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1. Market Efficiency. . 1. The Efficient Market Model. DefinitionsAllocationally efficient marketsinformational (external) efficiency: prices capture all information All investors have costless access to currently available information about the futureAll investors are capable analystsAll inves
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1. Part 4: Market Behavior Research
2. 1. Market Efficiency
3. 1. The Efficient Market Model Definitions
Allocationally efficient markets
informational (external) efficiency: prices capture all information
All investors have costless access to currently available information about the future
All investors are capable analysts
All investors pay close attention to market prices and adjust their holdings appropriately
Fair game:
where
operational (internal) efficiency: low transactions cost
4. Why worry about efficiency?
Optimal asset allocation
Prices are signals which determine resource allocation in a market economy
Efficient prices are high-quality signals
For allocations to be optimal the prices should be efficient
Also, to encourage many small investors to become market participants, prices should be perceived as fair
Competition
Once information becomes available, market participants analyze it and trade on it
Markets can be efficient only if a large number of people disagree with the EMH and attempt to find ways of earning speculative profits.
While a return on a security is expected (due to risk) the long run abnormal return is zero.
There is a 50% chance of earning a positive abnormal return.
Therefore speculation is a zero-sum game.
The efficient market represents a fair game
5. Role of portfolio management
Active management
Security analysis: Identifying mis-priced stocks
Timing: Changing allocations between the risky and risk-free assets at the right times
Requires information that is not known by all investors (information gathering can be expensive)
Passive Management
Buy and Hold: Form a well-diversified portfolio and dont change the composition of the portfolio
Index Funds: A convenient vehicle for passive portfolio management
Even in an efficient market, a role exists for portfolio management
Allocations to suit the desired level of risk
Portfolios to suit various investors tax considerations (e.g. capital gains as opposed to dividends)
Portfolios tailored to age groups (e.g. short-term debt instruments for the retired and elderly)
6. Random Walk with Positive Trend
7. Forms of the EMH (Fama,1970)
Weak form
Prices reflect information contained in past prices
Price changes (returns) should be uncorrelated
Future prices cannot be predicted using information contained in past prices
e.g. if market is not weak form efficient, profitable trading opportunities can be discovered through technical analysis
Evidence using tests based on trading rules and return autocorrelations is largely supportive of the weak form of the EMH in U.S.
Semi-strong form
Prices reflect all public information
earnings announcements
publicly available financial information
product announcements, etc.
e.g. if market is not semi-strong form efficient, profitable trading opportunities can be discovered through fundamental analysis
The evidence is generally supportive of the semi-strong form of the EMH in U.S.
8. Strong form
Prices reflect all information, including insider information
e.g. if market is not strong form efficient, profitable trading opportunities can be found by trading on insiders information
The evidence clearly indicates:
insiders do earn abnormal returns
hence the need for insider trading regulation
Implication
In all cases the EMH is concerned with the conditions under which an investor can earn an excess profit on a security.
By excess profit we mean earnings over and above what is expected using for example
CAPM E(Ri) = RF + (E(Ri)-RF )?i
APT E(Ri) = RF +?1b1i + ?2b2i +
.
This is called an Abnormal Return given by ARi = Ri - E(Ri).
Efficiency does not mean that investments decisions can be made mindlessly.
9. Three Forms of Efficiency
10. 2. Testing For Market Efficiency Weak form evidence
Test of return predictability
Motivation:
In an efficient market we should not observe a seasonal pattern.
Methods:
Market Anomalies
Time (seasonal) patterns
Mondays phenomenon (Gibbons and Hess,1981; Harris,1986)
January effect (Fama,1991;Keim,1989;Reinganum,1983)
Correlation tests
Past return (Granger,1975)
Equilibrium return (Fama and MacBeth,1973;Galai,1977)
Portfolios
Firm characteristics (size effects, market to book, earnings price)
Market characteristics
Run tests
11. Testing some trading rule
Motivation:
If we follow a pre-defined trading rule on when to buy and sell, can we make abnormally high returns (Fama,1991)?
Methods:
Charts/Trading rules
Head and shoulders
Resistence and support
High-low
Symmetric triangle
Candle
Filter
Moving average
12. Evidences:
Roberts (1959) finds no evidence of patterns in stock price behavior
Conrad & Kaul (1988) find positive serial correlation in weekly NYSE stock returns, but it is too weak to lead to profits after transaction costs
Jegadeesh & Titman (1993) find that stocks exhibit a momentum property at the 3-12 month horizon, where good or bad recent performance continues
Conrad & Kaul (1998) test 120 momentum and contrarian trading strategies and find that most do not yield positive profits. However, they do find that momentum strategies at the 3-12 month horizon are generally able to yield statistically significant profits
15. Semi-strong form experiments
Event studies
Motivation:
examine how rapidly do security prices adjust to unexpected new events (an earnings announcement, government policy, etc).
Evidences:
IPOs
There is underpricing initially then poor returns afterward
Accounting information
Lifo to Fifo to Lifo to evidence is strong that the market adjusts to changes
Takeovers
market reacts quickly and often anticipates
13D files cause prices to jump
Seasoned Security Issues
new stock lowers the stock price immediately
new debt raises the stock price immediately
16. Seven steps in the Event Study:
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. Use daily data.
Define the period studied, e.g. 30 days (weeks, months) either side of the event.
For each firm compute the daily returns with market model approaches. [Rt = at + btRmt + et]
For each firm, compute the Abnormal Return for each asset. [et = Actual - (at + btRmt)]
Compute for each day the average abnormal return (AR) over all assets.
Compute the Cumulative Abnormal Return (CAR).
17. Figure IV.8 : Abnormal Returns
18. Figure IV.8 : Cumulative Abnormal Returns
19. Stock splits (Fama Fisher Jensen Roll ,1969)
Splits have no obvious effect on firm value
Maybe splits signal impending dividend increase
Issues in examining the results
Magnitude issue
Selection bias issue
Lucky event issue
Possible model misspecification
Strong form evidence
Assessing performance of professional managers
Motivation:
These test whether current publicly and/or privately available information is fully reflected in security prices and whether any type of investor (three groups: corporate insiders, security analysts and portfolio managers) can make an excess profit.
Evidences:
Although the first group can earn abnormal profits, the results on the ability of security analysts and portfolio managers to earn abnormal returns is mixed.
20. 4. Market Microstructure