mishkin ppt06

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Pearson Prentice Hall Financial Markets and Institutions 6 - 1

Expectations - Asset Demand: Returns, Risk, Liquidity - In2lation: Bond Prices, Interest Rates - Risk Structure: Default Risk - Term Structure: Future ST Rates EFFICIENT MARKET HYPOTHESIS / THEORY OF EFFICIENT CAPITAL MARKETS

- states that prices of securities in financial markets fully reflect all available information.


Ef2icient Market Hypothesis

- states that prices of securities in financial markets fully reflect all available information.

Rate of Return [from holding a security]- equals the sum of the capital gain on the security

(the change in the price) plus any cash payments, divided by the initial purchase price of the security:

Pt+1 = Price, end of HP Pt = Price, beg of HP C = Cash Payment

(Coupon or Dividend)

Pt+1 - Pt + C Pt

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Expected Rate of Return- Current Price (Pt) and Cash Payments (C) are known at the beginning, the only variable uncertain is the price next period (Pe t + 1)

C = Cash Payt (Coupon or Dividend) Pe t + 1 = Expected Price, end of HP Pt = Price, beg of HP

The ecient market hypothesis views expectations as equal to optimal forecasts using all available information. Pe t + 1 = Pof t + 1 Optimal forecast: best guess of the future; not perfectly accurate

e Pet+1 - Pt + C

Pt f



Expected Rate of Return Theorists states that e and et + 1 cannot be

observed, so the equations cannot be used to tell how the nancial markets behave.

Measuring value of e have important implications

for how prices of securities change in the nancial market.

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However, demand & supply shows the expected return on a security (interest rate) will have a tendency to head toward the equilibrium return that equates the quantity demanded to the quantity supplied. So using the equilibrium condition:

e *

The expected return on a security equals the equilibrium return.



Deriving an equation to describe pricing behavior using the equilibrium condition:

of *

The current prices in a financial market will be set so that the optimal forecast of a securitys return using all available information equals the securitys equilibrium return.

Financial economists state it: A securitys price fully reects all available information in an ecient market

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Application: Predicting Opening Prices, PtSuppose that a share of Microsoft had a closing price yesterday of $90, but new information was announced after the market closed that caused a revision in the forecast of the price for next year to go to $120. If the annual equilibrium return on Microsoft is 15%, what does the efficient market hypothesis indicate the price will go to today when the market opens? (Assume that Microsoft pays no dividends.)

Rof = optimal forecast of return = 15% R* = equilibrium return = 15% Poft+1 = optimal forecast Price = $120 Solve: Pt C = 0

of *Poft+1 - Pt + C

Pt f



Application: Predicting Opening Prices, Pt Rof = optimal forecast of return = 15% R* = equilibrium return = 15% Poft+1 = optimal forecast Price = $120 Solve: Pt C = 0

0.15 = $120 Pt Pt

Pt x 0.15 = $120 - PtPt x 1.15 = $120

Pt = $104.35

of *Poft+1 - Pt + C

Pt

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Rationale Behind the Hypothesis Arbitrage: market participants eliminate unexploited profit

opportunities (UPO), returns on a security that are larger than what is justied by the characteristics of that security

2 Types of Arbitrage: a. Pure elimination of UPO involves NO RISKS b. Arbitrageur takes on SOME RISK when eliminating UPO

Efficient Market condition: Rof R* " Pth "Rof Rof R* " Pti "Rof

until Rof R*



Rationale Behind the Hypothesis Efficient Market condition:

Rof R* " Pth "Rof

Rof R* " Pti "Rof

In an efficient market, all unexploited profit opportunities will be eliminated.

until Rof R*

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Rationale Behind the Hypothesis An extremely important factor in this reasoning is that

NOT everyone in a financial market must be well informed about a security for its price to be driven to the point at which the efficient market condition holds

SMART MONEY: the few market participants that keep their eyes open for UPO; they will eliminate the UPO because in so doing, they make a profit



Stronger Version of the Ef2icient Market Hypothesis Efficient market conditions:

a. Expectations are optimal using all available information b. prices reflect the market fundamentals - intrinsic value of

the securities

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Stronger Version of the Ef2icient Market Hypothesis Implications on the Security Price:

a. One investment is as good as any other because the securities prices are correct

b. Reects all available info about the intrinsic value of the security

c. Security prices can be used by managers to assess their cost of capital accurately and hence can be used to help them make the correct decisions about the worth of making a specic investment



