show that they were wrong when set. Evidence on factors has also weakened: after they were published, some of the premiums became smaller, and the value factor in the US had a very long period of underperformance in the 2010s.
Defenders of active management add that markets need some active investors to keep prices informative, so efficiency is not a fixed fact but an equilibrium.
What to take from it
Treat a claim of beating the market with scepticism, including your own. Look at costs, because in an efficient market they are the main thing you can control. If you are interested in factors, understand that they are long-term tendencies with long bad periods, not guarantees. And judge any strategy by a record that is visible, public and not selected afterwards.
That last point is the reason this site exists in its current form.
Where it meets our bots
Our site is a public test of this debate. The reference bot is the market itself, and sixty bots in three sections try to do better by various rules, with their trades and costs open to anyone. Several of them are Fama's factors in mechanical form: the factor rotation bot chooses between growth, value, small companies and calm stocks, the low-volatility bot buys the twenty calmest stocks, and the momentum bot buys the ten strongest stocks of the year. We do not claim they will win. The accounts are virtual, nothing is replaced afterwards, and a loss stays visible.
The guides below explain how each rule works and where it can fail.
Related strategy guides
Factor rotation: growth, value, small caps or low volatility
Low-volatility stocks: the twenty calmest
Momentum stocks: the ten strongest of the year
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