the efficient market hypothesis chapter 8. 8-2 introduce the three forms of the efficient market...

The Efficient Market Hypothesis

CHAPTER 8

8-2

Introduce the three forms of the Efficient Market Hypothesis (EMH) (效率市場假說 )Discuss the practicability (可行性 ) of technical and fundamental analyses and the active asset management under different forms of the EMHCite evidence that supports or disproves the EMHExamine the EMH by analyzing the performance of stock analysts and fund managers

※There is a lot of descriptive content in Ch. 8, so I rearrange the lecture slides in a more logical way than that of the text book

The Goals of Chapter 8

8-3

8.1 RANDOM WALKS AND THE EFFICIENT MARKET HYPOTHESIS

8-4

Efficient Market Hypothesis (EMH)Kendall (1953) first found that it is almost impossible to identify predictable patterns in stock prices– Stock prices seem to evolve randomly– The past performance provided no way to predict

future price movementsSome economists treated these results from the irrationality of the market– Because they believe that similar to predicting the

business cycle or GDP of a nation, it is possible to predict stock prices

– They soon realized that random price movements indicate a well-functioning or efficient market, not an irrational one

8-5

Efficient Market Hypothesis (EMH)The following arguments support that the stock prices are unpredictable in efficient markets– Stock prices react immediately to all news (even the

mentioned events will occur in the future)Suppose there is an accurate forecast that the stock price of XYZ will rise by 30% in one week

– Every investor intends to buy the shares of XYZ, but no stockholders of XYZ are willing to sell

– As a result, the stock price rises immediately to a proper level to reflect this good news

Therefore, a forecast about future performance leads to current stock price movement

Equivalently, we can say that the current stock price has already reflected all information that could be used to predict the future performance of the firm

8-6

Efficient Market Hypothesis (EMH)– Competition as a source of efficiency

Competition among many professional, highly paid, aggressive analysts ensures that all relevant information can be discovered soon in the stock marketsBased on the discovered information, they can buy or sell stocks such that stock prices ought to reflect available information regarding their proper levels

– Stock prices change randomlyNew information occurs and is discovered randomly and unpredictably

– If it is predictable, it would be part of today’s information, and the stock price should already reflects this information

As a result, the stock price, which reflects news immediately, should change randomly and unpredictablyWe can further conclude that the past performance is irrelevant with future performance

8-7

Efficient Market Hypothesis (EMH)The Efficient Market Hypothesis (EMH) (效率市場假說 )– The notion that current stock prices fully reflect all

available information is referred to as the efficient market hypothesis

– In other words, if the stock prices can reflect new information immediately, then the market is efficient

– The most important argument to support that markets should be efficient

The pursuit for profit and the competition among investors to discover information ensure the randomly evolving stock prices and thus the efficiency of markets

8-8

Cumulative Abnormal Returns (CAR) (累計異常報酬 ) For Takeover Attempts

※ The abnormal return (異常報酬 ) (or risk-adjusted return) is the difference between the actual return and the predicted return based on the CAPM

※ In most takeover events, the acquiring firm pays a substantial premium over the current market prices of the merged firm (synergy effect (綜效 ): the value of the combined firm is higher than the sum of the values of individual firms)

※ The figure shows that the announcement of a takeover attempt should cause the stock price of the merged firm to jump immediately

※ In addition, there is no further drift in prices after the announcement date, including the day on which the takeover transaction is physically completed

8-9

Stock Price Reaction to CNBC Reports

※ Busse and Green (2002) show that most of the stock price responses to the announcements of dividends or earnings occur within a very short period after the announcements (almost immediately)

※ The time 0 is the time point at which the stocks are mentioned on the midday show in the news program on CNBC

※ For firms with positive (negative) reports, the stock prices reflect the news in 5 minutes (12 minutes)

8-10

Different Forms of the EMHThree forms of the EMH:– Weak-form, semistrong-form, and strong-form EMH– Different forms of the EMH are determined by

different information sets that security prices can reflect

Weak-form EMH (弱式效率市場假說 ):– Security prices already reflect all information

contained in the history of past trading– If the historical data conveyed reliable signals

about future performance, all investors already would have leaned to exploit the signal

