As we have seen in previous chapters, expectations play a role in many sectors of the economy, having an important impact on the behavior of economic agents. In this chapter we look at the theory of rational expectations that attempts to explain how these important expectations are formed.

I.  Role of Expectations

Expectations play a role in consumer behavior, firm behavior, financial markets, and the behavior of financial institutions. Here are some examples:

Expectations about inflation affect

• interest rates in the bond market by shifting bond demand and supply curves
• Fed actions, such as the FOMC's vote on a federal funds rate target
• the AS curve and workers wage demands may shift the AS curve
• the movement of foreign exchange rates

• the term structure of interest rates, i.e. the slope of the yield curve
• the movement of foreign exchange rates
• bank behavior, such as the ER/D ratio

• the risk structure of interest rates
• bond supply and interest rates
• firm investment and AD

Expectations about income affect

• money demand
• consumer spending and AD
• bond demand and asset demand in general

II. Theory of Rational Expectations

Prior to the 1960s, most economists assumed that economic agents has adaptive expectations. That is, expectations about a variable were based on past values of that variable, and they changed slowly over time.

However, there are a couple of problems with this model of expectations:

• a variable may be affected by many other variables, so people will likely use all relevant data in forming an expectation about a variable.
• expectations can change very quickly if the environment also experiences sudden, large changes.

There is a strong incentive to form rational expectations: Better expectations mean better decisions. Banks and firms make more profit, consumers are better off, and the Fed does a better job at achieving the nation's economic goals.

Not all expectations will be rational all of the time. People will not always take the time to gather all information to make a decision. People may not be aware of all the information that is available. Nonetheless, for important decisions, rational expectations are a sound assumption for the economy as a whole.

If rational expectations are the norm for our economy as a whole, then we can expect

• Changes in the behavior of a variable will lead to changes in how we predict this variable.  If the yield curve were to stop sloping up and be flat most of the time, we would expect predictions about the slope of the yield curve to incorporate this development.
• Forecast errors of predictions (the actual value - the predicted value) will average zero over time, but are not predictable.  While any one prediction of the yield curve slope has some error, we do not know the error ahead of time, or we would adjust our forecast.  Over time we sometimes underpredict the slope, we sometimes overpredict the slope but on average these errors cancel out.

III. Efficient Markets Theory

Applying the theory of rational expectations to financial markets specifically, we get the efficient markets theory.
The efficient markets theory assumes that asset prices (particularly stock prices) reflect all available information.

For example, Microsoft's stock price on 5/1/02 was about $52 . Under the efficient markets theory, the share price of $52 reflects all past relevant info about Microsoft (such as their profits, sales, litigation, etc) as well as forecasts about future earnings, sales, market share, new products, etc. People who buy and sell Microsoft stock have an incentive to use all of this information to make a profit, so the price set by buyers and sellers will reflect this information.

Furthermore, under the efficient markets theory, a security's return always reverts to some equilibrium return that reflects expected future earnings and risks. Why?

• If Microsoft stock is earning an abnormally high return, people will buy the stock, bidding up the price. The higher price will drive down the return to some equilibrium level.
• If Microsoft stock is earning an abnormally low return, people will sell the stock, driving down its price. The lower price causes the return to rise to some equilibrium level.

A strong version of the efficient markets theory states that security prices are always a correct reflection of the market fundamentals. The fundamentals are variables that directly impact the future cash flow of a security and include information about the company, its product, and economic conditions.

Evidence on Efficient Markets

One key implication of the efficients markets theory is that over time it will be almost impossible to "beat the market." This means that we should not see any one group or person earning returns in the stock market that are consistently above average stock returns (the market return). Since prices already reflect all available information, using this information to predict stock prices will be worthless, so investment advisors using fancy formulas to forecast future stock prices should do no better than average over time. Is this true?  The evidence is mixed.

Evidence in favor of efficient markets

The is a large body of research that examines the returns of stock mutual funds over time to see if these expertly managed portfolios outperform the market. Well, they do not. In any given year over half of all mutual fund returns will be below the average stock return. Over time investors are better off trying to match the market average. This suggests that professional management does not give anyone an "edge" in trying to get superior returns. This is what we would expect if stock prices already reflect all available information. Furthermore, mutual funds that do well in one year typically do not do well in subsequent years. There are exceptions, but overall mutual funds may get lucky in one year, but the luck does not hold out in later years. In fact, we would expect a top-rated mutual fund in 2001 to get an influx of cash from new investors in 2002, which will drag down its returns.

