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Investments: Analysis and Behavior

Investments: Analysis and Behavior. Chapter 6- Efficient Market Hypothesis. ©2008 McGraw-Hill/Irwin. Learning Objectives. Understand the role of randomness and luck investment performance. Identify the levels of market efficiency. Characterize the time series of stock returns.

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Investments: Analysis and Behavior

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  1. Investments: Analysis and Behavior Chapter 6- Efficient Market Hypothesis ©2008 McGraw-Hill/Irwin

  2. Learning Objectives • Understand the role of randomness and luck investment performance. • Identify the levels of market efficiency. • Characterize the time series of stock returns. • Avoid gamblers fallacy and data snooping problems. • Recognize that price bubbles challenge market efficiency.

  3. Short-term Speculation: Good, or Lucky? • A coin-flipping contest • 6 billion people pay $1 each to join • Heads you stay in, tails you are out • After one round, 3 billion are still in • After ten rounds, about 6 million are still in • Imagine, flipping 10 heads in a row. • People begin to believe they are good at flipping, not lucky. • After 20 rounds, around 6,000 people left • Locals become heroes! • But half of these falter in the next round • After 25 rounds, 180 flippers are remain • If the game stopped now, each would receive $33.3 million • These people write books about their technique and strategy

  4. After the 30th round, only 6 remain • Each would get $1 billion of the game stopped • It would probably take 32 rounds to end with a single winner • The odds of flipping heads 32 times in a row is roughly one in six billion. • Is the winner good a flipping? Lucky? • There are millions of investors, analysts, portfolio managers, advisors, etc. participating in the investment process. • Many will appear to be top performers (at least for the short-term) • Who is lucky and who is good? How can you tell?

  5. Market Efficiency • The price for any given stock is effectively “fair” • = the expected net present value of all future profits • Discounted using a fair risk-adjusted return • Need • Large number of buyers and sellers • Free and readily available information • Essentially identical securities • Uninhibited trading • If there are bargains available, investors would bid up the price buying those stocks until the stock is no longer a bargain. • If markets are efficient, then it would be difficult for an investor to consistently beat the market.

  6. Efficient Market Hypothesis • EMH • Security prices fully reflect all available information. • New information arrives in an independent and random fashion • Current stock prices reflect all relevant risk and return information • Investors rapidly adjust stock prices to reflect new information • Levels of Efficiency (based on Information) • Weak-form: prices reflect all stock market information • Prices, volume, patterns, trading rules, etc. • Semistrong-form: current prices reflect all public information • Accounting statements, economic activity, old news stories • Strong-form: current prices reflect all public and private info

  7. Prices do react quickly! • After the close of the stock market on Monday, April 18, 2005, Texas Instruments announced that it beat Wall Street's expectations for the first quarter of 2005 and posted a profit of $411 million, which is 12 percent more than in the year-ago quarter. TI had been expected to post single-digit profit growth.

  8. Are Daily Returns Predictable?

  9. Figure 6.3 Daily Returns Are Noisy and Random Around A Mean of Zero, from 1/1/97 to 12/31/05.

  10. Random Walks and Prediction • Random Walk Theory • Stock prices movements do not follow any patterns or trends • Past price action cannot be used to predict future price movements. • Subsequent price changes represent arbitrary departures from previous prices. • Random walk with a drift • Stock prices do tend to increase, on average, over time.

  11. Yet, millions of people examine charts and search for patterns and trends. • The Human Brain is well suited to seeing patterns • Even when the data is random and no pattern exists! • Gambler’s fallacy • Popular, but erroneous, belief that some self-correcting process impacts random events. • After 5 fair coin flips of “heads” in a row, many people act as if they believe the probably of a heads in the next flip is different from 50% • Lottery players examine previous numbers picked. So do Keno players. • Data-Snooping • Patterns may appear in random data if enough different tests are examined. • Much data is available and computers can quickly crunch it. • Back testing and out of sample tests can help determine whether a pattern may repeat in the future or is simply an artifact of the data.

