FNCE 4070: FINANCIAL MARKETS
AND INSTITUTIONS
Lecture 3: The Role of Expectations in
Financial Markets
How Expectations Shape
Financial Asset Prices.
The Efficient
Market Hypothesis
(Eugene Fama).
Where is this Financial Center?
Canary Wharf
The Role of Expectations
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Expectations play a very important role in all
aspects of life.
In financial markets expectations play an equally
important role. The behavior of what we observe
today in these markets is often driven by what
we expect will happen in the future.
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An expected political upheaval or civil unrest in oil
producing countries will increase the current (spot)
price of crude oil.
An expected increase in United States interest rates
relative to the U.K. will raise the rate of return on U.S.
dollars above the rate of return on British, leading to
an appreciation of the (spot) U.S. dollar against the
pound.
The Role of Expectations
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Additionally, many theoretical models in the financial
economics literature assume a relationship between
the current value of a financial instrument and
expectations about the future.
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For example, the dividend discount model assumes that
the current price of a certain common stock is the
discounted value (i.e., present value) of all expected future
dividend payments.
Gordon “Growth Model” based on future series of dividends
Market Price of a Stock (P) = D/(k – G), where:
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P = Present value of future dividends
D = Expected dividend 1 year from now
k = Required rate of return for an equity investor in the market
G = Expected annual growth rate in dividends
http://www.ultimatecalculators.com/constant_growth_model_calculator.html
Approximating Expectations
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However, one of the most critical aspects of
expectations is that they are unobservable.
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One approach to this issue has been to model how
market participants form expectations.
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Adaptive, Rational Expectations, Behavioral Finance (which
looks at the emotions ,irrational decision-making, and biases
that can come into play in setting asset prices; thus,
integrating both economics and psychology).
A second approach to “approximate” expectations is through
the use of survey data. In a typical survey, representative
market participants are questioned about their subjective
forecasts about the future value of a particular economic (e.g.,
GDP, unemployment) or financial variable (corporate
earnings).
The assumption is that the aggregate measure of
individual expectations should give a reasonable
proxy for `the' market's expectation.
How are Market “Expectations”
Formed? Adaptive Model
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Prior to the 1960s, most economists (and thus
economic models) assumed that market participants
formed adaptive expectations about the future, or
that:
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Market expectations about a variable were based primarily
on past values of that variable, and
These expectations changed slowly over time.
This approach undoubtedly reflected the “relatively stable”
environment of the early post World War II period, 1945 –
late 1950s. (see series of post WW II slides).
Post War (WWII) Interest Rate
Environment: 1945 - 1960
Post War (WW II)Interest Rate
Environment: 1945 - 1960
Post War (WWII) Exchange Rate
Environment: GPB Against the USD
Post War (WWII) Exchange Rate
Environment: JPY Against the USD
Problems with the Adaptive Model
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There were, however, potential problems with the
post WWII adaptive model of expectations:
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(1) A particular variable could easily be affected by many
other variables (not just the variable itself). Thus, financial
market participants are likely use all relevant data in
forming an expectation about a variable.
Perhaps more importantly:
 (1) By the 1970s, the economic and financial environment
began to experience sudden and dramatic swings.
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Change in U.S. monetary policy, demise of Bretton Woods (fixed
exchange rates) and formation of OPEC.
(2) As a result, we realized that expectations could change
very quickly.
Abrupt Change in 1970s/1980s in the
Environment Affecting Expectations
Inflation Environment in the 1970s
The 1970s -80s: A New Problem
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In the 1970’s, global
inflation became the major
economic issue for
industrial countries.
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The inflation of this period
was attributed to cost push
“supply shocks” to the
global economy.
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Two distinct inflation peaks:
1973/74 and 1980/81.
Especially oil.
As a result, many central
banks turned their attention
to inflation and some to the
use of inflation targets as a
macro economic goal.
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Beginning with New Zealand
in March 1980.
Inflation in Industrial
Countries, % per year
The Result of the Changing
Environment on U.S. Interest Rates
Volatility of Short Term Interest Rates
in the Late 1970s Though the 1980s
Changing Exchange Rate Environment;
The Japanese Yen: 1966 - 1979
Changing Exchange Rate Environment;
The British Pound: 1966 - 1979
Rational Expectations Model
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A second approach to financial market expectations,
called rational expectations, took hold in the 1960s.
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According to the rational expectations model, market
participants form expectations using all available
information (not just past information and not just the
variable itself).
Model also assumed that new information is
constantly being introduced to the market.