– Implies that the trend or technical analysis (技術分析 ) is fruitless (discussed in the next section)

8-11

Different Forms of the EMHSemistrong-form EMH (半強式效率市場假說 ):– Stock prices already reflect all publicly available

information, including past prices, fundamental data on the firm’s product line, balance sheets, earning forecasts, etc

– Implies that fundamental analyses (基本分析 ) to study earnings and growth forecasts do not work (discussed in the next section)

8-12

Different Forms of the EMHStrong-form EMH (強式效率市場假說 ):– Stock prices reflect all relevant information,

including public information and private information available only to company insiders

– Implies that even for investors with private information, they cannot earn abnormal returns

– SEC limits the trading by corporate officers, directors, and large stockholders and requires these insiders to report trades to prevents them from profiting by exploiting their privileged situation

Degree of efficiency differs in various markets or different securities– Emerging markets, markets with less rigorous

disclosure requirement, and small stocks with less notice by stock analysts are less efficient

8-13

Information Sets for Different Forms of the EMH

※ The above figure shows the information set of different EMH forms (strong-form > semistrong-form > weak-form)

※ Semistrong-form efficiency implies that weak-form efficiency holds (but NOT vice versa)

※ Strong-form efficiency implies that both semistrong-form and weak-form efficiency hold (but NOT vice versa)

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8.2 IMPLICATIONS OF THE EMH(For Technical and Fundamental Analyses and Active vs. Passive

Management )

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Types of Stock Analysis

Technical Analysis (技術分析 )– Using past information of prices and trading

volumes to search for recurrent and predictable patterns in future stock prices (introduced in Ch 9)

– Buying winners or shorting losers (追高殺低 ) are typical examples:

Buy (short) stock performing relatively well (poor) recently because such trend may continue for a long enough period of time to offer profit opportunities

– For markets in any form of efficiency, the technical analysis based on past information is worthless since the market prices already reflect all past information

8-16

Types of Stock AnalysisFundamental Analysis (基本分析 )– Using publicly economic and accounting

information to predict stock prices (Ch. 12 to Ch. 14)

– In a semistrong-form or strong-form efficient market, fundamental analyses do not work

Because many individual and institutional investors conduct fundamental analyses based on public information to design their investment strategies, the stock prices already reflect all public information

– In contrast, fundamental analyses are feasible in weak-form efficient and inefficient markets

Due to the competition among investors, you can make money only if your analysis is better than that of your competitors, i.e., you can predict the performance of firms more accurately than the prediction of other investors

8-17

Three reasons to suggest that the active management is not preferred in efficient markets1. Huge efforts to find securities with minor mispricing by

technical or fundamental analyses in efficient marketsAn example for a fund adopting active management:

– Consider a fund with a $5 billion portfolio, and the fund manager plan to organize a research to pursue the increase of the rate of return by 0.1% per year

– That means the fund manager would be willing to spend up to $5 million (= 0.1% × $5 billion) on research

– The active portfolio management is economically feasible only for managers of large portfolios but not appropriate for individual investors magnitude issue (規模問題 )

– For institutional investors, is it worthy to spend those huge efforts? Is there any alternative to improve the performance?

Implications of EMH for Active or Passive Management

8-18

2. Difficult to distinguish the change of the performance coming from the researches or the fluctuations of the market

Because of that, it is doubtful that whether mutual funds have the ability to discover mispriced stocks

3. Difficult to judge the degree of mispricing and whether it is sufficiently large to repay the costs in the active portfolio management

Proponents of the EMH believe the active management is largely wasted in an efficient market and they advocate a passive management that makes no attempt to outperform the market


8-19

Passive investment strategy is to buy a well-diversified portfolio without attempting to search out mispriced securities

One common strategy for the passive management is to invest in an index fund, which is designed to replicate the performance of the market portfolio underlying the index– The fees is relatively lower because an index fund

does not need to pay analysts to assess stock prospects and incurs less tax and transaction costs due to its low turnover rate


