Download Chapter 06

Investments: Analysis
and Behavior
Chapter 6- Efficient Market
Hypothesis
©2008 McGraw-Hill/Irwin
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.
6-2
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



After 20 rounds, around 6,000 people left



Imagine, flipping 10 heads in a row.
People begin to believe they are good at flipping, not lucky.
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
6-3

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 shortterm)
Who is lucky and who is good? How can you tell?
6-4
Market Efficiency

The price for any given stock is effectively “fair”



Need






= the expected net present value of all future profits
Discounted using a fair risk-adjusted return
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.
6-5
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


Semistrong-form: current prices reflect all public information


Prices, volume, patterns, trading rules, etc.
Accounting statements, economic activity, old news stories
Strong-form: current prices reflect all public and private info
6-6
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.
6-7
Are Daily Returns Predictable?
Date
Open
High
Low
Close
Change
%
Prior
Following
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%
4.86%
-0.36%
-0.78%
Averages
6-8
Date
Open
High
Low
Close
Change
%
Prior
Following
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.
6-9
Figure 6.3 Daily Returns Are Noisy and Random Around A Mean of Zero,
from 1/1/97 to 12/31/05.
A. DJIA Daily Returns
15.00%
10.00%
5.00%
C. Nasdaq Daily Returns
0.00%
15.00%
-5.00%
10.00%
-10.00%
Date
5.00%
0.00%
-5.00%
-10.00%
Date
6-10
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.
6-11
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. 6-12
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
6-13
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.”


Studies show that, on average, mutual funds and
investment newsletter writers do not beat their
benchmark.


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?
Evidence for EMH
What should investors do if markets are efficient?
6-14
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
6-15
Figure 6.4 Real Stock Prices and Present Values of
Subsequent Real Dividends
Source: Robert Shiller, 2003, “From Efficient Market Theory to Behavioral Finance,” Journal
of Economic Perspectives, 17(1), Figure 1.
6-16

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.
6-17
5,000
4,500
4,000
50,000
45,000
40,000
3,500
3,000
2,500
2,000
1,500
35,000
30,000
25,000
20,000
15,000
1,000
500
0
10,000
5,000
0
1995
1997
1999
2001
2003
2005
2007
2009
Nikkei 225
Nasdaq 100
Figure 6.6 Will Post-crash Nasdaq 100 Valuations Languish For A Decade or
More?
Nasdaq 100
Nikkei 225
2011
Year
6-18
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…
6-19

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:
E ( P)
kg

PV
k  E(g )
6-20



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
E ( P)
kg
12  4 8


  1.14
PV
k  E ( g ) 12  5 7

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.
6-21
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.
6-22
Red Flags!





Assets Are Large But Revenues Are Small
Unusual Accounting Issues
Thin Public Float
SEC Trading Suspensions
High Pressure Sales Tactics
6-23
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
6-24