Chapter 10

1. Chapter 10 Market Efficiency

2. Warren Buffet • "I'd be a bum on the street with a tin cup if the markets were always efficient" • ….”Observing correctly that the market was frequently efficient, they went on to conclude incorrectly that it was always efficient."

3. Learning Objectives • Explain the concept of efficient markets. • Describe the three forms of market efficiency – weak, semi-strong, and strong • Discuss the evidence regarding the Efficient Market Hypothesis. • State the implications of market efficiency for investors. • Outline major exceptions to the Efficient Market Hypothesis.

4. Efficient Markets • How well do markets respond to new information? • Should it be possible to decide between a profitable and unprofitable investment given current information? • Efficient Markets • The prices of all securities quickly and fully reflect all available information

5. Conditions for an Efficient Market • Large number of rational, profit-maximizing investors • Actively participate in the market • Individuals cannot affect market prices • Information is costless, widely available • Information is generated in a random fashion • Investors react quickly and fully to new information

6. Consequences of Efficient Market • Quick price adjustment in response to the arrival of random information makes the reward for analysis low • Prices reflect all available information • Price changes are independent of one another and move in a random fashion • New information is independent of past

7. Market Efficiency Forms • Efficient market hypothesis • To what extent do securities markets quickly and fully reflect different available information? • Three levels of Market Efficiency • Weak form - market level data • Semi-strong form - all public information • Strong form - all information, both public and private

8. Cumulative Levels of Market Efficiency and the Information Associated with Each Strong Form All Information Semi-Strong Form Public Information Weak Form Market Data

9. Weak Form • Prices reflect all past price and volume data • Technical analysis, which relies on the past history of prices, is of little or no value in assessing future changes in price • Market adjusts or incorporates this information quickly and fully

10. Semi-Strong Form • Prices reflect all publicly available information • Investors cannot act on new public information after its announcement and expect to earn above-average, risk-adjusted returns • Encompasses weak form as a subset

11. Strong Form • Prices reflect all information, public and private • No group of investors should be able to earn abnormal rates of return by using publicly and privately available information • Encompasses weak and semi-strong forms as subsets

12. Evidence on Market Efficiency • Keys: • Consistency of returns in excess of risk • Length of time over which returns are earned • Economically efficient markets • Assets are priced so that investors cannot exploit any discrepancies and earn unusual returns • Transaction costs matter

13. Weak-Form Evidence • Test for independence (randomness) of stock price changes • If independent, trends in price changes do not exist • Overreaction hypothesis and evidence • Test for profitability of trading rules after brokerage costs • Simple buy-and-hold better

14. Weak-Form EMH • Mostly supportive of weak-form EMH • E.g. technical trading rules have not consistently outperformed the market on average • Runs tests • looking for patterns in signs of returns • i.e. + + - + - + • Filter rules • sell after falls a certain % or buy after rises a certain %

15. Two Apparent Contradictions to the Weak-Form EMH • Momentum or persistence in stock returns • tendency of stocks that have done well over the past 6 to 12 months to continue to do well over the next 6 to 12 months • “Contrarian” Strategies • stocks that have done well over the past 3-5 year period, will do poorly over the subsequent 3-5 year period

16. Semi-Strong-Form Evidence • Event studies • Empirical analysis of stock price behaviour surrounding a particular event • Examine company unique returns • The residual error between the security’s actual return and that given by the index model • Abnormal return (Arit) = Rit - E(Rit) n • Cumulative abnormal return (CAR) = ΣArit t=1

17. Semi-Strong-Form Evidence • Stock splits • Implications of split reflected in price immediately following the announcement • Accounting changes • Quick reaction to real change in value • Initial public offerings • Only issues purchased at offer price yield abnormal returns • Announcements and news • Little impact on price after release

18. Professional Portfolio Manager Performance • Substantial evidence that they do not outperform the market (or earn abnormal risk-adjusted returns) over the long run • Based on fund averages • Based on persistence in manager performance (evidence on this point is weaker)

19. Strong-Form Evidence • Test performance of groups which have access to nonpublic information • Corporate insiders have valuable private information • Evidence that many have consistently earned abnormal returns on their stock transactions • Insider transactions must be publicly reported

20. Implications of Efficient Market Hypothesis • What should investors do if markets are efficient? • Technical analysis • Not valuable if weak-form holds • Fundamental analysis of intrinsic value • Not valuable if semi-strong-form holds • Experience average results

21. Implications of Efficient Market Hypothesis • For professional money managers • Less time spent on individual securities • Passive investing favoured • Otherwise, must believe in superior insight • Tasks if markets informationally efficient • Maintain correct diversification • Achieve and maintain desired portfolio risk • Manage tax burden • Control transaction costs

22. Market Anomalies • Exceptions that appear to be contrary to market efficiency • Earnings announcements affect stock prices • Adjustment occurs before announcement, but also significant amount after • Contrary to efficient market hypothesis because the lag should not exist

23. Market Anomalies • Low P/E ratio stocks tend to outperform high P/E ratio stocks • Low P/E stocks generally have higher risk-adjusted returns • But P/E ratio is public information • Should portfolio be based on P/E ratios? • Could result in an undiversified portfolio

24. Market Anomalies • Size effect • Tendency for small firms to have higher risk-adjusted returns than large firms • January effect • Tendency for small firm stock returns to be higher in January • Of 30.5% small-size premium, half of the effect occurs in January

25. Market Anomalies • Value Line Ranking System • Advisory service that ranks 1,700 stocks from best (1) to worst (5) • Probable price performance in next 12 months • 1980-1993, Group 1 stocks had annualized return of 19.3% • Best investment letter performance overall • Transaction costs may offset returns

26. Conclusions about Market Efficiency • Support for market efficiency is persuasive • Much research using different methods • Also many anomalies that cannot be explained satisfactorily • Markets very efficient, but not totally • To outperform the market, fundamental analysis beyond the norm must be done

27. Conclusions about Market Efficiency • If markets operationally efficient, some investors with the skill to detect a divergence between price and semi-strong value earn profits • Excludes the majority of investors • Anomalies offer opportunities • Controversy about the degree of market efficiency still remains

28. The (Mis)Behavior of Markets “Efficient Markets theory is elegant but flawed, as anyone who lived through the booms and busts of the 1990s can now see. The old financial orthodoxy was founded on two critical assumptions in Bachelier’s key model: Price changes are statistically independent, and they are normally distributed. The facts, as I vehemently argued in the 1960s and many economists now acknowledge, show otherwise.” Benoit Mandelbrot

29. Motivation • The Gaussian paradigm of independent normally distributed asset returns has been challenged: On daily data 7 std events are 10, 000,000 times more frequently than random data • Modeling financial price variations accurately is an essential step in engineering risk management techniques, portfolio optimization, derivative pricing, fund management and trading. • Where should I start? →extreme events, crashes

30. Studying Extremes • Markets as complex dynamical systems reveal their properties better in extremes • Extreme Value Theory is an emerging discipline of statistics for extreme events and statistical analysis of data showing clear non-normal behavior • Aims to characterize extreme events • Focus is on the tails of the data