Investments: Analysis and Behavior

Chapter 6- Efficient Market

Hypothesis

©2008 McGraw-Hill/Irwin

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Learning Objectives

Understand the role of randomness and luck investment performance.

Identify the levels of market efficiency. Characterize the time series of stock returns. Avoid gamblers fallacy and data snooping problems. Recognize that price bubbles challenge market

efficiency.

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Short-term Speculation: Good, or Lucky? A coin-flipping contest

6 billion people pay $1 each to join Heads you stay in, tails you are out

After one round, 3 billion are still in After ten rounds, about 6 million are still in

Imagine, flipping 10 heads in a row. People begin to believe they are good at flipping, not lucky.

After 20 rounds, around 6,000 people left Locals become heroes! But half of these falter in the next round

After 25 rounds, 180 flippers are remain If the game stopped now, each would receive $33.3 million These people write books about their technique and strategy

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After the 30th round, only 6 remain Each would get $1 billion of the game stopped

It would probably take 32 rounds to end with a single winner The odds of flipping heads 32 times in a row is roughly one in six

billion. Is the winner good a flipping? Lucky?

There are millions of investors, analysts, portfolio managers, advisors, etc. participating in the investment process.

Many will appear to be top performers (at least for the short-term)

Who is lucky and who is good? How can you tell?

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Market Efficiency

The price for any given stock is effectively “fair” = the expected net present value of all future profits Discounted using a fair risk-adjusted return

Need Large number of buyers and sellers Free and readily available information Essentially identical securities Uninhibited trading

If there are bargains available, investors would bid up the price buying those stocks until the stock is no longer a bargain.

If markets are efficient, then it would be difficult for an investor to consistently beat the market.

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Efficient Market Hypothesis

EMH Security prices fully reflect all available information.

New information arrives in an independent and random fashion Current stock prices reflect all relevant risk and return information Investors rapidly adjust stock prices to reflect new information

Levels of Efficiency (based on Information) Weak-form: prices reflect all stock market information

Prices, volume, patterns, trading rules, etc. Semistrong-form: current prices reflect all public information

Accounting statements, economic activity, old news stories Strong-form: current prices reflect all public and private info

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Prices do react quickly! After the close of the stock market on Monday, April 18, 2005, Texas Instruments

announced that it beat Wall Street's expectations for the first quarter of 2005 and posted a profit of $411 million, which is 12 percent more than in the year-ago quarter. TI had been expected to post single-digit profit growth.

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Are Daily Returns Predictable?Prior Following

Date Open High Low Close Change % Day Day

A. Dow Jones Industrial Average Big Up Days

24-Jul-02 7698.5 8243.1 7489.5 8191.3 489.0 6.35% -1.06% -0.06%

29-Jul-02 8268.0 8749.1 8268.0 8711.9 447.5 5.41% 0.95% -0.37%

8-Sep-98 7964.9 8103.7 7779.0 8020.8 380.5 4.98% -0.55% -1.94%

16-Mar-00 10139.6 10716.2 10139.6 10630.6 499.2 4.93% 3.26% -0.33%

15-Oct-02 7883.2 8304.6 7883.2 8255.7 151.4 4.80% 0.35% -2.66%

28-Oct-97 7190.9 7553.6 6933.0 7498.3 337.1 4.71% -7.18% 0.11%

1-Oct-02 7593.0 7964.2 7558.4 7938.8 346.9 4.57% -1.42% -2.31%

24-Sep-01 8242.3 8733.4 8242.3 8603.9 368.1 4.47% -1.68% 0.65%

5-Apr-01 9527.2 9969.9 9527.2 9918.1 402.6 4.23% 0.31% -1.28%

11-Oct-02 7540.7 7919.6 7540.7 7850.3 316.3 4.20% 3.40% 0.35%

Averages 4.86% -0.36% -0.78%

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Prior Following

Date Open High Low Close Change % Day Day

B. Dow Jones Industrial Average Big Down Days

27-Oct-97 7608.3 7717.4 7150.1 7161.2 -554.2 -7.18% -1.69% 4.71%

17-Sep-01 9294.6 9294.6 8755.5 8920.7 -684.8 -7.13% 0.00% -0.19%

31-Aug-98 8079.0 8149.0 7517.7 7539.1 -512.6 -6.37% -1.40% 3.82%

14-Apr-00 10922.9 10922.9 10173.9 10305.8 -617.8 -5.66% -1.81% 2.69%

19-Jul-02 8356.7 8356.7 7940.8 8019.3 -390.2 -4.64% -1.56% -2.93%

20-Sep-01 8375.7 8711.4 8304.5 8376.2 -382.8 -4.37% -1.62% -1.68%

27-Aug-98 8377.9 8448.7 8062.2 8166.0 -357.4 -4.19% -0.92% -1.40%

12-Mar-01 10638.5 10638.6 10138.9 10208.3 -436.4 -4.10% -1.97% 0.81%

3-Sep-02 8659.3 8659.3 8282.9 8308.1 -355.4 -4.10% -0.09% 1.41%

27-Sep-00 7996.0 7997.1 7664.9 7701.5 -295.7 -3.70% 1.98% -1.42%

-5.14% -0.91% 0.58%

Note: Data are for the nine-year period from 7/1/97 to 12/31/05.

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A. DJIA Daily Returns

-10.00%

-5.00%

0.00%

5.00%

10.00%

15.00%

Date

C. Nasdaq Daily Returns

-10.00%

-5.00%

0.00%

5.00%

10.00%

15.00%

Date

Figure 6.3 Daily Returns Are Noisy and Random Around A Mean of Zero, from 1/1/97 to 12/31/05.