8-20

Markets are weak-form efficient or worse Active management– Conduct security analyses, like fundamental and/or

technical analyses, to pick securitiesFor weak-form efficient or worse markets, it is valuable that stock analysts generate reports and send them to investors based on the results of fundamental analyses

For inefficient markets, it is also possible to timing the market based on the technical analyses

Markets are semistrong-form efficient or better Passive management– Buy and hold well-diversified portfolios, like index

funds


8-21

Although all securities are fairly priced (because the market is efficient), the most important function of portfolio managers is to construct portfolio to eliminate firm-specific risk by diversification– Moreover, the portfolio manager in an efficient

market is to tailor the portfolio for the needs of investors, rather than to outperform the market

Investors’ optimal positions vary according to many factors, like age, tax bracket, risk aversion, or employment status

For example, for retired persons, they may prefer funds providing high and stable dividend yields such that they can receive regular incomes from the funds

The Role of Portfolio Management in an Efficient Market

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8.3 ARE MARKETS EFFICIENT

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Three issues imply the debate of whether markets are efficient will never stop– Roles and performance of professional investors

The proponents of the EMH believe that the existence of professional investors can result in efficient markets

This is because stock prices are not far from fair values and that only managers of larger portfolios can exploit minor mispricing to earn enough trading profits

However, the effort of professional investors is difficult to be identified (0.1% improvement vs. 20% volatility)

Thus, we can conclude neither the effort of professional investors is valuable nor their existence results in an efficient market, although their actions are indeed the driving force to let market prices move to fair levels

Empirical Tests of Market Efficiency

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– Selection bias issue (選擇性偏誤 )Another method to examine the EMH is to test all trading strategies in the market. If they can not provide abnormally higher returns, we can conclude the market is efficient

Assuming that you discover an investment strategy that really makes money, what will you do?

Hence, the trading strategies we observe in the market have been preselected in favor of failed attempts, so we cannot evaluate the true ability of portfolio managers to invent profitable strategies

You cannot deny the possible existence of profitable strategies that are not released and therefore the possibility that the market is not efficient


8-25

– Lucky event issue (純屬好運 )Some studies examine the EMH according to the performance of fund managers. If they cannot beat the market, then we can conclude that the market is efficient

However, if many professional investors use a variety of schemes to make fair bets, statistically speaking, some will be lucky and win a great majority of bets (e.g., Peter Lynch or Warren Buffett), and some will be unlucky and lose a lot

– So, we cannot conclude that the superior record of few winners disprove the efficient market hypothesis although what we heard are all about the feats of winners

Proper tests (discussed in Section 8.4) may include:– To study the distribution or the average of the performance of

fund mangers– To test whether the winners can repeat their performance in

another periods, i.e., to examine the consistency of the performance of fund managers


8-26

Weak-Form Tests: Patterns in Stock Returns

Patterns from the past information can be found Markets are not weak-form efficientReturns over short horizons (< 1 year)– For weekly returns of NYSE individual stocks,

fairly small magnitude of positive serial correlation is found

– For 3- to 12-month periods, there is some evidence of positive serial correlation in both the aggregate market and portfolios of best- and worst-performing stocks (the latter is known as the momentum effect (動能效果 ))

Returns over long horizons (3 to 5 years)– Pronounced negative serial correlation in the

performance of the aggregate market

8-27

Weak-Form Tests: Patterns in Stock Returns– The reversal effect (反轉效果 ) for extremely

performing individual stocksMany studies suggest that over long horizons, the performance of extreme-performing stocks tends to reverse, i.e., losers rebound and winners fade backDe Bondt and Thaler (1985) find that the worst-performing portfolio (according to 5-year historical returns) outperform the best-performing portfolio in the following three yearsThe reversal effect implies a contrarian (反向操作 ) investment strategy–investing in recent losers and avoiding recent winners–should be profitable

※Possible explanation for the short-term momentum and long-term reversal effects

Stock market might overreact to relevant news, and such overreaction leads to momentum effect over short horizonsSubsequent correction of the overreaction leads to negative serial correlation (the reversal effect) over longer horizons

