The Efficient Market Hypothesis

Dr. Himanshu JoshiFORE School of Management

New Delhi

The Efficient Market Hypothesis

• One of the earliest application of computers in economics was to analyze economic time series. Business theorist felt that tracing the evolution of several economic variables over time would clarify and predict the progress of the economy through boom and bust periods.

Assumption for stock prices..

• A natural candidate for analysis was the behavior of stock market prices over time.

• Assuming that stock market prices reflect prospects of the firm, recurrent patterns of peaks and trough in economic performance ought to show up in these prices.

The Experiment and the Result..

• Maurice Kendall examined this proposition in 1953. he found to his great surprise that he could identify no predictable patterns in stock prices.

• Prices seems to evolve randomly.• They were likely to go up as they were to go

down on any particular day, regardless of past performance.

• The data provided no way to predict price movements.

Interpretation..

• Kendall’s results were disturbing to some financial economists. They seemed to imply that stock market is dominated by erratic market psychology. It follows no logical rules.

• So result seems to confirmed irrationality of the market.

Random Walks and the Efficient Market Hypothesis

• Suppose Kendall had discovered that stock prices are predictable.

• What a gold mine this would have been.• If they could use the Kendall’s equations to

predict stock prices, investors would reap unending profits simply by purchasing stocks that the computer model implied were about to increase in price and by selling those stocks about to fall in price.

Model predicts???

• Suppose model predict with great confidence that Infosys share, currently at $100 would increase dramatically in 3 days to $110.

• What would all investors with access to the model’s prediction do today?

• When price of Infosys will reach $110.

Model?

• This simple example illustrate why Kendall's attempt to find recurrent patterns in stock price movements was likely to fail.

• A forecast about favorable future price performance leads to favorable current performance, as market participants all try to get into the action before price jump.

Revised Interpretation of Random Walk.

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

• As soon as there is any information indicating that stock is underpriced and therefore offer a profit opportunity, investors flock to buy the stock and immediately bid up its price to a fair level, where only ordinary rates of return can be expected.

• These “ordinary rates” are simply rate of return commensurate with the risk of the stock.

Random Walk and EMH..

• This is the essence of the argument that stock prices should follow a random walk, that is that price should be random and unpredictable.

• Therefore, the notion that stocks already reflect all available information is referred to as the efficient market hypothesis. (EMH.)

Application.

• On January 9, 2009, Sensex fell from 9586.88 points to 9406.47 points, a decline of 1.88%. If the sale of Siemens Information Systems Limited is a value-neutral decision, then Siemen’s stock price should have fallen by 1.88% × 0.86, that is 1.62%.

• However, on Jan 9, 2009, the price of Siemens fell from 298 to 260.7, a decline of 12.52%. If we assume that on January 9, 2009 the stock market did not get any other value relevant information about Siemens (other than the sale of its 100% subsidiary), then the entire difference of 10.9% decline (12.52% - 1.62%) can be attributed to this sale transaction.

Examples of Random Walk Cumulative Abnormal Returns Before Takeover Attempts: Target

Companies

Examples of Random Walk Stock Price Reaction to CNBC Reports

Competition as the source of efficiency.

• Stock prices fully and accurately reflect publicly available information.

• Once information becomes available, market participants analyze it.

• Competition assures prices reflect information.

IS Equity Research is a Wasteful Exercise?

Competition as the source of efficiency..

• Why should we expect stock prices to reflect all available information?• After all if you are willing to spend time and money on gathering

information, it might seem reasonable that you could turn up something that has been overlooked by the rest of the investment community.

• When information is costly to uncover and analyze, one would expect investment analysis calling for such expenditures to result in an increased expected return.

• Investors will have an incentive to spend time and resources to analyze and uncover new information only if such activity is likely to generate higher investment returns.

• Thus, in market equilibrium, efficient information gathering should be fruitful.

• Weak (Stock Prices reflect all past trends)

• Semi-strong (Stock Prices reflect all public information)

• Strong (Stock Prices reflect all information public or private)

Versions of the EMH

Quiz?

Q1.Suppose you observe that high level managers make superior returns on investments in their company’s stock. Would this be violation of weak-form market efficiency? Would it be violation of semi strong form market efficiency?

Q2.If the weak form of the efficient market hypothesis is valid, must the strong form also hold?

• Conversely, does strong-form efficiency imply weak form efficiency?

• 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

Types of Stock Analysis

Technical Analysis

• Technical analysis is essentially the search for recurrent and predictable patterns in stock prices.

• Although Technicians recognize the value of information regarding future economic prospects of the firm, they believe that such information is not necessary for successful trading strategy.

• This is because whatever the fundamental reason for change in stock price, if the stock price responds slowly enough, the analyst will be able to identify a trend that can be exploited during the adjustment period.

Technical Analysis

• Thus the key to successful technical analysis is a sluggish response of stock prices to fundamental supply and demand factors.