If stock prices reflect all available information, then there is nothing to use to predict future stock prices. That is, if markets are efficient, stock prices are unpredictable or a random walk in statistical terms. So look for past price patterns to predict future prices should be a worthless exercise. Using past prices to predict future prices is known as technical analysis. Studies of technical analysts show that over time they do not outperform the market. In fact they often do worse because they are constantly trading stocks, which generates costly commissions.

Evidence against efficient markets

Starting in the 1970s, researchers discovered some return patterns in the stock market that are inconsistent with efficiency. These inconsistencies are referred to as anomalies, and provide some evidence that the stock market is not perfectly efficient.

The small-firm effect literature has found that small firm stocks have earned higher returns over long periods of time, even when adjusted for risk. Many explanations for this have been offered, but none are truly satisfactory. In the late 1990s, large firm stocks actually did much better than small firm stocks. This size effect has become smaller over time, but if markets are efficient, it should have disappeared very quickly as investors tried to profit from this information.

The January effect is the tendency for stocks to post large returns in January for long periods of time. While this can be explained by sell-offs in December for tax reasons, this effect should have disappeared as tax-exempt institutions (like pension funds) tried to profit from this anomaly. This effect has gotten smaller over time, but it has persisted too long to be consistent with efficient prices.

There are actually many other effects out there: day-of-the-week effect (better returns on Friday, worse on Monday), a weather effect (better returns on sunny days), and more. All of them have been too persistent to be consistent with efficiency.  However, many of these anomalies are also too small to be profitable once you take into account the transactions costs of trading.

There is also a body of research above the over-reaction of stock prices to news (good or bad) and the excess volatility of the stock market. Studies show the stock prices pluge in response to bad earnings reports, only to creep back upward the following week. Stock prices fluctuate much more than the fundamentals behind them fluctuate.

So there is evidence against perfect efficiency, but let's keep some perspective. The overwhelming weight of evidence suggests that earning above-average returns is very difficult. Even with some of the anonmalies mentioned, the potential to profit from them is very small.

Implications for investment strategy

The chief implication from efficient markets is to stop trying to beat the market. It does not work and you just generate a lot of trading costs that drag down your returns. Even if markets are not perfectly efficient, they are close enough so that it is very difficult for the average person or even financial advisors to generate above-average returns over time. Yes there are exceptions, but in any time period, some investors will be lucky and some unlucky.

So what's an investor to do? The best time-proven strategy is to buy-and-hold a well-diversified portfolio to minimize taxes, trading costs, and achieve the long-run average return for the stock market. One way to do this is with the index mutual funds out there. Index funds seek to match the return of a stock market index (like the S&P 500) by holding a portfolio identical to the index. The Vanguard 500 was the first index fund, started back in 1976. At the time many made fun of the objective "to be average," but the fund has been a consistent performer and now there are hundreds of S&P 500 index funds along with index funds using other stock market indices.

The lesson: by earning average returns over time you will do better than most mutual funds out there.

The Crash of 1987: A Rational Response?

On October 19, 1987, the stock market plunged with what was, at the time, the largest one-day point loss in history for the Dow Jones Industrial Average (over 500 points, or 20% of the index value). Could such a large one-day loss be reconciled with efficient markets?

The were several factors justifying lower stock prices at the time: widening federal budget and trade deficits, legislation against corporate takeovers, rising inflation, and a falling dollar. However, none of these fundamentals experienced such a dramatic one-day change as to precipitate Black Monday.

Most economists conclude that this episode is evidence that investor psychology plays a role in stock prices along with the fundamentals, and that the strong version of the efficient markets theory is not correct.

FYI: Related Links

A Random Walk Down Wall Street by Burton Malkiel. This links you to the book's site on Amazon.com. An accessible book that covers investing approaches and academic theories on the efficient market hypothesis. This book was written by a former Princeton Prof. who also invested hands-on in the market. It's a bestseller, written for the public and available in paperback.