Market Efficiency and Behavioral Finance

Market Efficiency and Behavioral

Finance

Copyright ©2014 Pearson Education, Inc. All rights reserved. 9-2

Market Price Behavior

• Learning Goals

1. Describe the characteristics of an efficient market, explain what market anomalies are, and note some of the challenges that investors face when markets are efficient.

2. Summarize the evidence which indicates that the stock market is efficient.

3. List four “decision traps” that may lead investors to make systematic errors in their investment decisions.


Market Price Behavior

• Learning Goals (cont’d)

4. Explain how behavioral finance links market anomalies to investors’ cognitive biases.

5. Describe some of the approaches to technical analysis.

6. Compute and use technical trading rules for individual stocks and the market as a whole.


Random Walks and Efficient Markets

• Random Walk: the theory that stock price movements are unpredictable, so there is no way to know where prices are headed

– Studies of stock price movements indicate that they do not move in neat patterns

– This random pattern is a natural outcome of markets that are highly efficient and respond quickly to changes in material information

– Definition of random walk: The best prediction of the future price is today’s price.


Random Walks and Efficient Markets (cont’d)

• Efficient Market: a market in which securities reflect all possible information quickly and accurately

• To have an efficient market, you must have:– Many knowledgeable investors actively analyzing and

trading stocks

– Information is widely available to all investors

– Events, such as labor strikes or accidents, tend to happen randomly

– Investors react quickly and accurately to new information


Figure 9.1 Walmart QuarterlyRevenues


Figure 9.2 Walmart’s Stock Price


Efficient Market Hypothesis

• Efficient Market Hypothesis (EMH): information is reflected in prices—not only the type and source of information, but also the quality and speed with which it is reflected in prices. The more information that is incorporated into prices, the more efficient the market becomes.

• Levels of the EMH– Weak Form EMH– Semi-strong Form EMH– Strong Form EMH


Levels of EMH

• Weak Form EMH– Past data on stock prices are of no use in predicting future

stock price changes– Everything is random– Should simply use a “buy-and-hold” strategy

• Semi-strong Form EMH– Abnormally large profits cannot be consistently earned

using public information– Any price anomalies are quickly found out and the stock

market adjusts

• Strong Form EMH– There is no information, public or private, that allows

investors to consistently earn abnormally high returns


Figure 9.3 Daily Stock Price Reactions Surrounding Positive Earnings News

Source: Andreas Neuhierl, Anna Scherbina, and Bernd Schlusche. “Market Reaction to Corporate Press Releases,” forthcoming in the Journal of Financial and Quantitative Analysis.


Market Anomalies

• Calendar Effects– Stocks returns may be closely tied to the time of

year or time of week– Questionable if really provide opportunity– Examples: January effect, weekend effect

• Small-Firm Effect– Size of a firm impacts stock returns– Small firms may offer higher returns than larger

firms, even after adjusting for risk– (market impact of trading?)


Market Anomalies (cont’d)

• Post Earnings Announcement Drift (Momentum)– Stock price adjustments may continue after

earnings adjustments have been announced– Unusually good quarterly earnings reports may

signal buying opportunity

• Value Effect– Uses P/E ratio to value stocks– Low P/E stocks may outperform high P/E stocks,

even after adjusting for risk


Figure 9.4 Post EarningsAnnouncement Drift


Possible Explanations

• Stocks that appear to earn abnormally returns are actually riskier, so higher returns merely represent compensation for risk

• Some anomalies may simply be patterns in that data that appeared by chance and are thus not likely to persist over time

• Behavioral biases may cause investors to make systematic mistakes when they invest, and those mistakes create inefficiencies in the market


Investor Behavior and Security Prices

• Overconfidence– Investors tend to be overconfident in their judgment,

leading them to underestimate risks

• Self-Attribution Bias– Investors tend to take credit for successes and blame

others for failures– Investors will follow information that supports their beliefs

and disregard conflicting information

• These biases may cause investors to trade too often


Investor Behavior and Security Prices (cont’d)

• Loss Aversion– Investors dislike losses much more than gains– Investors will hang on to losing stocks hoping

they will bounce back

• Representativeness– Investors tend to draw strong conclusions from

small samples– Investors tend to underestimate the effects of

random chance


Investor Behavior and Security Prices (cont’d)

