FNCE 4070: FINANCIAL MARKETS AND INSTITUTIONS Lecture 7: The Role of Expectations in Financial Markets

How Expectations Shape Financial Asset Prices.

The Efficient Market Hypothesis

(Eugene Fama).

Where is this Financial Center?

NYSE

New York Stock Exchange: Traced back to 1790; Trading in Federal Government Bonds issued to finance the Revolutionary War. In 2007, merged with Euronext (NYSE-Euronext). In 2008, acquired the American Stock Exchange. About 2,800 companies, with a combined market capitalization of about $18 trillion, are listed on the NYSE, trading approximately 1.46 billion shares each day. World’s largest stock exchange by market capitalization.

Site of Federal Hall built in 1700. Home to the first U.S. Congress, Supreme Court, and Executive Branch. George Washington’s inauguration took place here. U.S. Bill of Rights introduced in Federal Hall.

Two Objectives for This Lecture (1) To discuss the role of expectations in

financial markets. How are expectations formed and how do

expectations influence asset prices? (2) To introduce you to the concept of financial

market efficiency and the Efficient Market Hypothesis. What does it mean if financial markets are efficient (or

inefficient)? How do financial asset prices respond if markets are efficient (or inefficient)?

The Role of Expectations Expectations play a critical role in financial markets.

Here are some examples: Markets’ expectations about future inflation affects

Market interest rates (and thus, bond prices) Central bank actions (especially those that target inflation)

relating to their short term benchmark interest rate. Markets’ expectations about future (forward) interest

rates affects Spot interest rates (expectations and liquidity premium theories). The term structure of interest rates, i.e. the shape and slope of

the yield curve. Bond prices, stock prices and foreign exchange rates.

Markets’ expectations about future economic activity affects Stock prices. Commodity prices (e.g., oil)

How are Market “Expectations” Formed? Adaptive Model Prior to the 1960s, most economists (and thus

economic models) assumed that market participants formed adaptive expectations about the future, or that: 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 There were, however, potential problems with the

post WWII adaptive model of expectations: (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. 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 In the 1970’s, global

inflation became the major economic issue for industrial countries. Two distinct inflation peaks:

1973/74 and 1980/81. The inflation of this period

was attributed to cost push “supply shocks” to the global economy. 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. 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 A second approach to financial market expectations,

called rational expectations, took hold in the 1960s. 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).” 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 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:

(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

The Role of Expectation 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.

Key issues: 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 two slides illustrate possible answers to these

questions (Illustrations from Nikolai Chuvakhin, “Efficient Market Hypothesis and Behavioral Finance – Is a Compromise in Sight?)”

Unanticipated “Favorable” EventEfficient Market: Prices would adjust up very quickly Inefficient Market: Prices would drift

upward for some time following the event

Anticipated “Favorable” EventEfficient Market: Prices would drift up for some time before the event and then stabilize

Inefficient Market: Prices would drift up for some time before the event and continue up after

Krispy Kreme and the Efficient Market Theory 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 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.

The Stock Market Reacts to an Unanticipated “Favorable” Event On Tuesday, September 18, 2007, the Federal Reserve surprised

financial markets by lowering the fed funds rate 50 basis points to 4.75% (the markets had been anticipating a reduction of 25 basis points). The announcement took place at 2:15EST.

Conclusions from the Efficient Market Hypothesis 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). 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. Essentially your return will be no better than what the market,

or, a particular security returns.

Issues Surrounding the Efficient Market Hypothesis How efficient are financial markets in terms or

assimilating new information into asset prices? 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? See Appendix 2.

How Efficient are Equity Markets? Equity Markets:

Dann, Mayers, and Raab (1977), Patell and Wolfson (1984), Jennings and Starks (1985): Prices adjusted within 1 to 15 minutes upon receiving information.

Brooks, Patel and Su (2003) Price reaction to announcements of unanticipated negative

events took over 20 minutes and tended to reverse over the following two hours (because of over reaction to the bad news).

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)

See: Raymond Brooks, Ajay Patel and Tie Su, “How the Equity Market Responds to Unanticipated Events,” Journal of Business, 2003, vol. 76, no, 1, pp. 109-133.

How Efficient are Foreign Exchange and Bond Markets? Foreign Exchange (U.S. Dollar/German Mark) Market:

Ederington and Lee (1993, 1995): Found that exchange rates reacted after about 10 seconds of

scheduled macroeconomic news releases and are complete after another 30 seconds. If the market over-reacts, it is corrected within 2 minutes after the release.

Interest Rate (Treasury Bond) Markets: Ederington and Lee (1993, 1995)

Same results as found for the foreign exchange market. Conclusion: Foreign exchange and interest rate markets

(e.g., Treasury markets) react very quickly to information. See: Louis H. Ederington and Jae Ha Lee, “The Short-Run

Dynamics of the Price Adjustment to New Information,” The Journal of Financial and Quantitative Analysis, Vol. 30, No. 1 (Mar., 1995), pp. 117-134

Appendix 1

Eugene Fama, the Efficient Market Hypothesis and Stock Prices

Short Bio on Eugene Fama 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=20093&person_id=12824813568

Fama: The Efficient Market Hypothesis and Stock Prices 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. 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 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. 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 Some of the main financial market anomalies

that have been identified are as follows: 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 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

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'. 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 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. 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

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. 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

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.

Volatility Effect 8. Volatility Effect: These tests are designed to test

for rationality of market behavior by examining the volatility of share prices relative to the volatility of the fundamental variables that affect share prices.

Shiller (1981) and LeRoy and Porter (1981) showed that fluctuations in actual prices (for both stocks and bonds) were greater than those implied by changes in fundamental variables during volatile periods.

Schwert (1989) found increased volatility in financial asset returns during recessions. The empirical evidence provided by volatility tests suggests

that movements in stock prices cannot be attributed merely to the rational expectations of investors, but also involve an irrational component.

Volatility Effect: October 19, 1987 On October 19, 1987, the stock market plunged with what, on

that day, was the largest one-day point loss in the history of the Dow Jones Industrial Average (507.99 points, or 22.6%). Issue: Could such a large one-day loss be reconciled with

efficient markets and the data at that time? The were several factors justifying lower stock prices at the

time: widening federal budget, 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 the 22.6% decline. Many economists concluded that this episode is evidence

that investor psychology plays a role in setting stock prices (along with the fundamentals).

Lead to the study of Behavioral Finance

Human Behavior in Markets 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. 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 Suggests that real people:

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 The studies based on EMH have made an

invaluable contribution to our understanding of financial market. 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: Over-Reaction Effect

Case Study: Nike and the Over Reaction Effect

Nike and the Overreaction Effect Thursday, November 18, 2004  Near the close of the market (just before 4:00) the

company announced that Philip H. Knight, co-founder of Nike (NYSE: NKE) Inc., was stepping down as president and chief executive officer of the company.

Overreaction of Nike Stock

Close Day Before $85.99 (11/17)

Close Day Of $85.00 (11/18) % change* -1.2%

Close the Day After: $82.50 (11/19) % change* -4.1%

Close 7 Days After $86.55 (12/1) % change** = 4.9%

Note: * = % change from close day before announcement.

** = % change from close the day after the announcement.

Appendix 4: Three Forms of Market Efficiency

The following slide discusses the three forms of market efficiency

Three Forms of The Efficient Market Hypothesis

There are actually three stages of the EMH model: 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.