Evidence on the Ef2icient Market Hypothesis In Favor of Market Efficiency:

a. Performance of Investment Analysts & Mutual Funds b. Stock Prices Reect Publicly Available Information c. Random-Walk Behavior of Stock Prices d. Technical Analysis

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Evidence on the Ef2icient Market Hypothesis Against Market Efficiency

a. Small-Firm Eect b. January Eect c. Market Overreaction d. Excessive Volatility e. Mean Reversion f. New Information Is Not Always Immediately

Incorporated into Stock Prices



Evidence In Favor of Market Ef2iciency a. Performance of Investment Analysts & Mutual Funds

It is impossible to beat the market Buy & sell recommendations from a group of advisers or mutual funds and compare the performance of the resulting selection of stocks with the market as a whole

Having performed well in the past does not indicate that an investment adviser or a mutual fund will perform well in the future

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Ef2icient Market Hypothesis Evidence In Favor of Market Ef2iciency b. Stock Prices Reect Publicly Available Information

Positive announcement about a company will not, on average, raise the price of its stock because this information is already reected in the stock price

c. Random-Walk Behavior of Stock Prices Random Walk: future changes in stock prices should, for all practical purposes, be unpredictable


Ef2icient Market Hypothesis Evidence In Favor of Market Ef2iciency d. Technical Analysis

Study past STOCK PRICE DATA and search for patterns such as trends and regular cycles.

Rules for when to buy and sell stocks are then established on the basis of the patterns that emerge.

Conclusion: Technical analysts fare no better than other nancial analysts. On average, they do not outperform the market, and successful past forecasting does not imply that their forecasts will outperform the market in the future.

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Ef2icient Market Hypothesis Evidence Against Market Ef2iciency a. Small-Firm Eect b. January Eect c. Market Overreaction d. Excessive Volatility e. Mean Reversion f. New Information Is Not Always Immediately

Incorporated into Stock Prices


Ef2icient Market Hypothesis Evidence Against Market Ef2iciency a. Small-Firm Eect

Many empirical studies have shown that small rms have earned abnormally high returns over long periods of time, even when the greater risk for these rms has been taken into account.

Various theories have been developed to explain the small-rm eect, suggesting that it may be due to rebalancing of portfolios by institutional investors, tax issues, low liquidity of small-rm stocks, large information costs in evaluating small rms, or an inappropriate measurement of risk for small-rm stocks.

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Ef2icient Market Hypothesis Evidence Against Market Ef2iciency b. January Eect

Over long periods of time, stock prices have tended to experience an abnormal price rise from December to January that is predictable and hence inconsistent with random-walk behavior.

Some nancial economists argue that the January eect is due to tax issues. Although this explanation seems sensible, it does not explain why institutional investors such as private pension funds, which are not subject to income taxes, do not take advantage of the abnormal returns.


Ef2icient Market Hypothesis Evidence Against Market Ef2iciency c. Market Overreaction

Corporate announcements of major change in earnings, say, a large decline, the stock price may overshoot, and after an initial large decline, it may rise back to more normal levels over a period of several weeks.

This violates the ecient market hypothesis because an investor could earn abnormally high returns, on average, by buying a stock immediately after a poor earnings announcement and then selling it after a couple of weeks when it has risen back to normal levels.

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Ef2icient Market Hypothesis Evidence Against Market Ef2iciency d. Excessive Volatility

Fluctuations in stock prices may be much greater than is warranted by uctuations in their fundamental value.

Robert Shiller of Yale University found that uctuations in the S&P 500 stock index could not be justied by the subsequent uctuations in the dividends of the stocks making up this index.

Consensus that stock market prices appear to be driven by factors other than fundamentals; e.g. Black Monday Crash of 1987 & Tech Crash of 2000


Ef2icient Market Hypothesis Evidence Against Market Ef2iciency e. Mean Reversion

Stocks with low returns today tend to have high returns in the future, and vice versa.

Hence stocks that have done poorly in the past are more likely to do well in the future because mean reversion indicates that there will be a predictable positive change in the future price, suggesting that stock prices are not a random walk.

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Ef2icient Market Hypothesis Evidence Against Market Ef2iciency f. New Information Is Not Always Immediately Incorporated

into Stock Prices Generally, stock prices adjust rapidly to new information.

Recent evidence suggests that, inconsistent with the ecient market hypothesis, stock prices do not instantaneously adjust to prot announcements.

