The-Efficient-Market-Hyp課件

1、CHAPTER 11The Efficient Market Hypothesis11-1Maurice Kendall (1953) found no predictable pattern in stock prices.Prices are as likely to go up as to go down on any particular day.How do we explain random stock price changes?Efficient Market Hypothesis (EMH)11-2Efficient Market Hypothesis (EMH)EMH sa

2、ys stock prices already reflect all available informationA forecast about favorable future performance leads to favorable current performance, as market participants rush to trade on new information.Result: Prices change until expected returns are exactly commensurate with risk.11-3Efficient Market

3、Hypothesis (EMH)New information is unpredictable; if it could be predicted, then the prediction would be part of todays information.Stock prices that change in response to new (unpredictable) information also must move unpredictably.Stock price changes follow a random walk.11-4Figure 11.1 Cumulative

4、 Abnormal Returns Before Takeover Attempts: Target Companies11-5Figure 11.2 Stock Price Reaction to CNBC Reports11-6Information: The most precious commodity on Wall Street Strong competition assures prices reflect information.Information-gathering is motivated by desire for higher investment returns

5、.The marginal return on research activity may be so small that only managers of the largest portfolios will find them worth pursuing.EMH and Competition11-7WeakSemi-strongStrongVersions of the EMH11-8Technical Analysis - using prices and volume information to predict future pricesSuccess depends on

6、a sluggish response of stock prices to fundamental supply-and-demand factors.Weak form efficiencyRelative strengthResistance levelsTypes of Stock Analysis11-9Types of Stock AnalysisFundamental Analysis - using economic and accounting information to predict stock pricesTry to find firms that are bett

7、er than everyone elses estimate.Try to find poorly run firms that are not as bad as the market thinks.Semi strong form efficiency and fundamental analysis11-10Active ManagementAn expensive strategySuitable only for very large portfoliosPassive Management: No attempt to outsmart the marketAccept EMHI

8、ndex Funds and ETFsVery low costsActive or Passive Management11-11Even if the market is efficient a role exists for portfolio management:DiversificationAppropriate risk levelTax considerationsMarket Efficiency & Portfolio Management11-12Resource AllocationIf markets were inefficient, resources would

9、 be systematically misallocated.Firm with overvalued securities can raise capital too cheaply.Firm with undervalued securities may have to pass up profitable opportunities because cost of capital is too high.Efficient market perfect foresight market 11-13Empirical financial research enables us to as

10、sess the impact of a particular event on a firms stock price.The abnormal return due to the event is the difference between the stocks actual return and a proxy for the stocks return in the absence of the event.Event Studies11-14Returns are adjusted to determine if they are abnormal.Market Model app

11、roach:a. rt = a + brmt + et(Expected Return)b. Excess Return = (Actual - Expected)et = rt - (a + brMt)How Tests Are Structured11-15Magnitude IssueOnly managers of large portfolios can earn enough trading profits to make the exploitation of minor mispricing worth the effort.Selection Bias IssueOnly u

12、nsuccessful investment schemes are made public; good schemes remain private.Lucky Event IssueAre Markets Efficient?11-16Weak-Form TestsReturns over the Short HorizonMomentum: Good or bad recent performance continues over short to intermediate time horizonsReturns over Long HorizonsEpisodes of oversh

13、ooting followed by correction11-17Predictors of Broad Market ReturnsFama and FrenchAggregate returns are higher with higher dividend ratiosCampbell and ShillerEarnings yield can predict market returnsKeim and StambaughBond spreads can predict market returns11-18P/E EffectSmall Firm Effect (January E

14、ffect)Neglected Firm Effect and Liquidity EffectsBook-to-Market RatiosPost-Earnings Announcement Price DriftSemistrong Tests: Anomalies11-19Figure 11.3 Average Annual Return for 10 Size-Based Portfolios, 1926 200811-20Figure 11.4 Average Return as a Function of Book-To-Market Ratio, 1926200811-21Fig

15、ure 11.5 Cumulative Abnormal Returns in Response to Earnings Announcements11-22Strong-Form Tests: Inside InformationThe ability of insiders to trade profitability in their own stock has been documented in studies by Jaffe, Seyhun, Givoly, and PalmonSEC requires all insiders to register their trading

16、 activity11-23Interpreting the AnomaliesThe most puzzling anomalies are price-earnings, small-firm, market-to-book, momentum, and long-term reversal.Fama and French argue that these effects can be explained by risk premiums.Lakonishok, Shleifer, and Vishney argue that these effects are evidence of i

17、nefficient markets.11-24Figure 11.6 Returns to Style Portfolio as a Predictor of GDP Growth 11-25Interpreting the EvidenceAnomalies or data mining?Some anomalies have disappeared.Book-to-market, size, and momentum may be real anomalies.11-26Interpreting the EvidenceBubbles and market efficiencyPrice

18、s appear to differ from intrinsic values.Rapid run up followed by crashBubbles are difficult to predict and exploit.11-27Stock Market AnalystsSome analysts may add value, but:Difficult to separate effects of new information from changes in investor demandFindings may lead to investing strategies tha

