Market behavior research @ bec doms


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Market behavior research @ bec doms

  1. 1. Part 4: Market Behavior Research
  2. 2. 1. Market Efficiency
  3. 3. 1. The Efficient Market Model <ul><li>Definitions </li></ul><ul><ul><li>Allocationally efficient markets </li></ul></ul><ul><ul><li>informational (external) efficiency: prices capture all information </li></ul></ul><ul><ul><ul><li>All investors have costless access to currently available information about the future </li></ul></ul></ul><ul><ul><ul><li>All investors are capable analysts </li></ul></ul></ul><ul><ul><ul><li>All investors pay close attention to market prices and adjust their holdings appropriately </li></ul></ul></ul><ul><ul><ul><li>“ Fair game” : </li></ul></ul></ul><ul><ul><ul><li>where </li></ul></ul></ul><ul><ul><li>operational (internal) efficiency: low transactions cost </li></ul></ul>
  4. 4. <ul><li>Why worry about efficiency? </li></ul><ul><ul><li>Optimal asset allocation </li></ul></ul><ul><ul><ul><li>Prices are signals which determine resource allocation in a market economy </li></ul></ul></ul><ul><ul><ul><li>Efficient prices are high-quality signals </li></ul></ul></ul><ul><ul><ul><li>For allocations to be “optimal” the prices should be efficient </li></ul></ul></ul><ul><ul><ul><li>Also, to encourage many small investors to become market participants, prices should be perceived as “fair” </li></ul></ul></ul><ul><ul><li>Competition </li></ul></ul><ul><ul><ul><li>Once information becomes available, market participants analyze it and trade on it </li></ul></ul></ul><ul><ul><ul><li>Markets can be efficient only if a large number of people disagree with the EMH and attempt to find ways of earning speculative profits. </li></ul></ul></ul><ul><ul><ul><li>While a return on a security is expected (due to risk) the long run abnormal return is zero. </li></ul></ul></ul><ul><ul><ul><li>There is a 50% chance of earning a positive abnormal return. </li></ul></ul></ul><ul><ul><ul><li>Therefore speculation is a zero-sum game. </li></ul></ul></ul><ul><ul><ul><li>The efficient market represents a fair game </li></ul></ul></ul>
  5. 5. <ul><ul><li>Role of portfolio management </li></ul></ul><ul><ul><ul><li>Active management </li></ul></ul></ul><ul><ul><ul><ul><li>Security analysis: Identifying mis-priced stocks </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Timing: Changing allocations between the risky and risk-free assets at the right times </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Requires information that is not known by all investors (information gathering can be expensive) </li></ul></ul></ul></ul><ul><ul><ul><li>Passive Management </li></ul></ul></ul><ul><ul><ul><ul><li>Buy and Hold: Form a well-diversified portfolio and don’t change the composition of the portfolio </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Index Funds: A convenient vehicle for passive portfolio management </li></ul></ul></ul></ul><ul><ul><ul><li>Even in an efficient market, a role exists for portfolio management </li></ul></ul></ul><ul><ul><ul><ul><li>Allocations to suit the desired level of risk </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Portfolios to suit various investors’ tax considerations (e.g. capital gains as opposed to dividends) </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Portfolios tailored to age groups (e.g. short-term debt instruments for the retired and elderly) </li></ul></ul></ul></ul>
  6. 6. Random Walk with Positive Trend Security Prices Time
  7. 7. <ul><li>Forms of the EMH (Fama,1970) </li></ul><ul><ul><li>Weak form </li></ul></ul><ul><ul><ul><li>Prices reflect information contained in past prices </li></ul></ul></ul><ul><ul><ul><li>Price changes (returns) should be uncorrelated </li></ul></ul></ul><ul><ul><ul><li>Future prices cannot be predicted using information contained in past prices </li></ul></ul></ul><ul><ul><ul><li>e.g. if market is not weak form efficient, profitable trading opportunities can be discovered through technical analysis </li></ul></ul></ul><ul><ul><ul><li>Evidence using tests based on trading rules and return autocorrelations is largely supportive of the weak form of the EMH in U.S. </li></ul></ul></ul><ul><ul><li>Semi-strong form </li></ul></ul><ul><ul><ul><li>Prices reflect all public information </li></ul></ul></ul><ul><ul><ul><ul><li>earnings announcements </li></ul></ul></ul></ul><ul><ul><ul><ul><li>publicly available financial information </li></ul></ul></ul></ul><ul><ul><ul><ul><li>product announcements, etc. </li></ul></ul></ul></ul><ul><ul><ul><li>e.g. if market is not semi-strong form efficient, profitable trading opportunities can be discovered through fundamental analysis </li></ul></ul></ul><ul><ul><ul><li>The evidence is generally supportive of the semi-strong form of the EMH in U.S. </li></ul></ul></ul>
