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Efficient Market Hypothesis vs. Behavioral Finance

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Title: Chap 1 Background and Trend Author: ITSD Last modified by: Tong Created Date: 8/23/2005 2:40:39 PM Document presentation format: On-screen Show (4:3) – PowerPoint PPT presentation

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Title: Efficient Market Hypothesis vs. Behavioral Finance


1
Efficient Market Hypothesis vs. Behavioral Finance
  • Market Efficiency
  • Random walk versus market efficiency
  • Versions of market efficiency
  • Technical analysis vs. fundamental analysis
  • Predictors of future returns and market anomalies
  • Behavioral finance

2
Cumulative Abnormal Returns Around Takeover
Attempts Target Companies
3
Stock Price Reaction to CNBC Reports
4
EMH and Competition
  • Stock prices fully and accurately reflect
    publicly available information.
  • Once information becomes available, market
    participants analyze it.
  • Competition assures prices reflect information.
  • What does competition mean here? -- page 351
  • Is there a role for active portfolio management
    in an efficient market?

5
Forms of the EMH
  • Weak
  • Semi-strong
  • Strong
  • See page 347-348.

6
Types of Stock Analysis
  • Technical Analysis - using prices and volume
    information to predict future prices.
  • Weak form efficiency technical analysis
  • Chartist
  • Relative strength versus resistance levels
  • Fundamental Analysis - using economic and
    accounting information to predict stock prices.
  • Semi strong form efficiency fundamental analysis

7
Technical Analysis
  • Relative strength page 348
  • Resistance levels upper bound or
  • Support levels lower bound
  • Whether a workable technical trading rule will
    continue to work in the future once it becomes
    publicly known?

8
Fundamental Analysis
  • Uses earnings and dividend prospects of the firm,
    expectations of future interest rates, and risk
    evaluation of the firm to determine proper stock
    prices.
  • Fundamental analysis is much beyond identifying
    well-run firms with good prospects. It is to
    identify companies better than every elses
    estimate.

9
Active or Passive Management
  • Active Management
  • Security analysis
  • Timing
  • Passive Management
  • Buy and Hold
  • Index Funds

10
Market Efficiency Portfolio Management
  • Even if the market is efficient a role exists for
    portfolio management
  • Appropriate risk level
  • Tax considerations
  • Other considerations

11
Empirical Tests of Market Efficiency
  • Event studies
  • Assessing performance of professional managers
  • Testing some trading rule

12
Issues in Examining the Results
  • Magnitude Issue
  • Selection Bias Issue investing in small stocks
  • Lucky Event Issue

13
Weak-Form Tests
  • Serial Correlation
  • Momentum
  • Returns over Long Horizons

14
Experience with 911
  • Anticipating market chaos, panic selling and a
    disastrous loss of value in the wake of the
    attacks, the NYSE and the Nasdaq remained closed
    until September 17, the longest shutdown since
    1933. Moreover, many trading, brokerage and other
    financial firms had offices in the World Trade
    Center and were unable to function in the wake of
    the tragic loss of life and collapse of both
    towers.
  • On the first day of NYSE trading after 9/11, the
    market fell 684 points, a 7.1 decline, setting a
    record for the biggest loss in exchange history
    for one trading day. At the close of trading that
    Friday, ending a week that saw the biggest losses
    in NYSE history, the Dow Jones was down almost
    1,370 points, representing a loss of over 14.
  • Major stock sell-offs hit the airline and
    insurance sectors as anticipated when trading
    resumed. Hardest hit were American Airlines and
    United Airlines, carriers whose planes were
    hijacked for the terrorist attacks.
  • American Airlines (NYSEAMR) stock dropped from a
    29.70 per share close of September 11 to 18.00
    per share close on September 17, a 39
    decline. United Airlines (NYSEUAL) stock dropped
    from 30.82 per share close to 17.50 per share
    on the close on September 17, a 42 decline.

15
Also Program trading algorithmic trading and
high-frequency trading According to the New York
Stock Exchange, in 2006 program trading accounts
for about 30 and as high as 46.4 of the trading
volume on that exchange every day. http//www.prog
ramtrading.com/ The greatest point loss of the
Dow Jones Industrial Average was 777.68 points on
September 29, 2008.
16
Predictors of Broad Market Returns
  • Fama and French
  • Aggregate returns are higher with higher dividend
    ratios
  • Campbell and Shiller
  • Earnings yield can predict market returns
  • Keim and Stambaugh
  • Bond spreads can predict market returns

17
Anomalies
  • P/E Effect
  • Small Firm Effect (January Effect)
  • Neglected Firm
  • Book-to-Market Effects
  • Post-Earnings Announcement Drift
  • http//biz.yahoo.com/research/earncal/today.html

18
Returns in Excess of Risk-Free Rate and in excess
of the Security Market Line for 10 Size-Based
Portfolios, 1926 2005
19
Average Monthly Returns as a Function of the
Book-To Market Ratio, 1963 2004
20
Cumulative Abnormal Returns in Response to
Earnings Announcements
21
Mutual Fund Performance
  • Some evidence of persistent positive and negative
    performance.
  • Potential measurement error for benchmark
    returns.
  • Style changes
  • May be risk premiums

22
Persistence of Mutual Fund Performance
23
Behavioral Finance
  • The premise of behavioral finance is that
    conventional financial theory ignores how real
    people make decisions and that people make a
    difference.
  • Investors Do Not Always Process Information
    Correctly
  • Investors Often Make Inconsistent or
    Systematically Suboptimal Decisions

24
Behavioral Biases
  • Framing
  • Decisions seem to be affected by how choices are
    framed page 387
  • example
  • Mental Accounting
  • A special form of framing in which people
    segregate certain decisions
  • example
  • Regret Avoidance
  • Individuals would have more regrets when their
    decisions are more unconventional
  • example
  • Prospect Theory
  • Traders become risk seeking after they lose money

25
Prospect Theory Graphs
26
Prospect theory (2)
  • Loss aversion utility depends not on the level
    of wealth from current levels.
  • The convex curvature to the left of the origin
    will induce investors to be risk seeking rather
    risk averse when it comes to losses
  • Traders in T-bond futures often take
    significantly greater risk in afternoon sessions
    following morning sessions in which they have
    lost money

27
Limits to Arbitrage
  • Fundamental Risk
  • Implementation Costs
  • Model Risk

28
Limits to Arbitrage and the Law of One Price
  • Violations
  • Siamese Twin Companies
  • Equity Carve-outs
  • Closed-End Funds

29
Bubbles and Market Efficiency
  • The bust of dot-com bubble
  • Financial crisis housing price bubble
  • Hard to be justified by the position that
    security prices represent rational, unbiased
    assessments of intrinsic value.
  • Dynamic risk taking excessive risk taking in
    bubble period

30
Technical Analysis and Behavioral Finance
  • Trends and corrections
  • momentum (page 393)
  • Dow theory primary trend, secondary trend, and
    tertiary trend
  • see Figure 12-4
  • Moving averages
  • Breadth the spread between the number of stocks
    that advance and decline in price.

31
Technical Analysis and Behavioral Finance
  • Trin statistic
  • Confidence index
  • Put/call ratio

32
Investment-based CAPM
  • Cochrane (1991, 1996)
  • Low costs of capital imply high NPV of new
    projects and high investment
  • High costs of capital imply low NPV of new
    project and low investment
  • Inverse relationship between expected return and
    investments
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