8-28

Efficient market anomalies (效率市場異常現象 ): The phenomenon difficult to reconcile with the semistrong-form EMH that several easily accessible quantity, e.g., the P/E ratio or the firm size, seem to predict risk-adjusted returns P/E (price/earning) ratio (本益比 ) effect– Basu (1977, 1983) found that the portfolios with low

P/E have higher returns than those with high P/E– The P/E ratio effect holds even for returns adjusted

for portfolio beta, i.e., the return in excess of the return predicted by CAPM

– A possible explanation is that the CAPM beta cannot fully adjusts for risk, and P/E can act as a useful indicator of another source of risk

Semistrong Form Tests: Market Anomalies

8-29

Small-Firm Effect (小公司效應 )– Banz (1981) examined the small-firm effect

The smaller-firm portfolios tend to be riskier (with higher betas), so it is not surprised that they should provide higher expected rates of return

Even when returns are adjusted for risk using the CAPM, there is still a consistent premium of the smaller-sized portfolios

See the figure on the next slide

– Keim (1983), Reinganum (1983), and Blume and Stambaugh (1983) showed that the small-firm effect occurs virtually entirely in January, particularly in the first 2 weeks of January. Thus the size effect is also called the “small-firm-in-January” effect

Semi-Strong Form Tests: Market Anomalies

8-30

Returns in Excess of Risk-Free Rate and in Excess of the SML

※ This figure shows the historical performance of portfolios formed by classifying the NYSE stocks into 10 portfolios according to the firm size each year

※ Returns in excess of CAPM, also known as abnormal returns (異常報酬 ), means to calculate the results of ri – [rf + βi(rM – rf)]

※ It is obvious that “invest in low-capitalization stocks” could earn more abnormal returns, i.e., earn higher returns for bearing the same level of the systematic risk

8-31

Neglected-firm and liquidity effects (流動性效應 )– Neglected-firm effect

Small firms tend to be neglected by large institutional traders, so information about smaller firms is less available (see Arbel and Strebel (1983) and Arbel (1985))

This information deficiency makes smaller firms riskier investments that command higher returns (another way to explain the small-firm effect)

– Since small and less-analyzed stocks are in general less liquid and less-liquid stocks usually provide higher returns, Amihud and Mendelson (1986, 1991) intend to use the liquidity risk on stock returns to explain both the small- and neglected-firm effects

However, their theory cannot explain why the abnormal returns of small firms concentrate in January


8-32

Book-to-market ratio (帳面市值比 )– Fama and French (1992) showed that B/M ratio can

be a powerful predictor of stock returns, i.e., high B/M ratio stocks offer higher expected return (see the figure on the next slide)

– In addition, they also found that the dramatic dependence of returns on book-to-market ratio is independent of beta (betas for these ten groups are almost indistinguishable), so the same pattern can be derived by comparing the risk-adjusted returns for the ten groups


8-33

Average Annual Return as a Function of Book-to-Market

※ The decile with the highest B/M ratio has an average annual return of 18.7%, while the lowest B/M ratio decile has an average of only 10.64%

8-34

Post-Earnings Announcement Price Drift– Although the EMH suggests the stock price

should jump immediately when good or bad news is made public, stock prices response to firm’s earnings announcements in a sluggish way (see the figure on the next slide)

– Therefore, it is possible to earn abnormal profits by simply purchasing a stock portfolio of positive-earnings-surprise companies

– Since predictable continuing trends ought to be impossible in an efficient market, so this phenomenon is still a anomaly


8-35

Cumulative Abnormal Returns (CAR) in Response to Earnings Announcements

※ Rendleman, Jones, and Latane (1982) classified stocks into 10 deciles based on the magnitude of the “surprise” of the earnings, and calculated CARs for each decile for the following 3 months

※ Earnings surprise is the difference between the actual announced earnings and the expected earnings from market participants

※ There are indeed jumps on the announcement day to reflect the earnings surprise, but the stock price continues to move in the same direction of the jump for the following 3 months

8-36

Strong-Form Tests: Inside Information

It is not surprising if insiders are able to make superior profits in their trading firm’s stock (see Jaffe (1974), Seyhun (1986), Givoly and Palmon (1985), etc.)

