1. THE EFFICIENT MARKET HYPOTHESIS
CHAPTER 10
THE EFFICIENT MARKET HYPOTHESIS

2. Analysis of economic time series in 1950s
Business cycle theorist, evolution of several economic variables overtime
What about the behavior of stock market prices
Maurice Kendall 1953, no predictable patterns in stock prices
Irrationality?
Random price movements indicate a well- functioning or efficient market, no an irrational one
Why and implications 2

3. 10.1 RANDOM WALKS AND THE EFFICIENT MARKET

4. Efficient Market Hypothesis
Do security prices reflect information ?
Why look at market efficiency?
Implications for business and corporate finance
Implications for investment

5. Efficient Market Hypothesis
Forecast of a future price increase will lead instead to an immediate price increase
If it is sure the stock price will increase, then large orders to buy the stock and no one holding the stock will sell, immediate jump in stock price
Stock price will immediately reflect the good news implicit in the model’s forecast
Any information that could be used to predict stock performance should already be reflected in stock prices
Increase or decrease only in response to new information, which is unpredictable; the stock prices that change in response to new information also must move unpredictably
Random walk

6. Random Walk and the EMH Random Walk - stock prices are random
the price changes should be random and unpredictable
Not irrationality
Randomly evolving stock prices are the consequence of intelligent investors competing to discover relevant information
Random walk would be the natural result of prices that always reflect all current knowledge
EMH
The stocks already reflect all available information

7. Cumulative Abnormal Returns Before Takeover Attempts: Target Companies

8. Stock Price Reaction to CNBC Reports

9. Competition as the source of efficiency
Why expect prices to reflect all available information
Grossman and Stiglitz (1980)
Investors have incentive to spend time and resources to analyze and uncover new information only if higher returns
Degree of efficiency differs across various markets
Emerging markets, less intensively analyzed, accounting disclosure requirements less rigorous, small stocks receive relatively little coverage

10. Competition as the source of efficiency
Competition among the well-backed, highly paid, aggressive analyst ensures that stock prices ought to reflect available information regarding their proper levels
With many well-backed analysts willing to spend resources on research, easy picking in the market are rare, incremental return on research activity may be small that only largest portfolios will find them worth pursuing

11. Versions of EMH Weak Semi-strong Strong
Reflect all information that can be derived by examining market
trading data, past prices, trading volume, or short interest
Semi-strong
All publicly available information regarding the prospects of a firm
Past prices, fundamental data
Strong
All information relevant to the firm
Even including information available only to company insiders

12. 10.2 IMPLICATIONS OF THE EMH

13. Types of Stock Analysis
Technical Analysis - using prices and volume information to predict future prices.
Weak form efficiency & technical analysis
Fundamental Analysis - using economic and accounting information to predict stock prices.
Semi strong form efficiency & fundamental analysis

14. Technical Analysis
Search for recurrent and predictable patterns in stock prices
Prices responds slowly enough
Resistance levels/ supprt levels
Example, XYZ traded at 70 for several months. Once it declined to 65 then increased, 70 is considered a resistance level, because investors who bought at 70 will be eager to sell their shares as soon as they can break even, selling pressure at 70
EMH implies technical analysis is without merit
Past history of prices and trading volume is publicly available, any information from analyzing past prices has already been reflected in stock prices
Price patterns self-destructing, occasionally uncover a profitable trading rule, then it will be invalidated when the mass of traders attempts to exploit it
Market dynamic is one of a continual search for profitable trading rules

15. Technical Analysis Dow theory Elliott wave theory Moving averages
Primary trend
Secondary trends
Minor trends
Elliott wave theory
A set of wave patterns
Moving averages
Relative strength approach

16. Fundamental Analysis
Use earnings and dividend prospects of the firm, expectations of future interest rates, risk evaluation of the firm to determine proper stock prices
Attempt to determine the present discounted value of all payments a stockholder will receive
Past earnings, balance sheets, further detailed economic analysis (quality of management, standing within its industry, prospects for the industry)

17. Fundamental Analysis
EMH implies most fundamental analysis is doomed to failure.
Competition of uncovering information
Many well-informed well-financed firms conducting market research
Difficult to uncover special information
Only analysts with a unique insight will be rewarded
Not to identify firms that are good, but to find firms that are better than everyone else’s estimate

18. Active or Passive Management
Competition among investors
Only serious analysis and uncommon techniques are likely to generate the differential insight necessary to yield trading profits
Feasible economically only for managers of large portfolios
Active Management
Security analysis
Timing
Passive Management
Aims only to establishing a well-diversified portfolio of securities without attempting to find under-or-overvalued
Buy and Hold
Index Funds
Broad diversification, low management fees

