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Efficient markets
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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.

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Efficient markets


The efficient market hypothesis

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

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

The random walk

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.

Test of return predictability

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

January and size effect

January and Size Effect

Explanations of january effect

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

Test of return predictability1

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

Test of return predictability2

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

Correlation tests

Correlation Tests

  • A regression of the following model:

Correlation tests1

Correlation Tests

Weekly correlation coefficients

Weekly Correlation Coefficients

Runs tests

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.

Runs tests1

Runs Tests

Announcement and price return

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.

Methodology of event studies

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.

Methodology of event studies1

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

Methodology of event studies2

Methodology of Event Studies

Methodology of event studies3

Methodology of Event Studies

Results of some event studies

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.

Results of some event studies1

Results of Some Event Studies

Results of some event studies2

Results of Some Event Studies

Strong form efficiency

Strong Form Efficiency

  • Insider Trading

  • Information in Analysts’ Forecasts

  • Mutual Fund Performance

Market rationality

Market Rationality

  • Volatility Tests

  • Winners-Losers

  • Market Crash of October 1987

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