In other words, it is not expected that markets are strong-form efficient

In order to prevent the inside trading hurts the interests of investing public, SEC requires all insiders to register their trading activities and release this information to the investing public

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Interpreting the Evidence

The P/E, small-firm, B/M, short-term momentum, and long-term reversal effects are currently the most puzzling phenomena in empirical finance

Two kinds of explanations: Risk Premiums (風險溢酬 ) vs. Market Inefficiencies (市場無效率 )– Fama and French (1993) argue that these effects

can be explained as manifestations of risk premiums (that is, in their three-factor model, size or B/M ratios act as proxies for some other fundamental risks)

– Indeed, not only rM can reflect the business cycle, rSMB and rHML seem to predict the business cycles in many countries as well (see the next slide)

8-38

Return to Style Portfolio as a Predictor of GDP Growth

※ This figure shows the difference between the average rSMB (rHML) before a good GDP growth and the average rSMB (rHML) before a poor GDP growth

※ The differences are significantly different from zero for many countries, which indicates there must be some relationship between the rSMB (rHML) and the business cycle and thus rSMB (rHML) can act as proxies for other fundamental risks

8-39

Interpreting the Evidence– On the other hand, Lakonishok, Shleifer, and Vishny

(1994) argue that these effects are evidences of inefficient markets

– They believe that investors extrapolate (外插 ) past performance too far into the future, and therefore overprice (underprice) firms with recent good (poor) performance. Ultimately, when investors recognize their errors, prices move reversely

– This argument can explain the short-term momentum, the long-term reversal, and partial P/E, small-firm, B/M effects

Prices decrease (increase) P/Es decrease (increase), tend to be small (large) firms, and B/Ms increase (decrease)Investors seem too pessimistic (optimistic) about the future according to recent poor (well) performance. When these too-extreme expectations are corrected, firms with recent poor performance will outperform firms with recent well performance

8-40

Anomalies (異常現象 ) or Data Mining (數據挖掘 )– Some academics wonder whether these anomalies

are really unexplained puzzles in financial markets, or whether they instead are an artifact of data mining

– Data mining: Rerun the computer to analyze past returns over and over and examine stock returns along enough dimensions simple chance may cause some criteria to appear to predict returns

– One way to address the problem of data mining is to find a data set that has not already been researched and see whether the relationship in question shows up in the new data set (in-sample vs. out-of-sample tests)

Interpreting the Evidence

8-41

8.4 MUTUAL FUND AND ANALYST PERFORMANCE

(Another Indicators for the Degree of Efficiency of Markets)

8-42

Stock Market Analysts

Markets are efficient Almost all securities reflect news quickly and are at their fair prices Stock analysts’ reports are worthless, and fund managers cannot earn abnormal returns and show persistent performance

Do stock analysts add value – mixed evidence– Womack (1996)

Positive (negative) changes of stock analysts’ recommendations are associated with the changes of stock prices by 5% (–11%)

Are price changes due to stock analysts’ superior information or pressure brought by the recommendations themselves?

Womack argues that the price impact seems to be permanent, which supports that stock analysts do reveal new information

8-43

Stock Market Analysts– Jegadeesh, Kim, Krische, and Lee (2004)

Changes in consensus recommendations are associated with price changes, but the level of consensus recommendations is an inconsistent predictor of future stock performance

(Consensus recommendations are the mean of all outstanding recommendations for a given firm)

– Barber, Lehavy, McNichols, and Trueman (2001)Firms with the most-favorable recommendations outperform those with the least-favorable recommendations (level of consensus recommendations does matter)

8-44

Mutual Fund Managers

Persistent well or poor performance for fund managers – mixed evidence– The phenomenon may be caused from potential

measurement error for benchmark returnsMaybe some funds bear more (less) systematic risk such that can provide consistently higher (lower) rate of return

Therefore, we should examine the abnormal (or risk-adjusted) return (i.e., the difference between the actual returns and the returns predicted by the CAPM or said the α in the CAPM)

Malkiel (1995) computed these abnormal returns (α) for a large sample of mutual funds between 1972 and 1991 (see the figure on the next slide)

8-45

Estimates of Individual Mutual Fund Alphas Based on CAPM

※ The distribution of α is near a normal distribution, with a mean that is slightly negative but statistically indistinguishable from zero