  8. 8. <ul><ul><li>Strong form </li></ul></ul><ul><ul><ul><li>Prices reflect all information, including insider information </li></ul></ul></ul><ul><ul><ul><li>e.g. if market is not strong form efficient, profitable trading opportunities can be found by trading on insider’s information </li></ul></ul></ul><ul><ul><ul><li>The evidence clearly indicates: </li></ul></ul></ul><ul><ul><ul><ul><li>insiders do earn abnormal returns </li></ul></ul></ul></ul><ul><ul><ul><ul><li>hence the need for insider trading regulation </li></ul></ul></ul></ul><ul><ul><li>Implication </li></ul></ul><ul><ul><ul><li>In all cases the EMH is concerned with the conditions under which an investor can earn an excess profit on a security. </li></ul></ul></ul><ul><ul><ul><li>By excess profit we mean earnings over and above what is expected using for example </li></ul></ul></ul><ul><ul><ul><ul><li>CAPM E(R i ) = R F + (E(R i )-R F )  i </li></ul></ul></ul></ul><ul><ul><ul><ul><li>APT E(R i ) = R F +  1 b 1i +  2 b 2i +…. </li></ul></ul></ul></ul><ul><ul><ul><ul><li>This is called an Abnormal Return given by AR i = R i - E(R i ). </li></ul></ul></ul></ul><ul><ul><ul><li>Efficiency does not mean that investments decisions can be made mindlessly. </li></ul></ul></ul>
  9. 9. Three Forms of Efficiency Semi-Strong Form Efficient Strong Form Efficient Weak Form Efficient
  10. 10. 2. Testing For Market Efficiency <ul><li>Weak form evidence </li></ul><ul><ul><li>Test of return predictability </li></ul></ul><ul><ul><li>Motivation : </li></ul></ul><ul><ul><ul><li>In an efficient market we should not observe a seasonal pattern. </li></ul></ul></ul><ul><ul><li>Methods : </li></ul></ul><ul><ul><ul><li>Market Anomalies </li></ul></ul></ul><ul><ul><ul><ul><li>Time (seasonal) patterns </li></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Mondays phenomenon (Gibbons and Hess,1981; Harris,1986) </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>January effect (Fama,1991;Keim,1989;Reinganum,1983) </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><li>Correlation tests </li></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Past return (Granger,1975) </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Equilibrium return (Fama and MacBeth,1973;Galai,1977) </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Portfolios </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Firm characteristics (size effects, market to book, earnings price) </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Market characteristics </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><li>Run tests </li></ul></ul></ul></ul>
  11. 11. <ul><ul><li>Testing some trading rule </li></ul></ul><ul><ul><li>Motivation : </li></ul></ul><ul><ul><ul><li>If we follow a pre-defined trading rule on when to buy and sell, can we make abnormally high returns (Fama,1991)? </li></ul></ul></ul><ul><ul><li>Methods : </li></ul></ul><ul><ul><ul><li>Charts/Trading rules </li></ul></ul></ul><ul><ul><ul><ul><li>Head and shoulders </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Resistence and support </li></ul></ul></ul></ul><ul><ul><ul><ul><li>High-low </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Symmetric triangle </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Candle </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Filter </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Moving average </li></ul></ul></ul></ul>
  12. 12. <ul><ul><li>Evidences : </li></ul></ul><ul><ul><ul><li>Roberts (1959) finds no evidence of patterns in stock price behavior </li></ul></ul></ul><ul><ul><ul><li>Conrad & Kaul (1988) find positive serial correlation in weekly NYSE stock returns, but it is too weak to lead to profits after transaction costs </li></ul></ul></ul><ul><ul><ul><li>Jegadeesh & Titman (1993) find that stocks exhibit a momentum property at the 3-12 month horizon, where good or bad recent performance continues </li></ul></ul></ul><ul><ul><ul><li>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 </li></ul></ul></ul>