• This prerequisite is of course, diametrically opposed to the notion of an efficient market hypothesis.

Technical Analysis

• Relative Strength Approach (Ratio of Stock Price to Market Indicator)

• Resistance and Support level.

If everyone in the market believe in resistance levels, why do these beliefs not become self-fulfilling prophecies?

• The market dynamic is one of a continual search for profitable trading rules, followed by destruction by overuse of those rule found to be successful, followed by more search for yet to be discovered rules.

Fundamental Analysis

• Fundamental Analysis uses earnings and dividend prospects of the firm, expected future interest rates, and risk evaluation of the firm to determine proper stock prices.

• Here we try to determine present discounted value of all the payments a stockholder will receive from each share of stock.

• If the value exceeds the stock price, buy it.

Fundamental Analysis

• FCFF • FCFE

• Active Management– Security analysis– Timing

• Passive Management– Buy and Hold– Index Funds

Active or Passive Management

27

Money Magazine – Oct. 03Top Picks from 24 Top Pros – Invest in the Best

• Asked some “first-rate investing minds to share their best ideas.”

• “We call this gathering of wise minds the Ultimate Investment Club.”

• The 24 top pros identified 34 domestically traded stocks as their top picks.

• Each pick was backed by brilliant and compelling logic.

EXAMPLE

The Ultimate Investment Club destroyed 14% vs. the Market!

First Rate Investing Minds

-2.4%

+11.5%US Stock Market

Twelve months ended August 31, 2004. Source: Calculated from Yahoo Finance - included dividend reinvestment. This included six stock picks listed on US exchanges but not included in the Wilshire 5000 Total Stock Index. The 28 US domiciled stocks had a -7.6% return which lagged the index by 19%.

THE STORY MONEY MAGAZINE NEVER PUBLISHEDBUT THE COLORADO SPRINGS BUSINESS JOURNAL DID

Even if the market is efficient a role exists for portfolio management:

• Appropriate risk level• Tax considerations• Other considerations

Market Efficiency & Portfolio Management

• 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

Event Studies

• Returns are adjusted to determine if they are abnormalMarket Model approach

a. rt = at + brmt + et

(Expected Return)

b. Excess Return = (Actual - Expected)

et = rt - (a + brMt)

How Tests Are Structured

• Magnitude Issue• Selection Bias Issue• Lucky Event Issue

Are Markets Efficient?

• Magnitude Issue: Bodie and Kane noted that an investment manager overseeing a $5 billion portfolio who can improve performance by only 0.1% per year will increase investment earning by $5 billion*0.1% = $5 million.

• The manager clearly would worth her salary.• Can we statistically measure her contribution?• Given the annual SD of S&P 500 portfolio is 20%.• All might agree that stock prices are very close to fair values

and that only managers of very large portfolios can earn enough trading profits to make the exploitation of minor mis-pricing worth the effort.

• Are market efficient? Should now be how efficient are markets?

Are Markets Efficient?

Are Market efficient?

• The Selection Bias:• Suppose that you discover an investment

scheme that could really make money.• You have two choice:• Either publish your technique in ‘wall street

journal’ to win fleeting fame, or• Keep your technique secret and use it to earn

millions of dollars.

Selection bias..

• Only investors who find that an investment scheme can not generate abnormal return will be willing to report their finding to the whole world.

• This is called selection bias: the outcome we are able to observe are preselected in favor of failed attempts.

Are market efficient?

• The Lucky Event Issue: in virtually any month it seems we read an article about some investor or investment company with fantastic investment performance over the recent past.

• Surely the superior records of such investors disprove the efficient market hypothesis.

The Lucky Event Issue..

• Consider a contest to flip the most number of heads out of 50 trials using a fair coin.

• The expected outcome for any person, is of course, 50% heads and 50% tails.

• If 10,000 people, however compete in this contest, it would not be surprising if atleast one or two contestant flipped more than 75% heads.

• In fact statistically there will be 2 contestants flipping more than 75% heads.

• It would be silly to crown these people the “the head flipping champions of the world”.

The Lucky Event Issue

• The analogy to efficient market is clear.• Under the hypothesis that any stock is fairly

priced given all available information, any bet on a stock is a simply a coin toss.

• The winners, though, turn up in Wall Street Journal as the latest STOCK MARKET GURUS. Then they can make fortune publishing market newsletters and providing market buy, sell or hold advice.

Weak-Form Tests: Pattern in Stock Return

• Returns over the Short Horizons: could speculators find trends in past prices that would enable them to earn abnormal profits?– Momentum & Serial Correlation– Serial correlation refers to the tendency for stock

returns to be related to past returns.– Positive serial correlation means that positive returns

tend to follow positive returns (Momentum property) – Negative serial correlation means that negative returns

tend to be followed by positive returns. (A reversal or correction property).