The rational expectations model, in turn, became a
bridge to “efficient markets theory (hypothesis).”
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The efficient markets theory assumes that asset prices
reflect all available information (events) that directly impact
on the future cash flow of a security (i.e., a financial asset).
Eugene Fama and The Efficient Market
Hypothesis
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According to Eugene Fama (see Appendix 1), who is
regarded as the originator of the efficient market
hypothesis:
“In an efficient market, competition among many
intelligent participants leads to a situation where,
at any point in time, the actual prices of securities
already reflects the effects of information based
on events that have:
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(1) already occurred [i.e., in the past], and events,
(2) as of now [i.e., in the present], and events
(3) the market expects to take place in the future. [i.e.,
what it anticipates]”
Source: Eugene F. Fama, "Random Walks in Stock
Market Prices," Financial Analysts Journal,
September/October 1965
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Illustrating The Role of Expectation
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Thus, according to Fama in an efficient market,
financial asset prices reflect the best knowledge of the
past, the present and predictions (anticipations) of the
future.
Important Questions:
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What happens when something unanticipated occurs and how
quickly do asset prices adjust?
 (1) How does the market react if the market is efficient?
 (2) How does the market react if the market is inefficient?
What happens when something anticipated occurs?
 (1) How does an efficient market react to anticipated events?
 (2) How does an inefficient market react to anticipated events?
Next four slides illustrate possible answers to these
questions.
Unanticipated “Favorable” Event
Efficient Market: Prices
would adjust up very
quickly at the time of the
announcement and
stabilize
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P
Inefficient Market: Prices
would drift upward for
some time following the
event
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Event Time
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P
Event Time
Example: Unanticipated “Favorable”
Event
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Walmart announced profits and sales which exceeded
analysts forecasts before the market opened on May 18,
2012
Unanticipated “Unfavorable” Event
Efficient Market: Prices
would adjust down very
quickly at the time of the
announcement and
stabilize
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P
Inefficient Market: Prices
would drift downward for
some time following the
event
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Event Time
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P
Event Time
Example: Unanticipated
“Unfavorable” Event
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JPMorgan announced a $2 billion dollar trading loss
before the market opened on Friday, May 11, 2012
Anticipated “Favorable” Event
Efficient Market: Prices
would drift up for some
time before the event and
then stabilize
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P
Inefficient Market: Prices
would drift up for some
time before the event and
continue up after
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Event Time
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P
Event Time
Anticipated “Unfavorable” Event
Efficient Market: Prices
would drift down for some
time before the event and
then stabilize
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P
Inefficient Market: Prices
would drift down for some
time before the event and
continue down after
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Event Time
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P
Event Time
Krispy Kreme and
the Efficient Market Theory
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Founded in 1937 (in Winston-Salem, NC) , the company went
public on April 5, 2000 and traded on NASDAQ (eventually listing
on the NYSE on May 17, 2001).
By 2004, the company was selling over 7.5 million doughnuts a
day.
Earnings announcement due on Monday, November 22, 2004 for
the three months ending October 31, 2004 (Announcement prior
to the opening on the NYSE).
 Stock had closed at $11.50 the previous Friday.
 Analysts anticipated earnings of 13 cents per share
 Instead, the company announced its first quarterly loss (of 5
cents a share) since going public in 2000.
Since announced earnings were not in line with market
expectations, what do you think happened to Krispy Kreme stock
and how quickly did it react?
Krispy Kreme: November 22, 2004; Reaction
to Unanticipated “Unfavorable” Event
Nike Reacts to an Unanticipated
“Unfavorable” Event
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On Thursday, November 18, 2004, near the close of the market (just
before 4:00) the company announced that the company’s co-founder
Philip H. Knight was stepping down as president and chief executive
officer of the company.
Conclusions from the Efficient
Market Hypothesis
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If markets are efficient, anticipated events have
already been discounted in asset prices.
If markets are efficient, financial asset prices will
adjust quickly to new and unanticipated events
(including data, news, speeches).
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Any unexploited profit opportunities (i.e., a situation in
which an investor can earn a higher than normal
return) will quickly disappear as market participants
adjust prices in accordance with the new event.
Thus, it is impossible to beat (or do better than) the
market with respect to any financial asset.
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Essentially your return will be no better than what the market,
or, a particular security returns.
Issues Surrounding the Efficient
Market Hypothesis
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How efficient are financial markets in terms or
assimilating new information into asset prices?
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Industrial country financial markets (especially the
large financial markets) appear to be very efficient.