  13. 13. Weak Form Evidence <ul><li>Random Walk Hypothesis </li></ul><ul><ul><li>where E (  t ) = 0 and Cov(  t  t-k ) = 0 so returns (price changes) are independent </li></ul></ul><ul><ul><li>empirical question is whether returns are serially correlated, Cov(R t , R t-1 )  </li></ul></ul><ul><li>Short Horizon Correlations </li></ul><ul><ul><li>Fama (1965) find zero serial correlation </li></ul></ul><ul><ul><li>Conrad and Kaul(1988), Lo and Makinlay (1988) find small positive serial correlation - may be too small for trading opportunities, depends on transactions costs </li></ul></ul><ul><li>Long Term Serial Correlation </li></ul><ul><ul><li>evidence is mixed </li></ul></ul>
  14. 14. Weak Form evidence (cont) <ul><li>Example 1: buy if a stock increases x%, sell if it decreases y% </li></ul><ul><ul><li>some evidence that momentum and price reversal strategies may work, but it is sketchy </li></ul></ul><ul><li>Example 2: buy and sell seasonally </li></ul><ul><ul><li>January effect: evidence is strong but are there any money managers who use it? </li></ul></ul><ul><ul><li>Monday effect: result of settlement </li></ul></ul><ul><li>Example 3: Technical Analysis </li></ul><ul><ul><li>no evidence it works but it is hard to quantify </li></ul></ul><ul><ul><li>non-linear models: neural networks, fractal models are getting more popular but no evidence exists on them </li></ul></ul>
  15. 15. <ul><li>Semi-strong form experiments </li></ul><ul><ul><li>Event studies </li></ul></ul><ul><ul><li>Motivation : </li></ul></ul><ul><ul><ul><li>examine how rapidly do security prices adjust to unexpected new events (an earnings announcement, government policy, etc). </li></ul></ul></ul><ul><ul><li>Evidences : </li></ul></ul><ul><ul><ul><li>IPOs </li></ul></ul></ul><ul><ul><ul><ul><li>There is “underpricing” initially then poor returns afterward </li></ul></ul></ul></ul><ul><ul><ul><li>Accounting information </li></ul></ul></ul><ul><ul><ul><ul><li>Lifo to Fifo to Lifo to evidence is strong that the market adjusts to changes </li></ul></ul></ul></ul><ul><ul><ul><li>Takeovers </li></ul></ul></ul><ul><ul><ul><ul><li>market reacts quickly and often anticipates </li></ul></ul></ul></ul><ul><ul><ul><ul><li>13D files cause prices to jump </li></ul></ul></ul></ul><ul><ul><ul><li>Seasoned Security Issues </li></ul></ul></ul><ul><ul><ul><ul><li>new stock lowers the stock price immediately </li></ul></ul></ul></ul><ul><ul><ul><ul><li>new debt raises the stock price immediately </li></ul></ul></ul></ul>
  16. 16. <ul><li>Seven steps in the Event Study: </li></ul><ul><li>Collect a sample of firms that had a surprise announcement (the event). </li></ul><ul><li>Determine the precise day of the announcement and designate this day as zero. Use daily data. </li></ul><ul><li>Define the period studied, e.g. 30 days (weeks, months) either side of the event. </li></ul><ul><li>For each firm compute the daily returns with market model approaches. [R t = a t + b t R mt + e t ] </li></ul><ul><li>For each firm, compute the Abnormal Return for each asset. [ e t = Actual - (a t + b t R mt )] </li></ul><ul><li>Compute for each day the average abnormal return (AR) over all assets. </li></ul><ul><li>Compute the Cumulative Abnormal Return (CAR). </li></ul>
  17. 17. Figure IV.8 : Abnormal Returns Time AR Day 0 -1 +1 -2 +2 0
  18. 18. Figure IV.8 : Cumulative Abnormal Returns Time CAR Day 0 -1 +1 -2 +2 Efficient Market Inefficient Market 0
  19. 19. <ul><ul><ul><li>Stock splits (Fama Fisher Jensen Roll ,1969) </li></ul></ul></ul><ul><ul><ul><ul><li>Splits have no obvious effect on firm value </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Maybe splits signal impending dividend increase </li></ul></ul></ul></ul><ul><ul><li>Issues in examining the results </li></ul></ul><ul><ul><ul><li>Magnitude issue </li></ul></ul></ul><ul><ul><ul><li>Selection bias issue </li></ul></ul></ul><ul><ul><ul><li>Lucky event issue </li></ul></ul></ul><ul><ul><ul><li>Possible model misspecification </li></ul></ul></ul><ul><li>Strong form evidence </li></ul><ul><ul><li>Assessing performance of professional managers </li></ul></ul><ul><ul><li>Motivation : </li></ul></ul><ul><ul><ul><li>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. </li></ul></ul></ul><ul><ul><li>Evidences : </li></ul></ul><ul><ul><ul><li>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. </li></ul></ul></ul>
  20. 20. 4. Market Microstructure