Chapter 12 Market Efficiency and Behavioral Finance

Efficient Market Hypothesis (EMH) Are security markets efficient relative to the information available for valuing securities? Do security prices reflect relevant information quickly and accurately? Why look at market efficiency? Implications for business and corporate finance Implications for investment

Random Walk - stock price changes are random Random Walk and the EMH Random Walk - stock price changes are random Actually submartingale Expected price is positive over time Positive trend and random about the trend

Random Walk with Positive Trend Security Prices Time

Market Efficiency The Efficient Market Hypothesis (EMH) is a hypothesis that asserts: As a practical matter, the major financial markets reflect all relevant information at a given time. Market efficiency research examines the relationship between stock prices and available information. The important research question: Is it possible for investors to “beat the market?” Prediction of the EMH theory: If a market is efficient, it is not possible to “beat the market” (except by luck).

What Does “Beat the Market” Mean? The excess return on an investment is the return in excess of that earned by other investments that have the same risk. “Beating the market” means consistently earning a positive excess return.

Forms of Market Efficiency, (i.e., What Information is Used?) A Weak-form Efficient Market is one in which past prices and volume figures are of no use in beating the market. If so, then technical analysis is of little use. A Semistrong-form Efficient Market is one in which publicly available information is of no use in beating the market. If so, then fundamental analysis is of little use. A Strong-form Efficient Market is one in which information of any kind, public or private, is of no use in beating the market. If so, then “inside information” is of little use. Securities law regulates insider trading, so the law believe markets are not strong form efficient.

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.

Random Price Changes Why are price changes random? Prices react to information Flow of information is random Therefore, price changes are random

EMH and Competition Stock prices fully and accurately reflect publicly available information. Once information becomes available, market participants analyze it. Competition assures prices reflect information.

Types of Stock Analysis Technical Analysis - using prices and volume information to predict future prices. If securities markets are weak form efficient, then technical analysis is useless Fundamental Analysis - using economic and accounting information to predict stock prices. If securities markets are semi strong form efficient, then fundamental analysis is useless

Technical Analysis Technical analysis differs significantly from fundamental analysis. Technical analysis is a controversial set of techniques for predicting market direction based on Historical price and volume behavior Investor sentiment Technical analysts essentially search for bullish (positive) and bearish (negative) signals about stock prices or market direction.

Dow Theory, I. The Dow theory is a method that attempts to interpret and signal changes in the stock market direction. Historically, quite popular. The Dow theory identifies three forces: a primary direction or trend, a secondary reaction or trend, and daily fluctuations Daily fluctuations are essentially noise and are of no real importance.

Secondary trends, temporary departures Dow Theory, II. The primary direction is either bullish or bearish, and reflects the long-run direction of the market. Secondary trends, temporary departures Corrections, reversions to the primary direction

The trend is your friend… Dow Theory, III. Purpose: to signal changes in the primary direction. Must monitor two indexes: Dow Jones Industrial Average Dow Jones Transportation Average If ONE index departs from the primary direction, this is not a signal. However, if a departure in one is followed by a departure in the other, this is viewed is confirmation that the trend has changed. The trend is your friend…

Support and Resistance Levels A support level is a price or level below which a stock or the market as a whole is unlikely to go, while a Resistance level is a price or level above which a stock or the market as a whole is unlikely to rise. Resistance and support areas are usually viewed as psychological barriers Bargain hunters help “support” the lower level. Profit takers “resist” the upper level. A “breakout” occurs when a stock (or the market) passes through either a support or a resistance level.

Market Diaries, A Collection of Technical Indicators

Technical Indicators, Notes The “advance/decline line” shows, for some period, the cumulative difference between advancing and declining issues. “Closing tick” is the difference between the number of shares that closed on an uptick and those that closed on a downtick. “Closing arms” or “trin” (trading index) is the ratio of average trading volume in declining issues to average trading volume in advancing issues. Using data from the "Previous Close:" “zBlock trades” are trades in excess of 10,000 shares.

Charting, Relative Strength Relative strength charts measure the performance of one investment relative to another. Comparing stock A to stock B, through relative strength. Month Stock A (4 Shares) Stock B (2 Shares) Relative Strength 1 $100 1.00 2 96 3 88 90 0.98 4 80 1.10 5 78 1.03 6 76

Charting, Moving Averages Moving average charts are average daily prices or index levels, calculated using a fixed number of previous days’ prices or levels, updated each day. Because daily price fluctuations are “smoothed out,” these charts are used to identify trends. Example: Suppose the technical trader calculates a 15-day and a 50-day moving average of a stock price. If the 15-day crosses the 50-day from above, it is a bearish signal—time to sell. If the 15-day crosses the 50-day from below, it is a bullish signal—time to buy.

