THE EFFICIENT MARKET HYPOTHESIS

Analysis of economic time series in 1950s◦ Business cycle theorist, evolution of several

economic variables overtime What about the behavior of stock market

prices ◦ Maurice Kendall 1953, no predictable patterns in

stock prices◦ Irrationality?◦ Random price movements indicate a well-

functioning or efficient market, no an irrational one

◦ Why and implications

10.1 RANDOM WALKS AND THE EFFICIENT MARKET

Do security prices reflect information ? Why look at market efficiency?

◦ Implications for business and corporate finance◦ Implications for investment

Forecast of a future price increase will lead instead to an immediate price increase◦ If it is sure the stock price will increase, then large orders to buy

the stock and no one holding the stock will sell, immediate jump in stock price

◦ Stock price will immediately reflect the good news implicit in the model’s forecast

Any information that could be used to predict stock performance should already be reflected in stock prices

Increase or decrease only in response to new information, which is unpredictable; the stock prices that change in response to new information also must move unpredictably

Random walk

Random Walk - stock prices are random◦ the price changes should be random and unpredictable

Not irrationality◦ Randomly evolving stock prices are the consequence

of intelligent investors competing to discover relevant information

◦ Random walk would be the natural result of prices that always reflect all current knowledge

EMH◦ The stocks already reflect all available

information

Why expect prices to reflect all available information

Grossman and Stiglitz (1980)◦ Investors have incentive to spend time and resources

to analyze and uncover new information only if higher returns

◦ Degree of efficiency differs across various markets Emerging markets, less intensively analyzed, accounting

disclosure requirements less rigorous, small stocks receive relatively little coverage

Competition among the well-backed, highly paid, aggressive analyst ensures that stock prices ought to reflect available information regarding their proper levels

With many well-backed analysts willing to spend resources on research, easy picking in the market are rare, incremental return on research activity may be small that only largest portfolios will find them worth pursuing

Weak◦ Reflect all information that can be derived by

examining market ◦ trading data, past prices, trading volume, or short

interest Semi-strong

◦ All publicly available information regarding the prospects of a firm

◦ Past prices, fundamental data Strong

◦ All information relevant to the firm◦ Even including information available only to

company insiders

10.2 IMPLICATIONS OF THE EMH

Technical Analysis - using prices and volume information to predict future prices.◦ Weak form efficiency & technical analysis

Fundamental Analysis - using economic and accounting information to predict stock prices.◦ Semi strong form efficiency & fundamental analysis

Search for recurrent and predictable patterns in stock prices◦ Prices responds slowly enough

Resistance levels/ supprt levels◦ Example, XYZ traded at 70 for several months. Once it

declined to 65 then increased, 70 is considered a resistance level, because investors who bought at 70 will be eager to sell their shares as soon as they can break even, selling pressure at 70

EMH implies technical analysis is without merit◦ Past history of prices and trading volume is publicly

available, any information from analyzing past prices has already been reflected in stock prices

◦ Price patterns self-destructing, occasionally uncover a profitable trading rule, then it will be invalidated when the mass of traders attempts to exploit it Market dynamic is one of a continual search for profitable

trading rules

Dow theory◦ Primary trend◦ Secondary trends◦ Minor trends

Elliott wave theory◦ A set of wave patterns

Moving averages Relative strength approach

Use earnings and dividend prospects of the firm, expectations of future interest rates, risk evaluation of the firm to determine proper stock prices

Attempt to determine the present discounted value of all payments a stockholder will receive

Past earnings, balance sheets, further detailed economic analysis (quality of management, standing within its industry, prospects for the industry)

EMH implies most fundamental analysis is doomed to failure.