19. Market Efficiency & Portfolio Management
if the market is efficient, what is the role of portfolio management?
Selection of a well-diversified portfolio
Tax considerations
Particular risk profile of an investor
Investors’ optimal positions will vary according to factors such as age, tax bracket, risk aversion and employment, the role of the portfolio managers in an efficient market is to tailor the portfolio to these needs, rather than to beat the market

20. 10.3 EVENT STUDIES

21. Empirical Tests of Market Efficiency
Event studies
A technique of empirical financial research, assess the impact of a particular event on a firm’s stock price
Assessing performance of professional managers
Testing some trading rule

22. Event Studies
Empirical financial research that enables an observer to assess the impact of a particular event on a firm’s stock price
Abnormal return due to the event is estimated as the difference between the stock’s actual return and a proxy for the stock’s return in the absence of the event (benchmark return)
Benchmark return:
broad market index
the stocks matched according to criteria such as firm size, beta, recent performance, ratio of P/B
Normal returns using CAPM or multifactor model

23. Market model to estimate abnormal returns
Single-index Model approach
rt = at + btrMt + et
(Expected Return)
Excess Return = (Actual - Expected)
et = Actual - (at + btrMt)
r is decomposed into market and firm-specific factors, the firm-specific or abnormal return may be interpreted as the unexpected return resulting from the event
et : (component due to the event) Abnormal return, the return beyond what would be predicted from market movements alone

24. How Tests Are Structured
steps
Estimate a and b using data of the prior period
Record the information release date
Abnormal returns surrounding the announcement
Statistical significance and magnitude of the typical abnormal return assessed to determine the impact of the newly released information
Leakage of information
Released to a small group of investors before official public release
Cumulative abnormal return
Sum of all abnormal returns over the time period of interest, capture the total firm-specific stock movement for an entire period when the market might be responding to new information

25. How Tests Are Structured (cont’d)
Cumulate the excess returns over time (leakage of information) +t -t

26. 10.4 ARE MARKETS EFFICIENT

27. Issues in Examining the Results
Magnitude Issue
Hard to measure the contribution of active research
Actions of intelligent investment managers are the driving force behind the evolution of prices to fair levels
Selection Bias Issue
The outcomes we observe have been preselected in favor of failed attempts
Cannot evaluate the true ability of portfolio managers
Lucky Event Issue
Possible Model Misspecification

28. Weak-Form Tests: Patterns in Stock Returns
Could speculators find trends in past prices that would enable them to earn abnormal profits
Test of the efficacy of technical analysis
Discerning trends by measuring the serial correlation of stock market returns
Tendency for stock returns to be related to past returns
serial correlation: positive, negative

29. Weak-Form Tests: Patterns in Stock Returns
Returns over short horizons (Empirical test)
weak price trends over short periods (weekly returns), no existence of trading opportunities
Positive serial correlation over short horizons, small correlation coefficients of weekly returns,
Short-to-intermediate-horizon price momentum in both the aggregate market and cross-sectionally (3-12 month )
good or bad recent performance of particular stocks continues over time
Portfolios of the best-performing stocks in the recent past appear to outperform other stocks with enough reliability to offer profit opportunities

30. Weak-Form Tests: Patterns in Stock Returns
Returns over long horizons (multiyear periods)–negative long-term serial correlation in the aggregate market
Fads hypothesis, the stock market might overreact to relevant news
Overreaction leads to positive serial correlation over short time horizons
Subsequent correction leads to poor performance following good performance
Not conclusive evidence regarding efficient markets
May be interpreted that the market risk premium varies over time
Rational response of market prices to changes in discount rates

31. Predictors of Broad Market Returns
Observable variables to predict market returns
Fama and French
Aggregate returns are higher with higher dividend/price ratios, dividend yield
Campbell and Shiller
Earnings yield can predict market returns
Keim and Stambaugh
Bond spreads can predict market returns
Proxy for variation in the market risk premium

32. Semi-Strong Tests: Market Anomalies
Whether publicly available information beyond trading history of a security can be used to improve investment performance to test sem-strong form
Market anomalies: findings in the market which are difficult to reconcile with the EMH
Adjust for portfolio risk before evaluating the success of an investment strategy
P/E Effect: Portfolios of low price-earnings ratio stocks have higher returns: higher risk, lower price, lower P/E; higher risk, higher expected return
Unless CAPM beta fully adjusts for risk, P/E will act as a useful additional descriptor of risk, associated with abnormal returns