Example: 15-Day and 50-Day Moving Averages Note the "whipsaw" action—i.e., plenty of buying and selling signals. This happens because 15 and 50 may be too "close" together in time.

More Chart Types A hi-lo-close chart is a bar chart showing, for each day, the high price, low price, and closing price. A candlestick chart is an extended version of the hi-lo-close chart. It plots the high, low, open, and closing prices, and also shows whether the closing price was above or below the opening price.

Candlestick Making, Basics

Candlestick “Formations”

Point and Figure Charts, I. Point-and-figure charts attempt to show only major price moves and their direction. The point and figure chart maker decides what price move is major. That is, it could be $2, $5, or any other level. A major up-move is marked with an “X” A major down-move is marked with an “O” Start a new column when there is a direction change. Buy and sell signals are generated when new highs or new lows are reached. Congestion area, the area between buy and sell signals—a time of market indecision concerning its trend.

Point and Figure Charts, II.

Point and Figure Charts, III.

Chart Formations Once a chart is drawn, technical analysts examine it for various formations or pattern types in an attempt to predict stock price or market direction. One example is the head-and-shoulders formation. When the stock price “pierces the neckline” after the right shoulder is finished, it is time to sell.

Chart Formations, The Head and Shoulders

Other Technical Indicators The “odd-lot” indicator looks at whether odd-lot purchases are up or down. Followers of the “hemline” indicator claim that hemlines tend to rise in good times. The Super Bowl indicator forecasts the direction of the market based on who wins the game. Two Conference representatives play in the Super Bowl: one from the National Football Conference and one from the American Football Conference. A win by the National Football Conference (or one of the original members of the National Football League) is bullish.

Are Financial Markets Efficient? Nevertheless, three generalities about market efficiency can be made: Short-term stock price and market movements appear to be difficult to predict with any accuracy. The market reacts quickly and sharply to new information, and various studies find little or no evidence that such reactions can be profitably exploited. If the stock market can be beaten, the way to do so is not obvious.

Some Implications if Markets are Efficient Security selection becomes less important, because securities will be fairly priced. There will be a small role for professional money managers. It makes little sense to time the market.

Active or Passive Management Active Management Security analysis Timing Passive Management Buy and Hold Index Funds

Market Efficiency & Portfolio Management Even if the market is efficient a role exists for portfolio management: Diversification still matters Tax considerations Appropriate risk level Other considerations Age Personal knowledge Personal circumstances

Empirical Tests of Market Efficiency Event studies Assessing performance of professional managers Testing some trading rule

Event Studies: How Tests Are Structured 1. Examine prices and returns over time

-t +t Announcement Date Returns Over Time -t +t Announcement Date

How Tests Are Structured (cont’d) 2. Returns are adjusted to determine if they are abnormal. Market Model approach a. Rt = at + btRMt + et (Expected Return) b. Excess Return = (Actual - Expected) et = Actual - (at + btRMt)

How Tests Are Structured (cont’d) 2. Returns are adjusted to determine if they are abnormal. Market Model approach Cumulate the excess returns over time: See Figure 12.1 -t +t

Issues in Examining the Results Magnitude Issue Someone researching for a large fund only needs a small gain to justify the research – too small too measure, relative to noise Selection Bias Issue Those who know how to beat the market keep it a secret (or else everyone would do it; thus, we don’t know how to study those who beat the market

Issues in Examining the Results Lucky Event Issue Was it luck or skill? Even in a “Candy Land” tournament, there will be a winner (and a loser) Possible Model Misspecification Are we making the correct risk adjustment when we make our comparisons. What if beta is not the correct way to measure risk? What if risk changes over time? Data snooping – all random data will have parts that look non random

What Does the Evidence Show? Technical Analysis Short horizon: Very short time horizons (weekly) shows some reversals, but not enough to trade profitably on (Negative serial correlations). Longer horizons (3 month to a year) shows that momentum exits, not in individual stocks, but in portfolios, with enough gain to cover trading costs (positive serial correlations). Long horizon: Fama and French find a long term negative serial correlation in the aggregate market. DeBont and Thaler find contrarian investing (winner and loser portfolios) over 5 years leads to excess return (January to January). Other researchers found much of the effect disappears if one looks at July to July.

