1 / 24

EFFICIENT MARKETS

EFFICIENT MARKETS. The Efficient Market Hypothesis. Most tests of EMH: How fast information is incorporated in prices Not whether information is correctly incorporated in prices Weak Form Semi-strong Form Strong Form. Fair Game. Information set Φ t can not be used to earn excess return.

hewitt
Télécharger la présentation

EFFICIENT MARKETS

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. EFFICIENT MARKETS

  2. The Efficient Market Hypothesis • Most tests of EMH: • How fast information is incorporated in prices • Not whether information is correctly incorporated in prices • Weak Form • Semi-strong Form • Strong Form

  3. Fair Game • Information set Φt can not be used to earn excess return. • What is Φt? • Weak form: past history of stock prices, company characteristics, market characteristics, and the time of the year. • Semi-strong form: announcement of one or more pieces of information. • Strong form: all information

  4. The Random Walk • Visualize a roulette wheel. • Returns are IID over time. • Fair game does not require returns to be IID over time. • Random walk is a restricted version of the fair game.

  5. Test Of Return Predictability • Time Patterns in Security Returns • Returns are systematically higher or lower depending on the time of the day, the day of the week, and the month of the year. • Intraday and Day-of-the-Week Patterns: • Day-end effect. • Week-end effect. • Monthly Patterns: • Returns in January are substantially higher than return in other months (January effect). • Especially true for small stocks

  6. January and Size Effect

  7. Microstructure explanation (Keim, 1989): Last trade in December was primarily at the bid, and this tendency was more pronounced for small stocks. First trade in January was between bid and ask. Return to appear high in the first few days of January. Tax-selling hypothesis: Selling securities with substantial losses before the year end. This creates a tax loss which should cover more than transaction costs. Purchasing similar securities in early January. Explanations of January Effect

  8. Test Of Return Predictability • Predicting Return from Past Return • Short-term Predictability • Correlation Tests • Runs Tests • Filter Rules • Relative Strength • Very Short-term Correlation • Correlation for Portfolios of Securities

  9. Test Of Return Predictability • Correlation over Long-run Horizons • Returns and Firm Characteristics • The Size Effect • Market to Book • Earnings Price • Predicting Long-run Returns from Firm and Market Characteristics

  10. Correlation Tests • A regression of the following model:

  11. Correlation Tests

  12. Weekly Correlation Coefficients

  13. Runs Tests • A price increase  “+” • A price decrease  “-” • No change  “0” • A sequence of the same sign is a “run”. • + - - - +++ 0  4 runs • Correlation and runs tests seem to show small positive relationship between today’s and yesterday’s return, but on average it is very small, and frequently negative for individual securities.

  14. Runs Tests

  15. Announcement and Price Return • The greatest amount of research in finance has been devoted to the effect of an announcement on share price. • “Event Study”  how fast the information was incorporated in share price. • Dozens of studies confirm that share price reacted rapidly to announcements, and in expected direction of the price change.

  16. Methodology of Event Studies • Collect a sample of firms that had a surprise announcement (the event) • Determine the precise day of the announcement and designate this day as “zero” • Define the period to be studied • For each of the firms in the sample, compute the return on each of the days being studied.

  17. Methodology of Event Studies • Compute the “abnormal” return for each of the days being studied for each firm in the sample • Compute for each day in the even period the average abnormal return for all the firms in the sample. • Often the individual day’s abnormal return is added together to compute the cumulative abnormal return from the beginning of the period. • Examine and discuss the results

  18. Methodology of Event Studies

  19. Methodology of Event Studies

  20. Results of Some Event Studies • Market efficiency with respect to purchase or sale of securities announcement. • Whether analysts’ information could be used to earn excess returns of if it was already incorporated in share price. • Dividend and stock split announcement.

  21. Results of Some Event Studies

  22. Results of Some Event Studies

  23. Strong Form Efficiency • Insider Trading • Information in Analysts’ Forecasts • Mutual Fund Performance

  24. Market Rationality • Volatility Tests • Winners-Losers • Market Crash of October 1987

More Related