33. Semi-Strong Tests: Market Anomalies
Small Firm Effect (January Effect)
Dividing the NYSE stocks into 10 portfolios each year according to firm size.
Average annual return are higher on the small-firm portfolios
Small-firms tend to be riskier, but adjusted for risk using the CAPM, there is still a consistent premium for the smaller-sized portfolios
Invest in low-capitalization stocks, earn excess returns
Small-firm-in-January effect

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

35. Semi-Strong Tests: Market Anomalies
Interpretation of the small-firm-in-january effect
Neglected Firm effect and liquidity effect
Book-to-Market Ratios
Post-Earnings Announcement Drift

36. Semi-Strong Tests: Market Anomalies
Neglected Firm effect and liquidity effect
Small firms tend to be neglected by large institutional traders, information about smaller firms is less available
Arbel (1985), Divide firms into highly researched, moderately researched, and neglected groups based on the number of institutions holding the stock, january effect was largest for the neglected firms
Merton(1987), neglected firms might be expected to earn higher equilibrium returns (maybe a type of risk premium)
Amihud(1986), effect of liquidity on stock returns might be a partial explanation of their abnormal returns. investors demand return premium to invest in less-liquid stocks that entail higher trading costs

37. Semi-Strong Tests: Market Anomalies
Book-to-Market Ratios
A powerful predictor of returns, higher ratio higher return
Fama and French (1992), divide firms into 10 groups according to book-to-market ratios, examine the average monthly return
Dependence of returns on b/m ratio is independent of beta, b/m ratio may serve as a proxy for a risk factor that affect equilibrium expected return
After control for size and book/market ratio, beta seemed to have no power to explain average security returns

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

39. Semi-Strong Tests: Market Anomalies
Post-Earnings Announcement Drift
Ball and Brown (1968) , sluggish response of stock prices to firms’ earnings announcements
News content of an earning announcement be evaluated, by comparing the announcement of actual earnings to the value previously expected by market participants. The difference is the earnings surprise.
Rendleman. etc (1982), divide firms into 10 deciles based on the size of the surprise, calculate CAR.
Correlation between ranking by earnings surprise and CAR. There is a large abnormal return on the earnings announcement day
Market appears to adjust to the earnings information only gradually, a sustained period of abnormal returns (concerning stock price movement after the announcement date)
CAR of positive surprise stocks continue to risk (momentum)
negative surprise firms continue to suffer negative abnormal returns

40. Cumulative Abnormal Returns in Response to Earnings Announcements

41. Strong-Form Tests: Inside Information
The ability of insiders to trade profitability in their own stock has been documented in studies by Jaffe, Seyhun, Givoly, and Palmon
SEC requires all insiders to register their trading activity
Once publish the summary of the insider trades, the trades become public information, if markets are efficient, fully and immediately processing the information, should no profit from following the trades

42. Interpreting the Evidence
How to interpret the ever-growing anomalies literature (P/E effect, small-firm, market-to- book, momentum, long-term reversal effects)
Related phenomena

43. Interpreting the Evidence
Risk Premiums or market inefficiencies— disagreement here
Fama and French (1993)argue that these effects can be explained as manifestations of risk premium ( higher betas, higher returns), three-factor model
Size or B/M ratios are not risk factors, but may act as proxies for more fundamental determinants of risk, there consistent with an efficient market in which expected returns are consistent with risk
Lakonishok etc (1995)argue that these effects are evidence of inefficient markets, systematic errors in the forecast of stock analysts
Extrapolate past performance too far into the future, overprice firms with recent good performance and underprice firms with recent poor performance

44. Interpreting the Evidence
Anomalies or Data Mining
Rerun the computer database of past returns over and over and examine stock returns along enough dimensions:
Simple chance may cause some criteria to appear to predict returns
Some anomalies have not shown much staying power after being reported in the academic literature, such as small-firm effect, B/M

45. THE NOISY MARKET HYPOTHESIS AND FUNDAMENTAL INDEXING
EMH, in favor of capitalization-weighted indexed portfolios that provide broad diversification with minimal trading costs
Noisy market hypothesis
Market prices may well contain pricing errors or noise relative to the intrinsic value.
Indexed portfolios invest in proportion to market capitalization, weights will track the pricing errors, with greater amounts invested in overpriced stocks
Fundamental indexing
Invests in proportion to intrinsic value would avoid the problem

46. What Does the Evidence Show?
Technical Analysis
Short horizon
Long horizon
Fundamental Analysis
Anomalies Exist

47. Anomalies Small Firm Effect (January Effect) Neglected Firm
Market to Book Ratios
Reversals
Post-Earnings Announcement Drift