What Does the Evidence Show? Fundamental Analysis Broad market returns seem to be influenced by dividend yields, earnings yields, bond yield spreads. These may simply be proxies for changing betas. Many event studies reinforce semi strong market efficiency such as Figure 12.1

What Does the Evidence Show? Anomalies Exist Anomalies are empirical results that are known, but should not exist in an efficient market. Is that beta is an incomplete or even wrong measure of risk, or are markets not efficient? For example, Basu found a P/E effect, after adjusting for Beta. Is there a P/E effect, or is P/E just a measure of the firm risk, that adjust quickly, while a beta measurement is based on long term data?

Stock Price Behavior and Market Efficiency The day-of-the-week effect refers to the tendency for Monday to have a negative average return.

The Amazing January Effect, I. The January effect refers to the tendency for small stocks to have large returns in January. Does it exist for the S&P 500?

The Amazing January Effect, II. The January effect refers to the tendency for small stocks to have large returns in January. What do we see when we look at returns on small stocks?

The Market Crash in October 1987 On October 19, 1987 (Black Monday), the Dow plummeted 500 points to 1,700. Investors lost about $500 billion in share value. The market lost over 20% of its value. The volume was a record at the time: 600 million shares. Today the NYSE has circuit breakers. Rules that kick in to slow or stop trading when the DJIA decreases (or increases) by more than a pre-set amount in a trading session.

The Performance of Professional Money Managers From 1963 to 1998, the S&P 500 index outperformed general equity mutual funds 22 times (out of 36). Why can’t the pros beat the averages? (You can hold a market average very easily—SPDRs)

Other Anomalies Neglected Firm Market to Book Ratios Neglected firms are typically small firms for which there is little analyst coverage. Tend to have higher returns – may be due to lack of liquidity. Suggests this a risk premium in addition to beta Market to Book Ratios market to book ratios seem to explain returns better than beta Post-Earnings Announcement Drift ( see Figure 12.7). The reaction to earnings announcement continues after the announcement date.

Strong Form Efficiency Tests Tests of insider trading suggests that insiders can usually beat the market suggest that markets are relatively efficient, up to semi strong form. Trying to mimic insiders does not seem to be of value, after their trades are reported.

Explanations of Anomalies May be risk premiums (but not beta) Behavioral Explanations What if people don’t act rationally? Does that mean prices are irrational? Some irrational decisions will create profit opportunities for arbitrageurs, so there will be limits to the degree of irrationality.

Information Processing Forecasting Errors – people put too much weight on recent evidence (one good exam grade does not necessarily mean you will ace the course or one good quarter does not means the firms prospects are forever better) Overconfidence – people tend to be over confident in their beliefs. Those who trade a lot (confident in their beliefs) do worse than others. Conservatism – some people under react Sample Size Neglect and Representativeness – anecdotal evidence move people more than large statistical samples

Behavioral Biases Framing – On the risk tolerance quiz, the same question mathematically, often reversed the answer, when asked a different way Mental Accounting – we budget in our mind for certain things. People are more likely to make risky gambles with the “house” money than with their own. Regret Avoidance – certain losses cause more pain than others, even if the dollar amount is the same.

Limits to Arbitrage Fundamental Risk – if prices wander too long, those trying to gain, may in the short term lose (E.g. Priceline short seller) Implementation Costs - transactions costs may limit arbitrage. Model Risk – what if your arbitrage model is wrong? Result: Prices could be wrong (do not reflect fundamentals) but its hard to profit from the apparent opportunities. In other words, absence of profit potential does not imply EMH

Mutual Fund Performance Some evidence of persistent positive and negative performance. Potential measurement error for benchmark returns. Style changes: When Elton et. Al. compared results to 3 potential index funds (large stocks, small stocks, bonds), mutual funds showed negative (but mostly not significant) alphas. May be risk premiums

So, are markets efficient? There’s the story of the finance professor walking with a graduate student who spies a $20 bill on the sidewalk. The professor says there is no point picking up the $20 bill as if there really was a $20 bill on the sidewalk someone else would have picked it up already Superstar phenomenon: Who are the best investors of all time? Peter Lynch, Warren Buffet, John Templeton, Jeff Neff. Why are there so few in the club?