Presentation on theme: "7-1 7 Stock Price Behavior and Market Efficiency."— Presentation transcript:
7-1 7 Stock Price Behavior and Market Efficiency
7-2 Learning Objectives 1. The foundations of market efficiency 2. The implications of the forms of market efficiency 3. Market efficiency and the performance of professional money managers 4. What stock market anomalies, bubbles, and crashes mean for market efficiency
7-3 Market Efficiency Can you consistently “beat the market?” Earn a positive excess return Excess return = return above that earned by other investments with the same risk Informational Efficiency Efficient relative to a specific information set Driving force = competition for profit
7-4 Economic Forces Driving Market Efficiency Investor rationality No systematic over- or under-valuation Independent deviation from rationality Irrational investors have dissimilar beliefs Arbitrage If inefficiencies exist, arbitrage will bid it away “Market efficiency doesn’t require that everybody be rational, just that somebody is.” These conditions are so powerful that any one of them leads to efficiency.
7-5 Market Efficiency The Efficient Market Hypothesis (EMH): Major financial markets reflect all relevant information at any given time Bachelier (1900); Fama (1960, 1972) Market efficiency research: Examines the relationship between stock prices and available information Prediction of EMH theory: if a market is efficient, it is not possible to “beat the market”
7-6 Forms of Market Efficiency Weak-form Efficient Market: Information = past prices and volume data Technical analysis is of little use Semistrong-form Efficient Market: Information = publicly available information Fundamental analysis is of little use Strong-form Efficient Market: Information = Public or private “Inside information” is of little use
7-7 Efficient Market Hypotheses WEAK Security Market Information SEMISTRONG Public Information STRONG Public & Private Information
7-8 Why Would a Market be Efficient? The driving force toward market efficiency is simply competition and the profit motive. Even a relatively small performance enhancement can be worth a tremendous amount of money (when multiplied by the dollar amount involved). This creates incentives to unearth relevant information and use it.
7-9 Implications of Market Efficiency Does Old Information Help Predict Future Stock Prices? Sophisticated research techniques employed Some results find future returns partly predictable by past returns Not enough predictability to earn an excess return Trading costs defeat trading systems built on past returns Result: Extremely difficult to outperform a buy-and-hold strategies involving broad market indexes Technical Analysis implication: No matter how often a particular stock price path has related to subsequent stock price changes in the past, there is no assurance that this relationship will occur again in the future.
7-10 Implications of Market Efficiency Random Walks and Stock Prices Many people would say stock prices are predictable Truth: it is very difficult to predict stock market prices. Considerable research has shown that stock prices change through time as if they are random. Price increases about as likely as price decreases Random Walk no discernable pattern to the path that a stock price follows Y t+1 = Y t + ε
7-12 How New Information Gets into Stock Prices Stock prices change when traders buy and sell shares based on their view of the future prospects for the stock. Future prospects are influenced by unexpected news announcements: News changes traders’ opinions Prices adjust to unexpected news in three basic ways: Efficient Market Reaction: The price instantaneously adjusts to the new information. Delayed Reaction: The price partially adjusts to the new information. Overreaction and Correction: The price over-adjusts to the new information, but eventually falls to the appropriate price.
7-13 How New Information Gets into Stock Prices
7-14 Event Studies A technique to test for the effects of new information on stock prices Two areas of focus: The adjustment process itself The size of the stock price reaction to a news announcement
7-15 Event Studies Isolate effect of stock specific news from overall market reactions: Abnormal return = Observed return – Expected return Expected return calculation: Market Model using an index (Nasdaq 100 or S&P 500) Long-term average return on the stock Align the abnormal return on a stock to the days relative to the news announcement. Day 0 = the day a news announcement is made. One day after news announcement = +1 One day before news announcement = -1
7-16 Event Studies According to the EMH: The abnormal return on any day should relate only to information released on that day Cumulative Average Return (CAR): CAR = abnormal returns accumulated over a 60 or 80-day period (day 0 +/- 30 or 40 days) The first cumulative abnormal return, or CAR, is just equal to the abnormal return on day -40. The CAR on day -39 is the sum of the first two abnormal returns. Examining CARs indicates any over- or under- reaction to an announcement
7-18 Event Study Example Friday, May 25, 2007: Advanced Medical Optics, Inc. (EYE), recalled a contact lens solution called Complete MoisturePlus Multi Purpose Solution. EYE took this voluntary action after the Centers for Disease Control and Prevention (CDC) found a link between the solution and a rare cornea infection called acanthamoeba keratitis (AK). EYE chose to recall their product even though no evidence was found that their manufacturing process introduced the parasite that can lead to AK. Further, company officials believed that the occurrences of AK were most likely the result of end users who failed to follow safe procedures when installing contact lenses.