19、t are too expensive to exploit11-28Mutual Fund PerformanceThe conventional performance benchmark today is a four-factor model, which employs:the three Fama-French factors (the return on the market index, and returns to portfolios based on size and book-to-market ratio) plus a momentum factor (a port

20、folio constructed based on prior-year stock return).11-29Figure 11.7 Estimates of Individual Mutual Fund Alphas, 1993 - 200711-30Consistency, the “hot hands” phenomenonCarhart weak evidence of persistencyBollen and Busse support for performance persistence over short time horizonsBerk and Green skil

21、led managers will attract new funds until the costs of managing those extra funds drive alphas down to zero.Mutual Fund Performance11-31Figure 11.8 Risk-adjusted performance in ranking quarter and following quarter11-32So, Are Markets Efficient?The performance of professional managers is broadly con

22、sistent with market efficiency.Most managers do not do better than the passive strategy.There are, however, some notable superstars:Peter Lynch, Warren Buffett, John Templeton, George Soros11-33CHAPTER 12Behavioral Finance and Technical Analysis34Behavioral FinanceConventional FinancePrices are corr

23、ect; equal to intrinsic value. Resources are allocated efficiently.Consistent with EMHBehavioral FinanceWhat if investors dont behave rationally?11-35The Behavioral CritiqueTwo categories of irrationalities:Investors do not always process information correctly.Result: Incorrect probability distribut

24、ions of future returns.Even when given a probability distribution of returns, investors may make inconsistent or suboptimal decisions.Result: They have behavioral biases.11-36Errors in Information Processing: Misestimating True ProbabilitiesForecasting Errors: Too much weight is placed on recent exp

25、eriences.Overconfidence: Investors overestimate their abilities and the precision of their forecasts.Conservatism: Investors are slow to update their beliefs and under react to new information. Sample Size Neglect and Representativeness: Investors are too quick to infer a pattern or trend from a sma

26、ll sample.11-37Behavioral BiasesBiases result in less than rational decisions, even with perfect information.Examples: Framing: How the risk is described, “risky losses” vs. “risky gains”, can affect investor decisions.11-38Behavioral BiasesMental Accounting:Investors may segregate accounts or monie

27、s and take risks with their gains that they would not take with their principal.Regret Avoidance:Investors blame themselves more when an unconventional or risky bet turns out badly.11-39Behavioral BiasesProspect Theory:Conventional view: Utility depends on level of wealth. Behavioral view: Utility d

28、epends on changes in current wealth.11-40Figure 12.1 Prospect Theory11-41Limits to ArbitrageBehavioral biases would not matter if rational arbitrageurs could fully exploit the mistakes of behavioral investors.Fundamental Risk: “Markets can remain irrational longer than you can remain solvent.”Intrin

29、sic value and market value may take too long to converge.11-42Limits to ArbitrageImplementation Costs:Transactions costs and restrictions on short selling can limit arbitrage activity.Model Risk:What if you have a bad model and the market value is actually correct?11-43Limits to Arbitrage and the La

30、w of One PriceSiamese Twin CompaniesRoyal Dutch should sell for 1.5 times ShellHave deviated from parity ratio for extended periodsExample of fundamental risk11-44Figure 12.2 Pricing of Royal Dutch Relative to Shell (Deviation from Parity)11-45Limits to Arbitrage and the Law of One PriceEquity Carve

31、-outs3Com and PalmArbitrage limited by availability of shares for shortingClosed-End FundsMay sell at premium or discount to NAVCan also be explained by rational return expectations11-46Bubbles and Behavioral EconomicsBubbles are easier to spot after they end.Dot-com bubbleHousing bubble11-47Bubbles

32、 and Behavioral EconomicsRational explanation for stock market bubble using the dividend discount model:S&P 500 is worth $12,883 million if dividend growth rate is 8% (close to actual value in 2000).S&P 500 is worth $8,589 million if dividend growth rate is 7.4% (close to actual value in 2002).11-48

33、Technical Analysis and Behavioral FinanceTechnical analysis attempts to exploit recurring and predictable patterns in stock prices.Prices adjust gradually to a new equilibrium.Market values and intrinsic values converge slowly. 11-49Technical Analysis and Behavioral FinanceDisposition effect: The te

34、ndency of investors to hold on to losing investments.Demand for shares depends on price historyCan lead to momentum in stock prices11-50Trends and Corrections: The Search for MomentumDow TheoryPrimary trend : Long-term movement of prices, lasting from several months to several years.Secondary or int

35、ermediate trend: short-term deviations of prices from the underlying trend line and are eliminated by corrections.Tertiary or minor trends: Daily fluctuations of little importance.11-51Figure 12.3 Dow Theory Trends11-52Trends and Corrections: Moving AveragesThe moving average is the average level of prices over a given interval of time.Bullish signal: Market price breaks through the moving average line from below. Time to buyBearish signal: When prices fall below the moving average, it is time to sell.11-53Figure 12.5 Moving Average for HPQ