1. Slides by: Pamela L. Hall, Western Washington University Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies1 Efficient Capital Markets and Anomalies Chapter 8

2. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 2 Background  If investors ignore information, market prices of securities will not react to news announcements  Security prices that do not fully reflect public information are said to be weakly efficient prices –A weakly efficient price drifts further away from the security’s value than a semi-strongly efficient price  Good investors can use these inefficiencies to earn trading profits

3. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 3 Background  A perfectly efficient price reflect all knowable information about the security –Always equal to the security’s value Value can change continuously to reflect arrival of new information  Good financial analysts that are active traders will be unable to earn returns sufficient to compensate them for their costs and still yield an economic profit in a perfectly efficient market –All securities are priced correctly

4. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 4 Background  This chapter examines security price behavior and pricing inefficiencies –Pricing inefficiencies provide profit opportunities Levels of pricing efficiency –Weakly Efficient Market Hypothesis »Market prices reflect all historical information –Semi-strong Efficient Market Hypothesis »Market prices reflect all public information (including all historical information mentioned above) –Perfectly (or Strong) Efficient Market Hypothesis »Market prices reflect everything that is knowable, including inside information

5. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 5 Background  Security prices should not move along smoothly –Rapid price movements due to new information should cause randomness in successive price changes, not a smooth continuity Randomness means that a trend-like series of small upward or downward prices moves is not likely to occur –If a price change is to happen, it should happen all at once, not in a series of small movements

6. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 6 Background Trading Days Market Price, $ t Over-reaction Efficient Learning Lag Over-reaction Efficient Learning Lag New information arrives in the market on day t. Bad News Good News

7. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 7 Background  This chapter offers both evidence supporting the hypotheses and anomalies  You should reach a conclusion about whether you believe each of the three hypotheses –Your conclusions will help determine the way you invest If, for example, you believe all three hypotheses, you should be a passive investor who trades infrequently

8. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 8 Evidence Supporting Weakly Efficient Hypothesis  Is it possible that security prices do not reflect all historical information? –Which is easy to obtain and cheap  Technicians focus on past security prices –Look for meaningful trends in historical security prices –Attempt to extract predictions from whatever patterns they find

9. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 9 Filter Rules  An X% filter is a mechanical trading rule –If a security’s price rises by at least X%, buy and hold until the price peaks and falls by at least X% –When price decreases from a peak level by X%, liquidate long position and sell short –Hold short position until price reaches a low point and then begins to rise –If (when) the price rises above X%, cover the short position and go long

10. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 10 Filter Rules  Different filter rules can be testing by changing the X value  If stock prices fluctuate randomly, filter rules should not outperform randomly chosen stocks

11. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 11 Figure 8-2: Using a 10% Filter Rule to Trade a Security

12. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 12 Filter Rules  Filters ranging from.05% to 50% have been tested  In general, filter rules generate large commissions (especially those with small X values) –After deducting for commissions, filter rules do not outperform naïve buy-and-hold strategy –Some filters result in large net losses after deducting commissions

13. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 13 Serial Correlation Tests  Serial correlation (autocorrelation) tests should be able to determine if security prices move in trends or reversals –Measures the correlation coefficient in a series of numbers with lagged values in the same series Lags of any length can be used  Stock prices exhibit a long-run upward trend of about 6.6% a year in the U.S. –Thus, some positive serial correlation is found But, technical analysts focus on short-term trends

14. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 14 Serial Correlation Tests  So, do daily or weekly price change trends exist and, if so, can they be used to earning a trading profit after commission? –Many studies have failed to detect statistically significant serial correlations on a daily, weekly or monthly basis Scientific evidence supporting weak form efficiency

15. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 15 Serial Correlation Tests  Some conflicting evidence exists –DeBondt & Thaler (1985) find evidence of long- term stock price overreaction and negative serial correlation for individual stocks –Lo & MacKinlay (1988) found positive serial correlation for a diversified portfolio of stocks –Conrad & Kaul (1993) suggest that the above results are due to statistical measurement errors

16. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 16 Runs Tests  Perhaps security prices change randomly most of the time but occasionally exhibit trends that the serial correlations tests cannot detect  A “runs” test can be performed to determine if irregular trends occur in price changes –A run occurs when the changes between consecutive numbers switch direction

17. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 17 Runs Tests  A series of random numbers is expected to generate a certain amount of positive, negative or zero runs –By comparing the actual number of runs to the expected number, we can determine if a non-random number of runs occurred Results suggest that actual number of runs do not differ statistically from the number of expected runs

18. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 18 Anomalies in Weakly Efficient Hypothesis  While most of the scientific evidence supports the weakly efficient hypothesis, some anomalous evidence exists –Day-of-the-Week Effects—the stock market tends to fall on Mondays and rise the rest of the week Monday’s returns are calculated from Friday’s closing price to Monday’s closing price; thus this is also known as the weekend effect –Most of Monday’s negative returns occur in the first hour of trading –This day-of-the-week pattern is observed in stock markets around the world

19. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 19 Anomalies in Weakly Efficient Hypothesis –Holiday effect Returns on the day before holiday weekends are 9 – 13 times higher than the average daily return –About 1/3 of the average stock’s annual return was earned in pre-holiday trading days –Friday to Monday Negative (positive) returns on a Friday are usually followed by large negative (positive) returns on Monday  The large commissions paid (relative to the small positive daily returns) will more than offset the potential benefit of this knowledge

20. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 20 Anomalies in Weakly Efficient Hypothesis –January Effect—average stock’s return in January is more than 5 times the mean monthly return A large part of the typical stock’s annual return is generated during January –This is a larger anomaly than the day-of-the-week effects –Can yield net trading profits after deducting transaction costs »Buy stocks before Christmas and sell at the end of January

21. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 21 Anomalies in Weakly Efficient Hypothesis Reasons for the January Effect –Perhaps investors are selling stocks in December to establish tax losses »Reinvesting in the market in January is fueling the effect January Effect is even stronger internationally than within the U.S.

22. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 22 Figure 8-5: Monthly Average Returns from Stock Markets Around the World for January and the Other 11 Months

23. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 23 Tests of Semi-Strong Efficiency  Most semi-strong tests utilize an event study –Event studies focus on a specific news event Observe security prices to determine if they react rationally when the event becomes public knowledge –If prices react quickly and efficiently, this supports semi-strong hypothesis

24. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 24 Reactions to Federal Announcements  Public announcements to macroeconomic statistics typically occur at scheduled times –U.S. government keeps statistics secret until the precise moment of the public announcement Many of the announcements are made when the financial markets are closed –If the statistics contain valuable new information the markets react immediately and continuously until the new information is impacted into security prices

25. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 25 Reactions to Federal Announcements  Gwilym, Buckle, Clarke and Thomas (GBCT) analyzed Financial Times Stock Exchange 100 stocks price index and the Short Sterling 3-Month Interest rate futures contracts on a transaction-by- transaction basis –Examine announcement windows beginning two minutes prior to a public announcement and ending 10 minutes after the announcement Both the stock market and the bond market remain at normal levels during the two minutes prior to announcement –Suggests no information leakage Within the first 15 seconds after the announcement, volatility increases but drops within six minutes after the announcement –Larger price changes initially but the price changes become gradually smaller

26. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 26 About Information and Market Prices  Stock price reactions to corporate-specific announcements are slower than federal government announcements –Fewer investors focus on corporate-specific announcements –Corporations do not announce information at precise pre- scheduled times  Studies show that stock prices take about 14 minutes to begin adjusting to corporate earnings announcements and there are no opportunities for profitable trading after 30 minutes  Results indicate that the financial markets adjust to new information quickly –In minutes and seconds (for industrialized nations) rather than days or weeks

27. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 27 Stock Splits and Stock Dividends  Neither of these events change the total value of the firm or investor’s wealth  Offer a nice way to test the semi-strong efficient market hypothesis  A two-for-one stock split (or a 100% stock dividend) will leave the firm with twice as many shares of stock with each share being worth half as much –If security markets are efficient, the firm’s market capitalization should not be impacted by a stock split or stock dividend

28. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 28 Stock Splits and Stock Dividends  Why do companies offer stock dividends and splits? –Information signaling hypothesis Companies can conserve cash while sending a signal to the public about future earnings growth –Liquidity hypothesis Reduces the stock’s market price making it more affordable to small investors

29. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 29 Stock Splits and Stock Dividends  Fama, Fisher, Jensen and Roll (1969) studied 940 stock splits and stock dividends –Calculated a characteristic line for each stock analyzed and examined the residual errors If residual error at time of event was zero, the security’s actual rate of return equaled the predicted rate of return, and the event had no impact on the return If residual error were positive (negative) the asset’s return was greater (lower) than expected Residual errors were averaged over the 940 stocks –Reduces the influence of other effects (events)

30. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 30 Stock Splits and Stock Dividends  FFJR find that the monthly residual error tended to be increasingly positive in the 30 months preceding the split or stock dividend  After the event the average residuals fluctuate around zero for the next 30 months  They evaluated the cumulative average monthly residuals when companies subsequently –Increased their cash dividend payments Have small positive residuals in the months after the event –Decreased their cash dividend payments Have larger negative residuals in the months after the event

31. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 31 Stock Splits and Stock Dividends  In the long-run, stock splits and stock dividends do not seem to impact –The liquidity of the split stocks –The market value of the firm –Investors’ returns  If an investor can correctly predict which companies are going to split, it may be possible to earn excess returns  Studies involving stock splits and stock dividends appear to support the semi-strong efficient market hypothesis

32. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 32 Anomaly: Size Effect  Banz (1981) & Reinganum (1981) show that small company stocks earned higher rates of return than large company stocks, on average –Size based on market capitalization  Found that small cap stocks were also riskier, but even after adjusting for risk the size effect remained  Even after adjusting for the impact of infrequent price changes the size effect remained

33. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 33 Inter-Relationship Between January and Size Effects  Keim (1983) found that abnormal returns in February through December tend to be similar –But, small firms experience a positive January effect while large firms experience a negative January effect Why this occurs is unknown  This appears to be a worldwide phenomenon

34. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 34 Growth-Value Anomaly  Semi-strong form of EMH suggests that money managers who use a particular management style should not consistently outperform managers using another management style –Value managers Seek undervalued stocks which they purchase, hold and sell when the price reaches the stock’s value –Typically buy stocks with low P-E ratios, below average earnings growth rates, high cash dividend yields and low price- to-book values –Growth manager Seek stocks enjoying a high rate of earnings growth which is expected to continue –Typically buy stocks with high P-E ratios, high Price-to-book values and low cash dividend yields

35. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 35 Growth-Value Anomaly  Both of these management styles are popular and are frequently compared –Value stock investors have historically outperformed growth stock investors on a risk-adjusted basis over extended periods of time Growth managers seem to over-estimate growth rates and therefore receive lower returns

36. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 36 Growth-Value Anomaly  Investors can analyze three different ratios to make quantitative distinctions between growth and value stocks –Current yield = cash dividend per share  market price per share –Growth rates in earnings –Price-earnings ratios

37. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 37 Price-to-Book Ratio  Fama and French (1992) analyzed only the Price-to-Book ratio to distinguish between value and growth stocks –Price-to-book ratio = market price of stock  book value of stock  Examined  2,000 firms and divided the sample into deciles –Lowest P/B decile contains value stocks while highest P/B decile contains growth stocks  Lakonishok, Schleifer and Vishny (1994) find the P/B anomaly persists even after adjusting for firm size  Loughran (1997) finds the P/B ratio does not have predictive power for large firms and that growth firms outperform value firms when considering value-weighted return by P/B quintiles

38. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 38 Figure 8-11: Companies’ Average Returns for Each P/B Decile, 1962-89 Earned more than twice the average return of the portfolio in Decile One.

39. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 39 SP/BARRA Growth and Value Index Funds  Vanguard started two new funds in 1992 based on P/B ratios –SP/BARRA Growth Fund contains those firms in the S&P500 with high P/B ratios –SP/BARRA Value Fund contains those firms in the S&P500 with low P/B ratios  Funds are rebalanced semi-annually –The SP/BARRA Value Index has offered superior long-run performance over the SP/BARRA Growth Index However, there are periods when the Growth Index outperformed the Value Index

40. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 40 Growth vs. Value Investing  Capaul, Rowley and Sharpe (1993) analyzed a similar investing strategy on an international level –Find that value investing seems to outperform growth investing  Constitutes an anomaly to the semi- strong form of efficient market hypothesis

41. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 41 Tests of Strong Form Efficiency  Mutual funds are managed by professional money managers –Do these funds offer superior performance? Findings –Large funds perform no better than small funds –Funds with high turnover perform slightly worse than funds with low turnover –Funds charging a load fee perform slightly worse than no-load funds –Funds with high management fees perform slightly worse than funds with low management fees –Majority of equity mutual funds in U.S. are unable to outperform S&P500 Burton Malkiel concludes that most investors would be better off selecting an index fund with low fees rather than trying to select a ‘hot’ active fund manager

42. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 42 Tests of Strong Form Efficiency  Inside information –An insider is defined as Any corporate director Any one owning 10%+ of the firm’s equity shares Any executive in corporation with access to non-public information about the corporation Any insider or outsider using material non-public information (obtained in a breach of fiduciary trust) to trade a corporation’s securities –Within the U.S., the SEC does not allow insiders to keep profits earned from trading corporate stock held less than six months Also does not allow insider to sell stock short Also requires full disclosure of dealings which is then released to the public –Weekly Insider Report (Vickers Stock Research Corp.) –Value Line Investment Survey –www.InsiderScores.com (free)www.InsiderScores.com –www.InsiderTrader.com (free)www.InsiderTrader.com

43. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 43 Insider Trading  Even outsiders receiving tips from insiders can be prosecuted for insider trading  Insider Trading Sanctions Act of 1984 and Securities Fraud Enforcement Act of 1988 provide for –Penalties of three times any damages that might have been caused –Fines up to $1,000,000 –Up to 10 years imprisonment

44. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 44 Tests of Strong Form Efficiency  Do insiders earn statistically significant trading profits? –Jaffe (1974) performed an event study If a security had three or more net insiders as buyers (sellers) Jaffe assumed a balance of favorable (unfavorable) inside information existed for that corporation Results indicate that the average insider did not earn enough after one month to pay their commission costs –After 8 months the average insiders gained 5.07%

45. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 45 Tests of Strong Form Efficiency –Seyhun (1986) finds that Jaffe’s estimates of insider profits may have been too high Also examines outsiders trading on purchased information about insider trades –Unable to earn net profits after commissions –Meulbroek (1992) analyzed 229 episodes of insider trading Finds abnormal returns of 3.06% on average, on the day of the trade –Provides support for claim that insider trading helps stock prices reflect all knowable information because on the inside trading day, the stock prices moved to incorporate the new information »Many financial economists argue that insider trading should be legalized

46. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 46 The Bottom Line  Your informed opinion on market pricing efficiency will determine the way you manage your investments –If you believe market anomalies are insignificant, you will not search for over- or under-valued securities  You may decide that some anomalies exist but cannot be used in any practical sense –For instance, if you bought small stocks before the Christmas holiday and held them through the end of January, you could expect to benefit from the holiday effect, the small stock effect and the January effect However, this is likely to amount to only very small abnormal returns and the effects you hope to capitalize upon may not occur this year

47. Francis & IbbotsonChapter 8: Efficient Capital Markets and Anomalies 47 The Bottom Line  Several well-documented anomalies force us to conclude that the market is not perfectly efficient –How should investors manage money given that, while securities markets are not perfectly efficient, they are highly efficient? Millions of investors select passive investing because they believe the anomalies are small Million of investors select active investing because they think the anomalies offer the opportunity for profitable trading Still others combine the above methods