7-19 EYE Event Study Tuesday, May 29, 2007 EYE shares opened at $34.37, down $5.83 from the Friday closing price.
7-20 EYE Event Study Advanced Medical Optics, Inc.’s cumulative abnormal return hovered around zero before the announcement. After the news was released, there was a large, sharp downward movement in the CAR. Overall CAR pattern = essentially what EMH would predict: A band of cumulative abnormal returns A sharp break in cumulative abnormal returns, and Another band of cumulative abnormal returns.
7-21 Informed Traders and Insider Trading If a market is strong-form efficient, no information of any kind, public or private, is useful in beating the market. But, it is clear that significant inside information would enable you to earn substantial excess returns. Should any of us be able to earn returns based on information that is not known to the public?
7-22 Informed Traders and Insider Trading In the U.S. it is illegal to make profits on non- public information: Necessary to instill trust in U.S. stock markets Enforced by SEC Distinguish between: Informed trading (vs. “noise” or “liquidity” trading) Legal insider trading Illegal insider trading
7-23 Informed Trading Informed Trader: One who makes a decision to buy or sell a stock based on publicly available information and analysis Information sources: The Wall Street Journal Quarterly reports issued by a company Financial information from the Internet Talking to other investors
7-24 Legal Insider Trading Some informed traders are also insider traders. Trading by company “insiders” in the stock of their own company: Perfectly legal trades Must comply with SEC reporting rules SEC reports trades to the public Corporate insiders must declare that trades made were based on public information about the company, rather than “inside” information.
7-25 Who is an “Insider”? Someone with material non-public information Information not known to the public if known, would impact the stock price Illegal insider trading = acting on such information in an attempt to make a profit
7-26 Illegal Insider Trading “Tipper” = person who purposely divulged material non-public information “Tippee” = person who knowingly used such information in an attempt to profit Enforcement Problems: Difficult to prove that a trader is truly a tippee Difficult to track insider information flows and trades People claim that they just “overheard” someone talking When you take possession of material non-public information, you become an insider, and are bound to obey insider trading laws.
7-27 It’s Not a Good Thing: What did Martha do? The SEC believed that Ms. Stewart was told by her friend and ImClone founder, Sam Waksal, that a cancer drug being developed by ImClone had been rejected by the FDA. December 27, 2001: Martha Stewart sold her 3,928 shares in ImClone ImClone traded below $60 per share, a level that Ms. Stewart claimed triggered an existing stop-loss order. December 28, 2001: FDA rejection announced after the market closed December 31, 2001: ImClone shares closed at about $46 per share on the next trading day
7-28 It’s Not a Good Thing: What did Martha do? June 2003: Ms. Stewart and her stock broker, Peter Bacanovic, were indicted and plead not guilty to nine federal counts. January 2004: Ms. Stewart’s trial began Securities fraud charge dismissed Ms. Stewart was convicted on all four counts of obstructing justice: Fined $30,000 – maximum allowed Sentenced to five months in prison Two years of probation Minimum permitted Five months of home confinement. Peter Bacanovic: Fined $4,000 Sentenced to five months in prison Two years of probation Martha Stewart was accused, but not convicted, of insider trading. Martha Stewart was accused, and convicted, of obstructing justice.
7-29 Are Financial Markets Efficient? Market efficiency difficult to test Four basic reasons: Risk-adjustment problem Relevant information problem Dumb luck problem Data snooping problem
7-30 Are Financial Markets Efficient? Short-term stock price and market movements are difficult to predict with any accuracy. The market reacts quickly and sharply to new information. Studies find little or no evidence that such reactions can be profitably exploited If the stock market can be beaten, the manner is not obvious.
7-31 Implications: If Markets are Efficient Security selection becomes less important, because securities will be fairly priced. Small role for professional money managers. Timing the market makes little sense.
7-32 Market Efficiency and the Performance of Professional Money Managers Hard to predict how many professional money managers will beat the Vanguard 500 Index Fund. The dashed red line the percentage of professional money managers who can beat the Vanguard 500 Index Fund over a 10-year investment period is low and stable
7-33 Percentage of Managed Equity Funds Beating the Vanguard 500 Index Fund, One-Year Returns – In only six of the 21 years (1986—2006) did more than half beat the Vanguard 500 Index Fund.