  12. From Dogs to Fools • Dogs of the Dow • Strategy identifies the 10 highest-dividend paying firms in the DJIA • 1992 book, Beating the Dow by O’Higgins and Downes • Buying the Dogs at the beginning of each year is shown to beat the buy-and-hold strategy of just owning the 30 stocks in the Dow by over 4% per year. • Value-oriented strategy • Dow Five • Buy the 5 lowest priced dogs • Beats the Dow by 8% per year • No basis in theory • Motley Fools’ adaptation • Foolish Four: Of the Dow Five, throw-out the lowest price stock and double-up on the second lowest price stock. • Purported to beat the Dow by 12% per year • Is the data tortured enough? • Motley Fool eventually abandoned this strategy when it both failed to perform well and other investors started trading against those following the strategy

  13. Investing in an Efficient Market • Two investors are walking down the street when one spots a $100 bill on the sidewalk. He points it out. The companion says, “It must not be a real $100 bill or someone would have already picked it up.” • If markets are efficient, we should not bother to look for bargains. However, if no one is looking for bargains, how can markets be efficient? • Studies show that, on average, mutual funds and investment newsletter writers do not beat their benchmark. • Evidence for EMH • What should investors do if markets are efficient?

  14. Challenges to EMH • Excessive Volatility • Why is the market so volatile? • Dividends are not volatile at all. • Bubbles • Dramatic increases and declines in the stock market

  15. Figure 6.4 Real Stock Prices and Present Values of Subsequent Real Dividends Source: Robert Shiller, 2003, “From Efficient Market Theory to Behavioral Finance,” Journal of Economic Perspectives, 17(1), Figure 1.

  16. From January 2, 1985, at 11,543, the Nikkei 225 soared to a closing high of 38,916 on December 29, 1989. • This represents a gain of 237.1% in the Nikkei over a 5-year period, and a stunning 27.5% compound annual rate of return. • Then, the bubble burst and the bottom fell out of the Japanese equity market. Fifteen years after the Japanese market peak, in December, 2004, the Nikkei stood at 10,796. That’s 72.3% below the December, 1989 peak. • From a (split-adjusted) level of 125 on January 31, 1985, the Nasdaq 100 soared to 4,816.35 on March 24, 2000. • This represents a 15 1/4-year return of 3,753.3%, and an amazing compound return of 27.1% per year. • Then the Nasdaq plunged, losing over 80% of its value by 2002.

  17. Why might the market not be efficient? • Investors make decisions influenced by emotions and psychological biases. • If large groups of investors become too optimistic or pessimistic, they may move prices • Investor mood • How investor mood can impact expectations…

  18. If prices reflect a dividend discount model: PV = D1 / (k – g) • But expectations become biased: E(P) = D1 / (k – E(g)) • So prices can deviate from true value by:

  19. Example: • If the annual market return over a long period of time is expected to be 12% and the long-term expected growth rate of stock market firms is 4%, the Dow Jones Industrial Average is fairly valued at 10,000. If Optimistic investors believe the long-term growth rate is 5%, how far would the DJIA be expected to fall? • The stock market should become over-valued as • The DJIA would be expected to rise to 1.14 × 10,000 = 11,400, or a 14% rise. However, it would also be 14% overvalued.

  20. Can investment fraud occur in an efficient market? • Microcap Fraud • Microcap stocks, or penny stocks, often trade as pink sheets on the OTC Bulletin Board • Low liquidity means the price can be susceptible to false press releases of exaggerations or lies, and “pump and dump” schemes. • Fraud on the Internet • Easy place to spread false “news” and “unbiased” opinion.

  21. Red Flags! • Assets Are Large But Revenues Are Small • Unusual Accounting Issues • Thin Public Float • SEC Trading Suspensions • High Pressure Sales Tactics

  22. EMH • The EMH is still hotly debated today. • In Support: • Short-term prices are unpredictable • Price adjust quickly and pretty accurately • Professional investors don’t seem to beat the market, on average. • Against: • Market is too volatile • Stock market bubbles exist • Investor mood may drive prices away from fair value • Investment fraud • The next chapter examine some interesting anomalies that also put the validity of the EMH into question

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