Instead, on average stock prices continue to rise for some time after the announcement of unexpectedly high prots, and they continue to fall after surprisingly low prot announcements.


Ef2icient Market Hypothesis Conclusion on Market Ef2iciency Debate on the ecient market hypothesis is far from over Evidence seems to suggest that the ecient market

hypothesis may be a reasonable starting point for evaluating behavior in nancial markets.

Ecient market hypothesis may not be the whole story and so may not be generalizable to all behavior in nancial markets.

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Ef2icient Market Hypothesis Investing Lessons: On publicly available info: hot tips, investment advisers

published recommendations, & technical analysis No one can outperform the general market, as empirical evidence conrms, even with recommendations from investment advisers; anecdotal evidence is not reliable.

A person who has done well regularly in the past cannot guarantee that he or she will do well in the future.

Be skeptical of Hot Tips Stock Prices DO NOT always rise when there is good news


Ef2icient Market Hypothesis Ef2icient Markets Prescription for the Investor: Pursue a buy and hold strategy - purchase stocks and

hold them for long periods of time. This will lead to the same returns, on average, but the investors net prots will be higher because fewer brokerage commissions will have to be paid.

Small investors: buy into a mutual fund. Choose one that has low management fees.

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Ef2icient Market Hypothesis Black Monday Crash of 1987 & Tech Crash of 2000 October 19, 1987, dubbed Black Monday, the Dow Jones Industrial Average declined more than 20%, largest 1-day decline in U.S. history.

NASDAQ index to fall from around 5,000 in March 2000 to around 1,500 in 2001 and 2002, for a decline of well over 60%

Stronger version of the ecient market hypothesis, which states that asset prices reect the true fundamental (intrinsic) value of securities, is incorrect.

Stock price determination: attributed to market psychology & to institutional structure of the marketplace.



Black Monday Crash of 1987 & Tech Crash of 2000 Rational Bubbles Theory: bubbles - situation in which the

price of an asset diers from its fundamental market value.

Investors hold the asset, because they believe that someone else will buy the asset for a higher price in the future.

Investors can have optimal forecasts, because the bursting of the bubble cannot be predicted & so there are no UPO.

However, other economists believe that the crashes suggest that there may be UPO & that the theory of rational expectations & the ecient market hypothesis might be fundamentally awed.

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Behavioral Finance Applies concepts from other social sciences, such as

anthropology, sociology, and particularly psychology, to understand the behavior of securities prices

Ecient market hypothesis suggests that smart money SELLS when a stock price goes up irrationally, with the result that the stock falls back down to what is justied by fundamentals.

Smart Money helps the market become ecient if they can dominate ordinary investors. But, they can do this only if they engage in short sales.



Behavioral Finance Loss Aversion Theory: Unhappy : Loss > Happy : Gain

Short sales: borrow stock from brokers, then sell it in the market, with the hope that they earn a prot by buying the stock back again (covering the short) after it has fallen in price.

Due to LOSS AVERSION, very little short selling actually takes place, because short sales can result in losses way in excess of an investors initial investment if the stock price climbs sharply above the price at which the short sale is made.

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Behavioral Finance Overcondence & social contagion provide an explanation for

stock market bubbles

When stock prices go up, investors attribute their prots to their intelligence and talk up the stock market.

This word-of-mouth enthusiasm and the media then can produce an environment in which even more investors think stock prices will rise in the future.

The result is then a so-called positive feedback loop in which prices continue to rise, producing a speculative bubble, which nally crashes when prices get too far out of line with fundamentals.



Questions: Optimal Forecasts 1. Forecasters predictions of ination are notoriously

inaccurate, so their expectations of ination cannot be optimal. Is this statement true, false, or uncertain? Explain your answer.

2. Whenever it is snowing when Joe Commuter gets up in the morning, he misjudges how long it will take him to drive to work. Otherwise, his expectations of the driving time are perfectly accurate. Considering that it snows only once every 10 years where Joe lives, Joes expectations are almost always perfectly accurate. Are Joes expectations optimal? Why or why not?

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Questions: Optimal Forecasts 3. If a forecaster spends hours every day studying data to

forecast interest rates, but his expectations are not as accurate as predicting that tomorrows interest rates will be identical to todays interest rates, are his expectations optimal?

4. If the public expects a corporation to lose $5 a share this quarter and it actually loses $4, which is still the largest loss in the history of the company, what does the ecient market hypothesis say will happen to the price of the stock when the $4 loss is announced?

mishkin ppt06

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