Competition of uncovering information◦ Many well-informed well-financed firms

conducting market research◦ Difficult to uncover special information◦ Only analysts with a unique insight will be

rewarded Not to identify firms that are good, but to

find firms that are better than everyone else’s estimate

Competition among investors◦ Only serious analysis and uncommon techniques are

likely to generate the differential insight necessary to yield trading profits

◦ Feasible economically only for managers of large portfolios

Active Management Security analysis Timing

Passive Management ◦ Aims only to establishing a well-diversified portfolio of

securities without attempting to find under-or-overvalued Buy and Hold Index Funds

Broad diversification, low management fees

if the market is efficient, what is the role of portfolio management?◦ Selection of a well-diversified portfolio ◦ Tax considerations◦ Particular risk profile of an investor

Investors’ optimal positions will vary according to factors such as age, tax bracket, risk aversion and employment, the role of the portfolio managers in an efficient market is to tailor the portfolio to these needs, rather than to beat the market

10.3 EVENT STUDIES

Event studies◦ A technique of empirical financial research,

assess the impact of a particular event on a firm’s stock price

Assessing performance of professional managers

Testing some trading rule

Empirical financial research that enables an observer to assess the impact of a particular event on a firm’s stock price

Abnormal return due to the event is estimated as the difference between the stock’s actual return and a proxy for the stock’s return in the absence of the event (benchmark return)

Benchmark return:◦ broad market index◦ the stocks matched according to criteria such as firm

size, beta, recent performance, ratio of P/B◦ Normal returns using CAPM or multifactor model

Market model to estimate abnormal returns◦ Single-index Model approach

rt = at + btrMt + et

(Expected Return)Excess Return = (Actual - Expected)

et = Actual - (at + btrMt)◦ r is decomposed into market and firm-specific factors,

the firm-specific or abnormal return may be interpreted as the unexpected return resulting from the event

◦ et : (component due to the event) Abnormal return, the return beyond what would be predicted from market movements alone

steps◦ Estimate a and b using data of the prior period◦ Record the information release date◦ Abnormal returns surrounding the announcement

Statistical significance and magnitude of the typical abnormal return assessed to determine the impact of the newly released information

Leakage of information◦ Released to a small group of investors before official public

release◦ Cumulative abnormal return

Sum of all abnormal returns over the time period of interest, capture the total firm-specific stock movement for an entire period when the market might be responding to new information

Cumulate the excess returns over time (leakage of information)

0 +t-t

10.4 ARE MARKETS EFFICIENT

Magnitude Issue◦ Hard to measure the contribution of active research◦ Actions of intelligent investment managers are the

driving force behind the evolution of prices to fair levels

Selection Bias Issue◦ The outcomes we observe have been preselected in

favor of failed attempts◦ Cannot evaluate the true ability of portfolio managers

Lucky Event Issue Possible Model Misspecification

Could speculators find trends in past prices that would enable them to earn abnormal profits◦ Test of the efficacy of technical analysis◦ Discerning trends by measuring the serial

correlation of stock market returns Tendency for stock returns to be related to

past returns serial correlation: positive, negative

Returns over short horizons (Empirical test)◦ weak price trends over short periods (weekly returns), no

existence of trading opportunities Positive serial correlation over short horizons, small

correlation coefficients of weekly returns, ◦ Short-to-intermediate-horizon price momentum in both

the aggregate market and cross-sectionally (3-12 month ) good or bad recent performance of particular stocks continues

over time Portfolios of the best-performing stocks in the recent past

appear to outperform other stocks with enough reliability to offer profit opportunities

Returns over long horizons (multiyear periods)–negative long-term serial correlation in the aggregate market ◦ Fads hypothesis, the stock market might overreact to relevant news

Overreaction leads to positive serial correlation over short time horizons

Subsequent correction leads to poor performance following good performance

Not conclusive evidence regarding efficient markets◦ May be interpreted that the market risk premium varies

over time◦ Rational response of market prices to changes in discount

rates

Observable variables to predict market returns◦ Fama and French

Aggregate returns are higher with higher dividend/price ratios, dividend yield

◦ Campbell and Shiller Earnings yield can predict market returns

◦ Keim and Stambaugh Bond spreads can predict market returns

Proxy for variation in the market risk premium

Whether publicly available information beyond trading history of a security can be used to improve investment performance to test sem-strong form

Market anomalies: findings in the market which are difficult to reconcile with the EMH

Adjust for portfolio risk before evaluating the success of an investment strategy◦ P/E Effect: Portfolios of low price-earnings ratio stocks have

higher returns: higher risk, lower price, lower P/E; higher risk, higher expected return

◦ Unless CAPM beta fully adjusts for risk, P/E will act as a useful additional descriptor of risk, associated with abnormal returns

