Is the Stock Market an "Efficient" Market?--Posner

The Dow Jones Industrial Average peaked at 14,200 on October 9, 2007, fell to 9,600 on November 4, 2008 (election day), kept falling, to 6,400 on March 6, 2009, and since then has risen sharply, to 8,100. (I have rounded to the nearest hundred. I use movements in the DJIA rather than in the S&P 500 because the DJIA is composed of heavily traded stocks and thus gives a clearer view of market-price changes.) What explains these gyrations? The housing bubble had already burst when the market peaked. Yet stocks of financial firms heavily invested in housing were flying high, and have now lost much of their value. The stock market was overpriced in October 2007, just as it had been at the peak of the dot-com bubble in the late 1990s, and on the eve the stock market crash of October 1929, and at other times as well. This raises the question whether and in what sense the stock market is an "efficient" market. It was Mark Twain who first, more than a century ago, advised investors to put all their eggs in one basket and watch the basket. His advice was picked up by businessmen like Andrew Carnegie and Bernard Baruch and became conventional investment wisdom. Modern finance theory demolished that conventional wisdom by showing that it is virtually impossible, certainly for the vast majority of investors, including professionals such as mutual fund managers, Wall Street gurus, securities analysts, and finance professors, to beat the market, in the sense of consistently identifying overpriced stocks to sell and underpriced ones to buy. (For a valuable collection of articles on this theme, see www.cxoadvisory.com/blog/internal/blog-analysts-experts/.) Much more sensible is a strategy of buying and holding a diversified portfolio of stocks (and other securities as well), thus minimizing trading costs and other transaction costs, along with variance, which investors who are risk averse, as most investors are, do not like. Even if the expected value of a particular stock is equal to the expected value of a diversified portfolio, the risk of being wiped out is much less if one holds a diversified portfolio than if one owns a single stock. Of course, some active traders (stock pickers or market timers) are lucky, just as some gamblers are, and earn supernormal returns from active trading. Others obtain supernormal returns in up markets by investing borrowed money (leverage)--and incur supernormal losses in down markets if they are investing with borrowed money, since the cost of that money is fixed, which is why investing with borrowed money yields supernormal returns if stock prices bought with the borrowed money are rising. More important, supernormal returns are possible for some investors as a matter of skill or sharp tactics when trading on private information is permitted (or done anyway), or when markets are illiquid or rigged, or when few analysts study the companies whose stock is traded. The difficulty of beating the market other than by luck or leverage or the market deficiencies just mentioned, whether by active trading of particular stocks believed to be overpriced or underpriced by the market or by trying to time market turns, suggests that when investors trading on public information--information that, by definition of "public," is equally accessible to all of them--will obtain only a normal profit. That is one definition of an efficient market: a market in which competition is so effective that it squeezes out economic rents, which is to say returns in excess of costs. There is good evidence that organized exchanges in mature economies are efficient in that sense, as most modern finance theorists believe. But how can their belief be squared with the frequency of investment bubbles? Investors in October 2007 may have had equal access to all available public information about banks and other firms, but they seem not to have drawn a correct inference from that information. Bubble behavior is exhibit number 1 to the claim by some behavioral economists that stock market investors often act irrationally. For example, buying in a rising market or selling in a falling one (both illustrating what is called "serial momentum" or "momentum trading") is said to illustrate "herding" behavior. I do not agree. Nor do I think investors should be criticized for the behavior that has led to the stock market gyrations that I mentioned at the outset. What is missing in the behavioral analysis is the distinction first made by the University of Chicago economist Frank Knight, in the 1920s, between calculable risk, that is, a risk to which an objective probability can be attached, and uncertainty, which is a risk to which such a probability cannot be attached. Insurance is based on calculable risks; an objective, quantitative estimate of the risk of an accident or other insured event enables the fixing of an insurance premium, a price equal to (if one ignores administrative costs) the expected cost of the loss insured against. The estimates of probable loss used to calculate insurance premiums are based primarily on past experience (frequencies), and if the future differs unpredictably the insurance company may incur windfall gains or losses. So there is some Knightian uncertainty even in insurance markets, but it is generally much less than in the stock market. A vast number of decisions that people make, including investors, are decisions under uncertainty in Knight's sense. When one has to choose between on the one hand marrying one's present girlfriend or boyfriend and on the other hand continuing to search for a "better" marriage partner, one cannot base the choice on a quantitative estimate of the probability that one choice will have better results than the other. A businessman who has to decide whether to invest in a project that will not yield revenues for several years is likewise making a decision under uncertainty because he cannot estimate the probabilities of many of the contingencies that, if they materialize, will make the project profitable or unprofitable. And an investor who decides to put more of his savings in the stock market, or shift some of his stock to an alternative investment, cannot estimate the probability that the price of the stock will rise or fall, and within what interval of time, and how far. He knows, moreover, that what moves stock prices is not the best estimate of future corporate profits as such, but the behavior of the investing public, which is influenced by other things besides beliefs concerning the future course of such profits. For example, when stock prices begin to fall, the market value of savings invested in the market falls and this may make cautious investors move their money into safer forms of saving to make sure they have enough protection against a rainy day--a decision that has little or nothing to do with predicting future stock prices. This precautionary motive has almost certainly been a factor in the steep fall of stock prices in the current economic downturn. The personal savings rate had plummeted in the early 2000s, and the housing collapse depleted the savings of many people, especially those whose principal investment was their house, so that when stock prices fell many of these people reduced their spending and increased their precautionary savings. This pushed down economic output, increased the rate of unemployment, reduced corporate profits, and so caused the stock market to fall even farther. But the impetus for the market decline, in this analysis, was not a judgment about corporate profits but a desire for safer savings. But what about stock market bubbles? The explanation may lie in the fact that under Knightian uncertainty, often the best, though not a good, predictor of the future is the immediate past. If there is no weather forecasting, probably the best guess as to tomorrow's weather is that it will be similar to today's. If stock prices are rising, this suggests that something is happening to make people think that corporate profits will be greater in the foreseeable future. One might counter by asking why, if investors are expecting stock prices to continue rising, prices don't immediately jump to their peak value. But there is some inertia in trading, and, more important, no one can know the market peak in advance; for if everyone knew that, no one would sell at the current price or buy at the peak price, and trading would come to a halt. So suppose that in 2007 you had money to invest. You could buy a CD, a Treasury security, mutual-fund shares, etc. Why would you think that the fact that stock prices had been rising made them a poor investment, so that rather than buy stocks you should sell them short? Yet I believe that the Federal Reserve should have lanced the housing bubble no later than 2006 by raising short-term interest rates (which would have pushed up long-term rates as well by increasing the borrowing costs of banks and other financial intermediaries and thus the rates they would have to charge for lending their borrowed capital), and if this did not burst the stock market bubble (the bubble that reached its maximum expansion in October 2007) to lance that bubble as well, by increasing margin requirements. But how can this suggestion be squared with my argument that buying stock (or, I would add, houses) in a bubble is rational behavior? The answer is that an individual investor in making an investment decision does not consider the effect of the decision on the economy as a whole; that is not his business, and anyway an individual investment decision is unlikely to have economy-wide effects. Protecting the economy is the business of government. Even if the Federal Reserve could not have spotted the housing or credit or stock market bubbles before they burst, it knew or should have known that these booms could be bubbles and that if so they would burst and when they burst they could bring down the economy. This made the expected cost of the booms high, even though that cost could not be quantified (another example of Knightian uncertainty)--high enough to justify intervention, or, at the very least, the formulation of contingency plans to deal with worst-case scenarios.

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