※ Therefore, it suggests that these funds, on average, does not outperform the market index on a risk-adjusted basis

8-46

Mutual Fund Managers– Another measurement error:

Since mutual funds tend to hold in equity of smaller firms, whereas the S&P 500 is comprised of large firms, mutual funds tend to outperform the S&P 500 market portfolio due to the small-firm effect

– The abnormal (or risk-adjusted) return of the Fama-French three-factor model should be examined

Some mutual funds exploit the momentum or reversal effects to earn abnormal returns

– The abnormal (or risk-adjusted) return of the Carhart four-factor model (introduced next) should be examined

8-47

Mutual Fund ManagersCarhart (1997) proposed a four-factor model to study the performance of mutual funds– Four factors include the rS&P 500, rSMB, rHML, and prior-

year stock market return (PR1YR)

– PR1YR, like rSMB and rHML, is the return of a zero-investment, factor-mimicking portfolio to capture the intermediate-term momentum effect

– PR1YR is defined as the difference of the this-year average returns between the best 30% performing stocks and the worst 30% performing stocks on NYSE, Amex, and Nasdaq in the prior year

– A positive (negative) coefficient for PR1YR indicates that the mutual funds tend to invest and hold the current winner (losers) in the next period

HML HML SMB SMB PR1YRPR1YRi i iM M i i i iR R r r e

8-48

Estimates of Individual Mutual Fund Alphas Based on the Four-Factor Model

※ Since α’s are distributed normally around 0, the evidence is consistent with market efficiency based on the 4-factor model

※ By examining the α of the 4-factor model, Carhart finds that there are no consistently superior performers, i.e., the consistent better (unadjusted) performance observed in the market is not due to the better skill of fund managers, but due to the consistent investment in smaller firms, higher B/M firms, or the past winners

※ On the contrary, there could be consistently inferior performers, but Carhart attributes the repeated weak performance to the structure of the expenses and transaction costs of mutual funds rather than to pick wrong stocks consistently

8-49

Persistence of Mutual Fund Performance

※ To analyze the persistence of mutual fund performance, Carhart classifies stocks into ten groups according to the excess returns of the formation year and examines their excess returns in the subsequent 5 years

※ The above figure shows that except for the best and worst performing groups, performances of the rest are independent of the formation-year returns, and in fact, the superiority of the best groups is very minor

8-50

Mutual Fund ManagersBerk and Green (2004)– Skill should show up not in superior returns but

rather in the amount of funds under managementSkilled fund managers with abnormal performance will attract new funds until the additional costs and complexity of managing those extra funds drive alphas down to zero

Thus, even if managers are skilled, positive alpha will be short-lived (see the figure on the next slide)

Black, Elton, and Gruber (1993)– On average, bond funds underperform fixed-income

indexes by an amount roughly equal to the expense costs

– For bond funds, there is no evidence that past performance can predict future performance

8-51

Alphas in Ranking Quarter and Following Quarter

※ Bollen and Busse (2004) rank mutual performance into 10 deciles, using the alpha of the 4-factor model over a base quarter

※ The solid (dashed) line is the average alpha of funds within each decile in the ranking quarter (in the following quarter)

※ Both lines are downward-sloping There exists some performance consistency

※ However, the consistency is weak due to the minor downward slope for the dashed line

8-52

Mutual Fund ManagersChen, Ferson, and Peters (2010)– On average, bond (equity) mutual funds outperform

passive bond (equity) index in terms of gross returns but underperform once the fees are subtracts

Kosowski, Timmerman, Wermers, and White (2006) (existence of stars of mutual funds)– There may be a minority of managers with exceptional

stock-picking ability, which is sufficient to cover their costs such that their superior performance tends to persist over time

– Peter Lynch (of Fidelity’s Magellan Fund), Warren Buffett (of Berkshire Hathaway), John Templeton (of Templeton Funds), Bill Miller (of Legg Mason), and John Neff (of Vanguard’s Windsor Fund)

the efficient market hypothesis chapter 8. 8-2 introduce the three forms of the efficient market...

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