The Efficient Markets Hypothesis Timothy R. Mayes, Ph.D. FIN 3600: Chapter 7.

The Efficient Markets Hypothesis

Timothy R. Mayes, Ph.D.FIN 3600: Chapter 7

Active or Passive Management?

“Investors, as a group, can do no better than the market, because collectively they are the market. Most investors trail the market because they are burdened by commissions and fund expenses.” —Jonathan Clements, the Wall Street Journal, June 17, 1997

“Fees paid for active management are not a good deal for investors, and they are beginning to realize it.” —Michael Kostoff, executive director, The Advisory Board, a Washington-based market research firm. InvestmentNews, February 8, 1999

“When you layer on big fees and high turnover, you’re really starting in a deep hole, one that most managers can’t dig their way out of. Costs really do matter.” — George “Gus” Sauter, Manager of the Vanguard S&P 500 Index Fund

Active or Passive Management?

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Definition of Efficient Markets

An efficient capital market is a market that is efficient in processing information.

We are talking about an “informationally efficient” market, as opposed to a “transactionally efficient” market. In other words, we mean that the market quickly and correctly adjusts to new information.

In an informationally efficient market, the prices of securities observed at any time are based on “correct” evaluation of all information available at that time.

Therefore, in an efficient market, prices immediately and fully reflect available information.

Definition of Efficient Markets (cont.)

Professor Eugene Fama, who coined the phrase “efficient markets”, defined market efficiency as follows: "In an efficient market, competition among the many intelligent

participants leads to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future. In other words, in an efficient market at any point in time the actual price of a security will be a good estimate of its intrinsic value."

History

Prior to the 1950’s it was generally believed that the use of fundamental or technical approaches could “beat the market” (though technical analysis has always been seen as something akin to voodoo).

In the 1950’s and 1960’s studies began to provide evidence against this view.

In particular, researchers found that stock price changes (not prices themselves) followed a “random walk.”

They also found that stock prices reacted to new information almost instantly, not gradually as had been believed.

The Efficient Markets Hypothesis

The Efficient Markets Hypothesis (EMH) is made up of three progressively stronger forms: Weak Form Semi-strong Form Strong Form

The EMH Graphically

In this diagram, the circles represent the amount of information that each form of the EMH includes.

Note that the weak form covers the least amount of information, and the strong form covers all information.

Also note that each successive form includes the previous ones.

Strong Form

Semi-Strong

Weak Form

All information, public and private All public information

All historical prices and returns

The Weak Form

The weak form of the EMH says that past prices, volume, and other market statistics provide no information that can be used to predict future prices.

If stock price changes are random, then past prices cannot be used to forecast future prices.

Price changes should be random because it is information that drives these changes, and information arrives randomly.

Prices should change very quickly and to the correct level when new information arrives (see next slide).

This form of the EMH, if correct, repudiates technical analysis. Most research supports the notion that the markets are weak form

efficient.

Price Adjustment with New Information

At 10AM EST, the U.S. Supreme Court refused to hear an appeal from MSFT regarding its anti-trust case. The stock immediately dropped. This example, one of hundreds available every day, illustrates that prices adjust extremely rapidly to new information.

But, did the price adjust correctly? Only time will tell, but it does seem that over the next hour the market is searching for the correct level.

Notes: Each bar represents high, low, and close for one-minute. Each solid gridline represents the top of an hour, and each dotted gridline represents a half-hour.

Tests of the Weak Form

Serial correlations. Runs tests. Filter rules. Relative strength tests. Many studies have been done, and nearly all

support weak form efficiency, though there have been a few anomalous results.

Serial Correlations

The following chart shows the relationship (there is none) between S&P 500 returns each month and the returns from the previous month. Data are from Feb. 1950 to Sept. 2001.

Note that the R2 is virtually 0 which means that knowing last month’s return does you no good in predicting this month’s return.

Also, notice that the trend line is virtually flat (slope = 0.008207, t-statistic = 0.2029, not even close to significant)

The correlation coefficient for this data set is 0.82%

Serial Correlations (cont.)

Unlagged vs One-month Lagged S&P 500 Returns

y = 0.008207x + 0.007451

R2 = 0.000067

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One-month Lagged Returns

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The Semi-strong Form

The semi-strong form says that prices fully reflect all publicly available information and expectations about the future.

This suggests that prices adjust very rapidly to new information, and that old information cannot be used to earn superior returns.

The semi-strong form, if correct, repudiates fundamental analysis.

Most studies find that the markets are reasonably efficient in this sense, but the evidence is somewhat mixed.

Tests of the Semi-strong Form

Event Studies Stock splits Earnings announcements Analysts recommendations

Cross-Sectional Return Prediction Firm size BV/MV P/E

Analysts’ Performance

This chart from the Wall Street Journal, shows that when analysts issue sell recommendations, those stocks frequently outperform those with buy or hold ratings. If the professionals can’t get it right, who can?

Mutual Fund Performance

Generally, most academic studies have found that mutual funds do not consistently outperform their benchmarks, especially after adjusting for risk and fees.

Even choosing only past best performing funds (say, 5-star funds by Morningstar) is of little help. A study by Blake and Morey finds that 5-star funds don’t significantly outperform 3- and 4-star funds over time.

However, it does seem that you can “weed out” the bad funds (1- and 2-stars). Funds that have performed badly in the past seem to continually perform badly in the future.

The Strong Form

The strong form says that prices fully reflect all information, whether publicly available or not.

Even the knowledge of material, non-public information cannot be used to earn superior results.

Most studies have found that the markets are not efficient in this sense.

Tests of the Strong Form

Corporate Insiders. Specialists. Mutual Funds. Studies have shown that insiders and specialists

often earn excessive profits, but mutual funds (and other professionally managed funds) do not.

In fact, in most years, around 85% of all mutual funds underperform the market.

Anomalies

Anomalies are unexplained empirical results that contradict the EMH: The Size effect. The “Incredible” January Effect. P/E Effect. Day of the Week (Monday Effect).

The Size Effect

Beginning in the early 1980’s a number of studies found that the stocks of small firms typically outperform (on a risk-adjusted basis) the stocks of large firms.

This is even true among the large-capitalization stocks within the S&P 500. The smaller (but still large) stocks tend to outperform the really large ones.

The “Incredible” January Effect

Stock returns appear to be higher in January than in other months of the year.

This may be related to the size effect since it is mostly small firms that outperform in January.

It may also be related to end of year tax selling.

The P/E Effect

It has been found that portfolios of “low P/E” stocks generally outperform portfolios of “high P/E” stocks.

This may be related to the size effect since there is a high correlation between the stock price and the P/E.

It may be that buying low P/E stocks is essentially the same as buying small company stocks.

The Day of the Week Effect

Based on daily stock prices from 1963 to 1985 Keim found that returns are higher on Fridays and lower on Mondays than should be expected.

This is partly due to the fact that Monday returns actually reflect the entire Friday close to Monday close time period (weekend plus Monday), rather than just one day.

Moreover, after the stock market crash in 1987, this effect disappeared completely and Monday became the best performing day of the week between 1989 and 1998.

Summary of Tests of the EMH

Weak form is supported, so technical analysis cannot consistently outperform the market.

Semi-strong form is mostly supported , so fundamental analysis cannot consistently outperform the market.

Strong form is generally not supported. If you have secret (“insider”) information, you CAN use it to earn excess returns on a consistent basis.

Ultimately, most believe that the market is very efficient, though not perfectly efficient. It is unlikely that any system of analysis could consistently and significantly beat the market (adjusted for costs and risk) over the long run.