Duong Nhu Hung Source: Investments 8 th Ed. (Bodie, Kane and Marcus) McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved. The Efficient Market Hypothesis (EMH)

Dương Như Hùng, Ph.D. Vice rector, University of Economics and Law PhD Finance (Old Dominion University, VA, USA) MBA (Asian Institute of Technology, Bangkok, Thailand) Electrical engineer (Budapest, Hungary) Research interest: Stock returns, KPI, Productivity

11-3 Agenda Introduction to EMH –What is EMH? –What are the implications of EMH? Testing methodology –Weak form –Semistrong form –Strong form

11-4 INTRODUCTION TO EFFICIENT MARKET HYPOTHESIS (EMH)

11-5 Are the stock markets illogical/ erratic? Economics: Tracing the evolution of several economic variables over time would clarify and predict the progress of the economy through boom and bust periods. Can we predict stock prices? Kendall (1953): stock prices evolved randomly  stock market is dominated by erratic market psychology, or no logical rules

11-6 A logical model to predict stock price? Investors will buy/ sell stocks  prices adjusted quickly What move stock prices? –New information How do new information arrive to the market? –randomly Random price movements indicate a well- functioning or efficient market, not an irrational one.

11-7 Security prices reflect all available information Why look at market efficiency? –Implications for business and corporate finance –Implications for investment Efficient Market Hypothesis (EMH)

11-8 Figure 11.1 Cumulative Abnormal Returns Before Takeover Attempts: Target Companies

11-9 Figure 11.2 Stock Price Reaction to CNBC Reports

11-10 Why should stock prices fully and accurately reflect publicly available information? Once information becomes available, market participants analyze it Competition assures prices reflect information What is the source of efficiency?

11-11 Joke A finance professor is walking across the University of Chicago campus with a student. They come upon $20 lying on the ground, and the student leans down to pick it up. The professor said, “Don’t bother. If it was really there, somebody else would’ve already picked it up.” Investments11

11-12 Weak –past prices, trading volume Semi-strong –Plus fundamental data on the firm’s product line, quality of management, balance sheet composition, patents held, earning forecasts, and accounting practices Strong –Plus information available only to company insiders Versions of the EMH

11-13 Technical Analysis - using prices and volume information to predict future prices –Weak form efficiency & technical analysis –Key: recognize the price movement patterns –Self-destructing price patterns Fundamental Analysis Types of Stock Analysis

11-14 Trend is assumed to be in effect until it gives definite signals that it has reversed

11-15 VN index during 2000 – 6/2010

11-16 Technical Analysis - using prices and volume information to predict future prices –Weak form efficiency & technical analysis –Key: recognize the price movement patterns –Self-destructing price patterns Fundamental Analysis - using economic and accounting information to predict stock prices –Semi strong form efficiency & fundamental analysis –Key: Get new info before other + process it correctly & quickly Types of Stock Analysis

11-17 Cost of information if markets are efficient, trading rules (TA), and the use of public information (FA) will not make abnormal returns! If there is no reward to hard works  no incentive for security analyst to collect information  markets not efficient! How much do you want to pay for “new information”?

11-18 Active Management –Security analysis –Timing Passive Management –Buy and Hold –Index Funds Who have more incentives to spend efforts on security analysis? –Small investor of $100,000 or a large investment firm of $1,000,000,000 Active or Passive Management

11-19 If the market were efficient, portfolio managers would be unemployed? Appropriate risk level Tax considerations Employment Ages Market Efficiency & Portfolio Management

11-20 Critical discussions What are the costs of inefficiency for the economy/ society?

11-21 TESTING METHODOLOGY

11-22 Weak-Form Tests Statistical Tests of Independence –autocorrelation tests of independence –runs test Tests of Trading Rules Returns over the Short Horizon –Momentum Returns over Long Horizons –Contrarian investment

11-23 Tests for Semistrong-form Prediction of future rate of returns using available public information –Time series: Dividend yield, default spread, term structure spread  future returns Return t = α + β1* [Div Yld] t-1 + β2 *[Default Spr] t-1 –Cross-sections: P/E, Size, B/M, Momentum Return i = α + β1* [Beta] i + β2 *[Size] i + β2 *[B/M] i

11-24 Figure 11.3 Average Annual Return for 10 Size-Based Portfolios, 1926 – 2006

11-25 Figure 11.4 Average Return as a Function of Book-To-Market Ratio, 1926–2006

11-26 Figure 11.6 Returns to Style Portfolio as a Predictor of GDP Growth

11-27 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

11-28 Tests for Semistrong-form Event studies –How fast stock prices adjust to an economic events –Events: Exchange Listing, Corporate Events (M&A, security issues, Stock Splits, IPOs, ) –Calculate returns surrounding events Abnormal return (AR)= Actual returns – Benchmark returns Cumulative Abnormal Returns (CAR) = sum of AR

11-29 Cumulative Abnormal Returns in Response to Earnings Announcements ( Post-Earnings Announcement Price Drift)

11-30 Tests for strong-form Corporate Insider Trading: –Do they outperform the markets? –Can we make profit by mimicking their trading? Security Analysts –Analysts’ Recommendations Performance of Professional Money Managers

11-31 Stock Market Analysts Do Analysts Add Value? –Mixed evidence –Ambiguity in results

11-32 Some evidence of persistent positive and negative performance Potential measurement error for benchmark returns –Style changes –May be risk premiums Mutual Fund Performance

11-33 Critical thinking Does an investor have buying skills if he buys a stock whose return is  Positive?  > market average?  > average in the industry?  > Return Average of the companies that have similar characteristics ? Riskier characteristics  higher expected return  compare performance using risk adjusted returns, not the returns alone!

11-34 Returns are adjusted to determine if they are abnormal Market Model approach a. r t = a t + br mt + e t (Expected Return) b. Excess Return = (Actual - Expected) e t = r t - (a + br Mt ) How to measure risk adjusted returns?

11-35 How to interpret the anomalies? Risk Premiums: firms that have higher returns are riskier  need to measure the risks properly (Fama French) –Other factors: Anomalies or Data Mining Market inefficiencies  investment opportunities (Lakonishok, Shleifer, and Vishney)

11-36 Conclusions If markets are efficient, prices reflect all available information Available information? –Historical prices, trading volume  weak form –Fundamental information  semi-strong –Private information  strong Why is EMH important? –Investment strategies Efficient  Passive investments Not efficient  active, fundamental, technical –Regulators Efficient Resource allocation in the economy

11-37 Tests If markets are efficient –Risk adjusted returns cannot be predicted! Tests for Weak-form –Statistical test of independence (autocorrelation tests, Run tests) –Tests of Trading Rules Tests for Semistrong form –Prediction of future rate of returns (Time series, Cross- sections) –Event studies: How fast stock prices adjust to an economic events Tests for strong form –Performance of insiders, Analysts’ Recommendations, fund managers

11-38 Reference Clarke, Jonathan, Tomas Jandik, Gershon Mandelker. Fama, E.F., "Efficient Capital Markets: II," Journal of Finance(December 1991). Fama, E.F., ”Random Walks in Stock Market Prices”, Financial Analysts Journal January - February1995 Fama, E.F., “The Cross-Section of Expected Stock Returns”, The Journal of Finance, Vol. 47, No. 2. (Jun., 1992)