Returns over short HorizonsEmpirical Evidences

• Conrad and Kaul and Lo and MacKinlay examine weekly returns of NYSE stocks and find positive serial correlation over short horizons.

• However correlation coefficient of weekly returns tends to be fairly small, at least for large stocks for which price data are the most reliably up-to-date.

• There appears to be stronger momentum in performance across market sectors exhibiting best and worst recent returns.

• In an investigation of intermediate –horizon stock price behaviour (3-12 months) Jagdeesh and Titman found a momentum effect in which good or bad recent performance of particular stock continues over time.

Returns over Long Horizons

• Long term horizon returns (i.e., return over multiyear periods) have found suggestions of pronounced negative long term serial correlation in the performance of aggregate market.

• fad hypothesis: it asserts that stock market may over react to relevant news. Such overreaction leads to positive serial correlation (momentum) over short time horizons. Subsequent correction of the overreaction leads to poor performance following good performance and vice versa.

• These episodes of apparent overshooting followed by correction give stock market the appearance of fluctuating around its fair value.

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

• P/E Effect (Sanjoy Basu)• Small Firm Effect (Banz)• Neglected Firm Effect and Liquidity Effects (Arbel

and Strebel)• Book-to-Market Ratios• Post-Earnings Announcement Price Drift

Semistrong Tests: Anomalies

The Neglected Firm Effect and Liquidity Effect

• Arbel and Strebel gave another interpretation of small-firm-in-January effect. Because small firms tend to be neglected by large institutional investors, information about smaller firms is less available.

• This information deficiency makes smaller firms riskier investments that command higher returns.

• “Brand name” firms are after all subject to considerable monitoring from institutional investors, which promises high quality information, and investors presumably do not purchase “generic stocks” without prospects of greater returns.

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

Average Return as a Function of Book-To-Market Ratio (FAMA and FRENCH

Model)• Fama and French showed that a powerful

predictor of returns across securities is the ratio of the book value of the firm’s equity to the market value of equity.

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

Result..

• The deciles with highest book-to-market ratio had an annual return of 16.84%, while the lowest decile averaged only 11.12%.

• The dramatic dependence of return on book to market ratio of the firm is independent of beta, suggesting either that:

• High book-to-market ratio firms are relatively underpriced (inefficient market)

• Or that the book-to-market ratio is serving as a proxy for a risk factor that affects equilibrium expected return.

Cumulative Abnormal Returns in Response to Earnings Announcements

• A fundamental principle of efficient market is that any new information ought to be reflected in stock price very rapidly. When good news is made public, the stock price should jump immediately.

• A puzzling anomaly, is therefore, sluggish response of stock prices to firm’s earning announcements, as discovered by Ball and Brown.

Cumulative Abnormal Returns in Response to Earnings Announcements

• Randleman, Jones and Latane provide influential study of sluggish price response to earning surprises for a large sample of firms, rank the magnitude of the surprise, divide firms into 10 deciles based on size of surprise, and calculate abnormal returns for each decile.

Figure 11.5 Cumulative Abnormal Returns in Response to Earnings Announcements

Results

• There is a large abnormal return (a jump in cumulative abnormal return) on the earning announcement day (day 0).

• The abnormal return is positive for positive-surprise firm and negative for negative-surprise firms.

• The more remarkable result of the study is that even after the announcement date stock price of positive-surprise firms continue to rise.

• In other words, exhibits momentum-even after the earning information become public.

Strong-Form Tests: Inside Information

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

• SEBI requires all insiders to register their trading activity

Interpreting the Evidence

• Risk Premiums or market inefficiencies—disagreement here– Fama and French argue that these effects can

be explained as manifestations of risky stocks with higher betas

– Lakonishok, Shleifer, and Vishney argue that these effects are evidence of inefficient markets

Interpreting the Evidence Continued

• Anomalies or Data Mining• The noisy market hypothesis• Fundamental indexing

Noisy Market Hypothesis and Fundamental Indexing

• The EMH argues in favor of Capitalization-weighted indexed portfolios that provides broad diversification with minimal trading costs.

• but several researchers and practitioners have forcefully argued that such “cap-Weighted” indexing is necessarily inferior to a strategy they call fundamental indexing.

• It is called noisy market hypothesis. The hypothesis begin with the observation that market prices may well contain pricing errors or “noise” relative to intrinsic value or true value of a firm.

Noisy Market Hypothesis and Fundamental Indexing

• Even if prices are correct on average, at any time some stocks will be overvalued and others undervalued.

• Because indexed portfolios invest in proportion to market capitalization, portfolio weights will track these pricing error, with greater amounts invested in overpriced stocks (which have poor expected returns) and lesser amounts in underpriced stocks (which have higher expected return)

• The conclusion is that a capitalization weighted strategy is destined to overweight the firms with the worst returns propects.

Stock Market Analysts

• Do Analysts Add Value–Mixed evidence– Ambiguity in results

•Thank You