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Random Walks and Prediction

Random Walk Theory Stock prices movements do not follow any patterns

or trends Past price action cannot be used to predict future price

movements. Subsequent price changes represent arbitrary departures

from previous prices.

Random walk with a drift Stock prices do tend to increase, on average, over time.

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Yet, millions of people examine charts and search for patterns and trends.

The Human Brain is well suited to seeing patterns Even when the data is random and no pattern exists!

Gambler’s fallacy Popular, but erroneous, belief that some self-correcting process

impacts random events. After 5 fair coin flips of “heads” in a row, many people act as if they

believe the probably of a heads in the next flip is different from 50% Lottery players examine previous numbers picked. So do Keno players.

Data-Snooping Patterns may appear in random data if enough different tests are

examined. Much data is available and computers can quickly crunch it.

Back testing and out of sample tests can help determine whether a pattern may repeat in the future or is simply an artifact of the data.

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From Dogs to Fools Dogs of the Dow

Strategy identifies the 10 highest-dividend paying firms in the DJIA 1992 book, Beating the Dow by O’Higgins and Downes Buying the Dogs at the beginning of each year is shown to beat the

buy-and-hold strategy of just owning the 30 stocks in the Dow by over 4% per year.

Value-oriented strategy Dow Five

Buy the 5 lowest priced dogs Beats the Dow by 8% per year No basis in theory

Motley Fools’ adaptation Foolish Four: Of the Dow Five, throw-out the lowest price

stock and double-up on the second lowest price stock. Purported to beat the Dow by 12% per year Is the data tortured enough? Motley Fool eventually abandoned this strategy when it both

failed to perform well and other investors started trading against those following the strategy

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Investing in an Efficient Market Two investors are walking down the street when one

spots a $100 bill on the sidewalk. He points it out. The companion says, “It must not be a real $100 bill or someone would have already picked it up.” If markets are efficient, we should not bother to look for

bargains. However, if no one is looking for bargains, how can markets be efficient?

Studies show that, on average, mutual funds and investment newsletter writers do not beat their benchmark. Evidence for EMH

What should investors do if markets are efficient?

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Challenges to EMH

Excessive Volatility Why is the market so volatile? Dividends are not volatile at all.

Bubbles Dramatic increases and declines in the

stock market

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Figure 6.4 Real Stock Prices and Present Values of Subsequent Real Dividends

10

100

1000

10000

1860 1880 1900 1920 1940 1960 1980 2000 2020

Year

Real Stock Price (S&P 500)

PDV, Constant Discount

PDV, Interest

PDV,

Source: Robert Shiller, 2003, “From Efficient Market Theory to Behavioral Finance,” Journal of Economic Perspectives, 17(1), Figure 1.

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From January 2, 1985, at 11,543, the Nikkei 225 soared to a closing high of 38,916 on December 29, 1989. This represents a gain of 237.1% in the Nikkei over a 5-year

period, and a stunning 27.5% compound annual rate of return. Then, the bubble burst and the bottom fell out of the Japanese

equity market. Fifteen years after the Japanese market peak, in December, 2004, the Nikkei stood at 10,796. That’s 72.3% below the December, 1989 peak.

From a (split-adjusted) level of 125 on January 31, 1985, the Nasdaq 100 soared to 4,816.35 on March 24, 2000. This represents a 15 1/4-year return of 3,753.3%, and an

amazing compound return of 27.1% per year. Then the Nasdaq plunged, losing over 80% of its value by 2002.

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Figure 6.6 Will Post-crash Nasdaq 100 Valuations Languish For A Decade or More?

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

Year

Nas

daq

100

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

50,000

Nik

kei 2

25 Nasdaq 100

Nikkei 225

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Why might the market not be efficient? Investors make decisions influenced by

emotions and psychological biases. If large groups of investors become too

optimistic or pessimistic, they may move prices Investor mood

How investor mood can impact expectations…

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If prices reflect a dividend discount model:PV = D1 / (k – g)

But expectations become biased:E(P) = D1 / (k – E(g))

So prices can deviate from true value by:

)(

)(

gEk

gk

PV

PE

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Example: If the annual market return over a long period of time is

expected to be 12% and the long-term expected growth rate of stock market firms is 4%, the Dow Jones Industrial Average is fairly valued at 10,000. If Optimistic investors believe the long-term growth rate is 5%, how far would the DJIA be expected to fall?

The stock market should become over-valued as

The DJIA would be expected to rise to 1.14 × 10,000 = 11,400, or a 14% rise. However, it would also be 14% overvalued.

14.17

8

512

412

)(

)(

gEk

gk

PV

PE

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Can investment fraud occur in an efficient market? Microcap Fraud

Microcap stocks, or penny stocks, often trade as pink sheets on the OTC Bulletin Board

Low liquidity means the price can be susceptible to false press releases of exaggerations or lies, and “pump and dump” schemes.

Fraud on the Internet Easy place to spread false “news”

and “unbiased” opinion.

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Red Flags!

Assets Are Large But Revenues Are Small  Unusual Accounting Issues Thin Public Float SEC Trading Suspensions High Pressure Sales Tactics

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EMH The EMH is still hotly debated today.

In Support: Short-term prices are unpredictable Price adjust quickly and pretty accurately Professional investors don’t seem to beat the market, on

average. Against:

Market is too volatile Stock market bubbles exist Investor mood may drive prices away from fair value Investment fraud

The next chapter examine some interesting anomalies that also put the validity of the EMH into question