Developing country financial market prices react more
slowly to information.
Even in industrial country markets, are there situations
when a market acts inefficiently?
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See Appendix 2 for possible examples.
Additionally, what news appears to be most
important in affecting asset prices?
How Efficient are Equity Markets?
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Studies suggest that equity prices adjust
within 1 to 15 minutes upon receiving
information.
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Dann, Mayers, and Raab (1977), Patell and
Wolfson (1984), Jennings and Starks (1985)
Conclusion: Most researchers generally agree
that equity markets are reasonably efficient,
however, debate is kept alive by the search
for and discovery of market anomalies (see
Appendix 2)
How Efficient are Foreign
Exchange and Bond Markets?
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Studies suggest that foreign exchange
markets (for major currency pairs) reacts
very quickly to news.
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Ederington and Lee (1993, 1995):
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Found that exchange rates (U.S. Dollar/German
Mark exchange rate study) reacted after about 10
seconds of scheduled macroeconomic news
releases and are complete after another 30
seconds.
This study also found similar reaction times in the
U.S. Treasury bond markets
The Role of Expectations in
Specific Financial Markets
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Kim, McKenzie, and Faff, Macroeconomic News
Announcements and the Role of Expectations: Evidence for
US Bond, Stock and Foreign Exchange Markets, Journal of
Multinational Finance Management, 2004:
These researchers found for the three markets tested that:
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(1) Balance of trade news had the greatest impact on the foreign
exchange market.
(2) In the bond market, news related to the internal economy
(e.g., retail sales) was found to be important.
(3) For the US stock market, consumer and producer price
information was found to be important.
They also concluded that: “it is not the act of releasing
macroeconomic information which the market considers to
be important, but rather the ‘news’ component of each
release – i.e., the difference between the markets
expectation and the actual figure.
Using Survey Data to “Proxy”
Market Expectations
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The following two sources provide us with
survey data which we can use to “approximate”
financial market expectations. We can then
compare these expectations to the actual event
(e.g., when the data is released) to assess
market moves.
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Bloomberg:
http://www.bloomberg.com/markets/economiccalendar/
FX Street:
http://www.fxstreet.com/fundamental/economiccalendar/
Appendix 1
Eugene Fama, the Efficient Market
Hypothesis and Stock Prices
Short Bio on Eugene Fama
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Eugene Fama (born February 14, 1939),
an American economist, best known for
his work on portfolio theory and asset
pricing, both theoretical and empirical. He
earned his undergraduate degree in
French from Tufts University in 1960 and
his MBA and Ph.D. from the Graduate
School of Business at the University of
Chicago in economics and finance.
Fama is most often thought of as the
father of the efficient market hypothesis,
beginning with his Ph.D. thesis (1964)
which concluded that stock price
movements are unpredictable and follow
a random walk.
In 1963, he joined the faculty at
University of Chicago Booth School of
Business.
For more information on Fama see:
http://www.chicagobooth.edu/faculty/bio.
aspx?&min_year=20084&max_year=200
93&person_id=12824813568
Fama: The Efficient Market
Hypothesis and Stock Prices
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Application of Efficient Market Theory to common
stocks can be traced to the work of Eugene Fama
(see: 1965, Financial Analyst Journal).
There are two critical elements in his work:
(1) Efficient market theory applied to Stock Prices:
Stocks are always “correctly priced” given that
everything that is publicly known about a stock is
reflected in its market price.
(2) Random walk theory: Since new information is
random, all future price changes are independent from
previous price changes; thus, future stock prices
cannot be predicted.
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For a more complete discussion see: Burton Malkiel, A
Random Walk Down Wall Street, (Norton Publishing 1973).
Appendix 2
Testing the Efficient Market
Hypothesis
Testing the Efficient Market Hypothesis
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The EMH provided the theoretical basis for much of the
financial market research during the 1970s and 1980s.
During that time, most of the evidence seems to have
been consistent with the EMH.
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Prices were seen to follow a random walk model and the
predictable variations in equity returns, if any, were found
to be statistically insignificant.
So, most of the studies in the 1970s focused on the inability
to predict prices from past prices.
However, beginning in the 1980s, the EMH became
somewhat controversial, especially after the detection of
certain anomalies in the capital markets (i.e., situations
which provided “abnormal returns”).
Testing for Financial Market Anomalies
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Some of the main financial market anomalies
that have been identified are as follows:
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1. The January Effect: Rozeff and Kinney (1976)
were the first to document evidence of higher
mean stock returns in January as compared to
other months.