7-34 Percentage of Managed Equity Funds Beating the Vanguard 500 Index Fund, Ten-Year Returns In only two of these 21 investment periods, did more than half the professional money managers beat the Vanguard 500 Index Fund
7-35 Market Efficiency and the Performance of Professional Money Managers Time periods: 1-year, rolling 3-, 5- and 10-year investment periods Two questions: - What % of the time did 1/2 professionally managed funds beat the Vanguard 500 Index Fund? - What % of the time did 3/4 of them beat the Vanguard 500 Index Fund?
7-36 Market Efficiency and the Performance of Professional Money Managers If: Markets are inefficient … and Fundamental analysis is valuable Then: Why can’t mutual fund managers beat a broad market index? Enormous resources Substantial survivorship bias Poorly performing managers and funds disappear Should lead to survivors who can beat the market Professional money managers’ inability to outperform a broad market index is consistent with equity market efficiency.
7-37 What is the Role for Portfolio Managers in an Efficient Market? To build a portfolio to the specific needs of individual investors: Basic principle of investing: hold a well-diversified portfolio Exactly which diversified portfolio is optimal varies by investor Factors that influence portfolio choice: Investor’s age Tax bracket Risk aversion Employer
7-38 Market Anomalies Stock price behavior that is both baffling and hard to reconcile with market efficiency Three facts to keep in mind about market anomalies: 1.Not many $$ involved 2.Fleeting, tending to disappear when discovered 3.Transaction costs render trading systems unprofitable
7-40 The Day-of-the-Week Effect Tendency for Monday to have a negative, statistically significant average The effect is much stronger in the 1950-1979 time period than in the 1980-2006 time period.
7-41 The Amazing January Effect Tendency for small-cap stocks to have large returns in January Does the January effect exist for the S&P 500? S&P500
7-42 The Amazing January Effect But, look at returns on small-cap stocks Small-cap
7-43 The Turn-of-the-Year Effect “Turn of the Year Days:” The last week in a calendar year and the first two weeks in the next calendar year “Rest of the Days:” Any daily return that does not fall into this three-week period “Turn of the Year” returns are higher than “Rest of the Days” returns Largest difference in the 1962-1983 period
7-44 The Turn-of-the-Month Effect. “Turn of the Month Days:” Daily returns from the last day of any month or the following three days of the following month “Rest of the Days:” Any other daily returns “ Turn of the Month” returns exceed “Rest of the Days” returns. The turn-of-the-month effect is apparent in all three time periods. Interestingly, the effect appears to be stronger in the 1984-2006 period than in the 1962-1983 period. The fact that this effect exists puzzles EMH proponents.
7-45 Bubbles and Crashes Bubble: Market prices soar far in excess of what normal and rational analysis would suggest. Investment bubbles eventually pop When bubble pops, asset values plummet Can form over weeks, months, or even years Crash: Significant and sudden drop in market values. Crashes are generally associated with a bubble Crashes are sudden, generally lasting less than a week. The financial aftermath of a crash can last for years
7-46 The Crash of 1929 October 1929 M T W R F M T W R
7-47 The Crash of 1929—The Aftermath 1929 - 1932
7-48 The Crash of 1987 & the Aftermath Friday, October 16 th : The DJIA fell 108 points to close at 2,246.73. Monday, October 19: DJIA lost about 22.6% of its value on a new record volume of about 600 million shares DJIA plummeted 508.32 points to close at 1,738.74; intraday low of 1,616.21. Tuesday, October 20th: Market rallied, closing at 1,841.01, up 102 points. Market recovered relatively quickly.
7-49 NYSE Circuit Breakers Triggered if DJIA drops by 10, 20, or 30 %: Designed to “break the circuit” with futures markets in Chicago. Reset quarterly based on DJIA at end of quarter
7-50 The Asian Crash “The Bubble” The Asian Crash started with a booming bull market in the 1980s Japan and emerging Asian economies seemed to be forming a powerful economic force. The “Asian economy” = investor outlet for those wary of the U.S. market after the Crash of 1987 “The Crash” The Nikkei Index crash began in 1990 Lengthened into a particularly long bear market
7-52 The “Dot-Com” Bubble and Crash Mid-1990s: Rise in Internet usage and growth potential fueled widespread excitement over the “new economy.” Investor euphoria led to a surge in Internet IPOs “DotComs” Lacked solid business models Many suffered huge losses