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EFFICIENT MARKET THEORY.pptx

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EFFICIENT MARKET THEORY.pptx

  1. 1. Introduction Market Efficiency Informational Efficiency Operational Efficiency
  2. 2. Definition of Efficient Markets  An efficient capital market is a market that is efficient in processing information.  We are talking about an “informationally efficient” market, as opposed to a “transactionally efficient” market. In other words, we mean that the market quickly and correctly adjusts to new information.  In an informationally efficient market, the prices of securities observed at any time are based on “correct” evaluation of all information available at that time.  Therefore, in an efficient market, prices immediately and fully reflect available information.
  3. 3. Definition of Efficient Markets (cont.)  Professor Eugene Fama, who coined the phrase “efficient markets”, defined market efficiency as follows:  "In an efficient market, competition among the many intelligent participants leads to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future. In other words, in an efficient market at any point in time the actual price of a security will be a good estimate of its intrinsic value."
  4. 4. Efficient Market  Stock prices fully reflect available information  Developed by Professor Eugene Fama  Argues that stocks trade at their fair value  Impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices  Only way an investor can possibly obtain higher returns is by purchasing riskier investments
  5. 5. Strong Form Efficient Markets Semi Strong Form Efficient Markets Weak Form Efficient Markets All information is reflected on prices All Public information is reflected on security prices All Historical information is reflected on security prices Variants of the Hypothesis
  6. 6. Weak Form of EMH  Historical Prices used  Current prices reflect all information found in the past prices and trade volumes.  Future prices cannot be predicted by analyzing prices from past  Technical analysis techniques do not provide excess returns, fundamental analysis in some form may still provide some returns  Share prices exhibit no serial dependencies (there are no patterns to asset prices)
  7. 7. The Random Walk Theory  Maurice Kendall : stock prices followed a random walk, each successive change is independent of the previous one.  Academic researchers : the randomness of stock prices was the result of an efficient market.
  8. 8. Semi Strong Form of EMH  Prices fully reflect all publicly available information (economic news, political news, annual report) and expectations about the future  Prices adjust rapidly to new information  Old information cannot be used to earn superior returns  Neither technical analysis nor fundamental analysis provide excess returns
  9. 9. Strong Form of EMH  Prices fully reflect all information whether publicly available or not.  Private information is available with companies but is not disclosed.  No one can earn superior returns.
  10. 10. Testing the Form of Market efficiency
  11. 11. Empirical Tests for Weak Form of Market efficiency Filter Rule Runs Test Serial Correlation
  12. 12. Serial Correlations  The following chart shows the relationship (there is none) between S&P 500 returns each month and the returns from the previous month. Data are from Feb. 1950 to Sept. 2001.  Note that the R2 is virtually 0 which means that knowing last month’s return does you no good in predicting this month’s return.  Also, notice that the trend line is virtually flat (slope = 0.008207, t-statistic = 0.2029, not even close to significant)  The correlation coefficient for this data set is 0.82%
  13. 13. Serial Correlations (cont.) Unlagged vs One-month Lagged S&P 500 Returns y = 0.008207x + 0.007451 R 2 = 0.000067 -30.00% -20.00% -10.00% 0.00% 10.00% 20.00% -30.00% -20.00% -10.00% 0.00% 10.00% 20.00% One-month Lagged Returns Unlagged Returns
  14. 14. Tests of the Semi-strong Form  Fama, Fisher, Jensen & Roll  Event Studies  Stock splits  Earnings announcements  Analysts recommendations  Cross-Sectional Return Prediction  Firm size  BV/MV  P/E
  15. 15. Empirical Evidence of strong form of Efficiency  Mutual Fund performances.  Difference in return of informed buyer and naïve buy- and-hold approach is not much.  Not able to forecast returns properly even after getting the information.
  16. 16. Types of market efficiency Types of Efficiency Reflect What works What does not work Strategy to be used Weak Form Past Price and Volume Fundamental Analysis & Insider Information Technical Analysis Active portfolio management Strategy Semi Strong Form Past Price, Volume & Publically held information Insider Information Fundamental Analysis & Technical Analysis Passive portfolio management Strategy Strong Form Past Price, Volume, Publically and privately held information Nothing Fundamental Analysis, Technical Analysis & Insider Information Passive portfolio management Strategy
  17. 17. Market Inefficiencies  Market prices of common stocks are not always accurately priced.  Opposes efficient market hypothesis.  Drives asset above or below their true value.  Example Dotcom bubble, recent market crashes.
  18. 18. Anomalies  Anomalies are unexplained empirical results that contradict the EMH:  The Size effect.  The “Incredible” January Effect.  P/E Effect.  Day of the Week (Monday Effect : Average closing price of Monday is lower than average closing price of Friday).  PEG Ratio Effect  P/B ratio effect  Dividend yield Effect
  19. 19. The Size Effect  Beginning in the early 1980’s a number of studies found that the stocks of small firms typically outperform (on a risk-adjusted basis) the stocks of large firms.  This is even true among the large-capitalization stocks within the S&P 500. The smaller (but still large) stocks tend to outperform the really large ones.  Greater amount of growth and opportunities.  More volatility.
  20. 20. The “Incredible” January Effect  Stock returns appear to be higher in January than in other months of the year.  This may be related to the size effect since it is mostly small firms that outperform in January.  It may also be related to end of year tax selling.
  21. 21. The P/E Effect  It has been found that portfolios of “low P/E” stocks generally outperform portfolios of “high P/E” stocks.  This may be related to the size effect since there is a high correlation between the stock price and the P/E.  It may be that buying low P/E stocks is essentially the same as buying small company stocks.  Historical data of PE ratios helps in generating superior returns.  Contradicts semi strong form of efficient market hypothesis.
  22. 22. The Day of the Week Effect  Based on daily stock prices from 1963 to 1985 Keim found that returns are higher on Fridays and lower on Mondays than should be expected.  This is partly due to the fact that Monday returns actually reflect the entire Friday close to Monday close time period (weekend plus Monday), rather than just one day.  Moreover, after the stock market crash in 1987, this effect disappeared completely and Monday became the best performing day of the week between 1989 and 1998.
  23. 23. Review  The Efficient Market Hypothesis  Types of Efficiency  Degrees of Informational Efficiency  The Semi-Efficient Market Hypothesis  Security Prices and Random Walks  Anomalies  The Low PE Effect  Low-Priced Stocks  The Small Firm and Neglected Firm Effects  Market Overreaction  The January Effect  The Weekend Effect  The Persistence of Technical Analysis 
  24. 24.  The persistence of technical analysis: If the EMH is true, technical analysis should be useless. Each year however, an immense amount of literature based in varying degrees on the subject is printed.
  25. 25. Thank You

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