Small Firm Effect (January Effect)◦ Dividing the NYSE stocks into 10 portfolios each year

according to firm size.◦ Average annual return are higher on the small-firm

portfolios◦ Small-firms tend to be riskier, but adjusted for risk

using the CAPM, there is still a consistent premium for the smaller-sized portfolios

◦ Invest in low-capitalization stocks, earn excess returns◦ Small-firm-in-January effect

Interpretation of the small-firm-in-january effect◦Neglected Firm effect and liquidity effect◦Book-to-Market Ratios◦Post-Earnings Announcement Drift

Neglected Firm effect and liquidity effect◦ Small firms tend to be neglected by large institutional

traders, information about smaller firms is less available◦ Arbel (1985), Divide firms into highly researched,

moderately researched, and neglected groups based on the number of institutions holding the stock, january effect was largest for the neglected firms

◦ Merton(1987), neglected firms might be expected to earn higher equilibrium returns (maybe a type of risk premium)

◦ Amihud(1986), effect of liquidity on stock returns might be a partial explanation of their abnormal returns. investors demand return premium to invest in less-liquid stocks that entail higher trading costs

Book-to-Market Ratios◦ A powerful predictor of returns, higher ratio

higher return◦ Fama and French (1992), divide firms into 10

groups according to book-to-market ratios, examine the average monthly return

◦ Dependence of returns on b/m ratio is independent of beta, b/m ratio may serve as a proxy for a risk factor that affect equilibrium expected return

◦ After control for size and book/market ratio, beta seemed to have no power to explain average security returns

Post-Earnings Announcement Drift◦ Ball and Brown (1968) , sluggish response of stock prices to

firms’ earnings announcements News content of an earning announcement be evaluated, by

comparing the announcement of actual earnings to the value previously expected by market participants. The difference is the earnings surprise.

◦ Rendleman. etc (1982), divide firms into 10 deciles based on the size of the surprise, calculate CAR. Correlation between ranking by earnings surprise and CAR. There is a

large abnormal return on the earnings announcement day Market appears to adjust to the earnings information only gradually, a

sustained period of abnormal returns (concerning stock price movement after the announcement date) CAR of positive surprise stocks continue to risk (momentum) negative surprise firms continue to suffer negative abnormal

returns

The ability of insiders to trade profitability in their own stock has been documented in studies by Jaffe, Seyhun, Givoly, and Palmon

SEC requires all insiders to register their trading activity◦ Once publish the summary of the insider trades,

the trades become public information, if markets are efficient, fully and immediately processing the information, should no profit from following the trades

How to interpret the ever-growing anomalies literature (P/E effect, small-firm, market-to-book, momentum, long-term reversal effects)◦ Related phenomena

Risk Premiums or market inefficiencies—disagreement here◦ Fama and French (1993)argue that these effects can be

explained as manifestations of risk premium ( higher betas, higher returns), three-factor model Size or B/M ratios are not risk factors, but may act as

proxies for more fundamental determinants of risk, there consistent with an efficient market in which expected returns are consistent with risk

◦ Lakonishok etc (1995)argue that these effects are evidence of inefficient markets, systematic errors in the forecast of stock analysts Extrapolate past performance too far into the future,

overprice firms with recent good performance and underprice firms with recent poor performance

Anomalies or Data Mining◦ Rerun the computer database of past returns over

and over and examine stock returns along enough dimensions: Simple chance may cause some criteria to appear to

predict returns◦ Some anomalies have not shown much staying

power after being reported in the academic literature, such as small-firm effect, B/M

EMH, in favor of capitalization-weighted indexed portfolios that provide broad diversification with minimal trading costs

Noisy market hypothesis◦ Market prices may well contain pricing errors or noise

relative to the intrinsic value.◦ Indexed portfolios invest in proportion to market

capitalization, weights will track the pricing errors, with greater amounts invested in overpriced stocks

Fundamental indexing◦ Invests in proportion to intrinsic value would avoid

the problem

Technical Analysis◦ Short horizon◦ Long horizon

Fundamental Analysis Anomalies Exist

Small Firm Effect (January Effect) Neglected Firm Market to Book Ratios Reversals Post-Earnings Announcement Drift