The January effect has also been documented for
bonds by Chang and Pinegar (1986).
Maxwell (1998) showed that the bond market
effect is strong for non-investment grade bonds,
but not for investment grade bonds.
The Weekend (or Monday) Effect
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2. The Weekend Effect (or Monday Effect):
French (1980) analyzed daily returns of U.S. stocks
for the period 1953-1977 and found that there was a
tendency for returns to be negative on Mondays
whereas they were positive on the other days of the
week.
Agrawal and Tandon (1994) found significantly
negative returns on Monday in nine countries and
on Tuesday in eight countries, yet large and positive
returns on Friday in 17 of the 18 countries studied.
Steeley (2001) found that the weekend effect in the
UK disappeared in the 1990s.
Seasonal Effects
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3. Seasonal Effects: Holiday and turn of the month
effects have been documented over time and across
countries.
Lakonishok and Smidt (1988) showed that U.S.
stock returns were significantly higher at the turn of
the month, defined as the last and first three trading
days of the month.
Ziemba (1991) found evidence of a turn of month
effect for Japan when turn of month was defined as
the last five and first two trading days of the month.
Cadsby and Ratner (1992) provided evidence to
show that returns were, on average, higher the day
before a holiday, than on other trading days.
Small Firm Effects
4. Small Firm Effect:
 Banz (1981) published one of the earliest
articles on the 'small-firm effect' which is also
known as the 'size-effect'.
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His analysis of the 1936-1975 period in the U.S.
revealed that excess returns would have been
earned by holding stocks of low capitalization
companies.
Over/Under Reaction Effect
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5. Over/Under Reaction of Stock Prices to
Earnings Announcements: DeBondt and
Thaler (1985, 1987) presented evidence that
is consistent with stock prices overreacting to
current changes in earnings.
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They reported positive (negative) estimated
abnormal stock returns for portfolios that
previously generated inferior (superior) stock price
and earning performance.
This was construed as the prior period stock price
behavior overreacting to earnings
announcements.
Standard and Poor’s Effect
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6. Standard & Poor’s (S&P) Index effect:
Harris and Gurel (1986) and Shleifer (1986)
found an increase in share prices (up to 3
percent) on the announcement of a stock's
inclusion into the S&P 500 index.
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Since in an efficient market only new information
should change prices, the positive stock price
reaction appears to be contrary to the EMH
because there is no new information about the
firm other than its inclusion in the index.
Weather Effect
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7. The Weather: Saunders (1993) showed
that the New York Stock Exchange index
tended to fall when it was cloudy.
Hirshleifer and Shumway (2001) analyzed
data for 26 countries from 1982-1997 and
found that stock market returns were
positively correlated with sunshine in almost
all of the countries studied.
Human Behavior in Markets
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If we assume that markets are not totally rational
(i.e., they don’t react as a rational expectations
model would suggest), it might be possible to
explain some of the anomaly findings on the basis of
human and social psychology.
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John Maynard Keynes once described the stock market as
a "casino" guided by "animal spirit" (1939).
Shiller (2000) describes the rise in the U.S. stock market in
the late 1990s as the result of “psychological contagion
leading to irrational exuberance.”
Behavioral Finance and Asset Pricing
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Suggests that real people:
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Have limited information processing capabilities
Exhibit systematic bias in processing information
Are prone to making mistakes
Tend to rely on the opinion of others (fads); referred to
as a “bandwagon” effect.
Conclusions from EMH Tests
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The studies based on EMH have made an
invaluable contribution to our understanding of
financial market.
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The role of information (especially new information) in
asset pricing.
However, for some there seems to be growing
discontentment with the theory’s “rational
expectations” focus.
However, for an excellent paper in support of the
EMH read: “The Efficient Market Hypothesis and
its Critics,” by Burton Malkiel, Princeton
University, Working Paper #91, April 2003.
Appendix 3: Three Forms
of Market Efficiency
The following slide discusses the three
forms of market efficiency
Three Forms of The Efficient Market
Hypothesis
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There are actually three stages of the EMH model:
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Weak Form: Current prices reflect all past price and past
volume information.
 The fundamental information contained in the past sequence of
prices of a security is fully reflected in the current market price
of that security.
Semi-strong Form: Current prices reflect all past price and past
volume information AND all publicly available information.
 Information such as interest rates, earnings, inflation, etc.
Strong Form: Current prices reflect all past price and past
volume information, all publicly available information publicly
available information AND all private (e.g., insider) information.