• Narrow Framing– Investors tend to analyze a situation in isolation,

while ignoring the larger context

• Belief Perseverance– Investors tend to ignore information that

conflicts with their existing beliefs

• Familiarity Bias– Investors buy stocks that are familiar to them

without regard to whether the stocks are good buys or not


Behavioral Finance at Work in the Markets

• Stock Return Predictability– It maybe profitable to buy underperforming

stocks when they are out-of-favor

– Momentum of stock prices up and down tends to continue over 6- to 12-month time horizons

– Value stocks may outperform growth stocks


Behavioral Finance at Work in the Markets (cont’d)

• Investor Behavior– Investors who believe they have superior

information tend to trade more, but earn lower returns

– Investors tend to sell stocks that have risen in value rather than declined

– Investors acting on emotions instead of facts may reduce market efficiency


Behavioral Finance at Work in the Markets (cont’d)

• Analyst Behavior

– Analysts may be biased by “herding” behavior, where they tend to issue similar recommendations for stocks

– Analysts may be overly optimistic about a favorite stock’s future


Using Behavioral Finance to Improve Investment Results (Table 9.1)

• Don’t hesitate to sell a losing stock

• Don’t chase performance

• Be humble and open-minded

• Review the performance of your investment on a periodic basis

• Don’t trade too much


Technical Analysis

• Before financial data/financial statements were required to be disclosed, investors could only watch the stock market itself to determine buy-or-sell decisions

• Investors began keeping “charts” of stock market movements to look for patterns, or “formations” that indicated whether to buy or sell

• Studies have shown that anywhere from 20% to 50% of the price behavior of a stock can be traced to overall market forces


Technical Analysis (cont’d)

• Technical Analysis is the study of the various forces at work in the marketplace and their affect on stock prices.– Focus is on trends in a business’ stock price and the

overall stock market

– Stock prices are a function of supply and demand for shares of stock

– Used to get a general sense of where the stock market is going in the next few months

– Several technical indicators may be used together


Market Technical Indicators

• Confidence Index– Looks at ratio between yields on high-grade

corporate bonds compared to intermediate-grade corporate bonds

– Optimism and pessimism about the future outlook is reflected in the bond yield spread

– Trend of “smart money” is revealed in bond market before it shows up in stock market


Market Technical Indicators (cont’d)

• Market Volume– Pure supply and demand analysis for

common stocks

– Strong market when volume goes up

– Weak market when volume goes down



• Breadth of the Market– Looks at number of stock prices that go up

(advances) versus number of stock prices that go down (declines)

– Strong market when advances outnumber declines

– Weak market when declines outnumber advances



• Short Interest– Looks at number of stocks that have been sold

short at any given time

– Can give two different interpretations:• Measure of Future Demand for Stock

– Strong market when short sales are high since guarantees future stock sales to cover the short positions

• Measure of Present Market Optimism or Pessimism – Weak market when short sales are high since professional

short sellers think stocks will decline



• Contrary Opinion and Odd-Lot Trading– Measures the volume of small traders

– Assumes that small traders will do just the opposite of what should be done

• Panic and sell when market is low• Speculate and buy when market is high

– Bull market when odd-lot sales significantly outnumber odd-lot purchases

– Bear market when odd-lot purchases significantly outnumber odd-lot sales


Figure 9.5 Basic Market Statistics

(Source: http://finance.yahoo.com/advances, accessed August 12, 2012.)


Trading Rules and Measures

• Advance-Decline Line

– Measures the difference between stocks closing higher and stocks closing lower than previous day

– Difference is plotted on graph to view trends

– Used as signal to buy or sell stocks

– Bull market when advances outnumber declines

– Bear market when declines outnumber advances


Trading Rules and Measures (cont’d)

• New Highs–New Lows

– Measures the difference between stocks reaching a 52-week high and stocks reaching a 52-week low

– 10-day moving average is plotted on graph to view trends


– Bull market when highs outnumber lows

– Bear market when lows outnumber highs



• The Arms Index or Trading Index (TRIN)– Combines advance-decline line with trading volume


– Bull market when TRIN values are lower

– Bear market when TRIN values are higher



• Mutual Fund Cash Ratio (MFCR)– Tracks cash position of mutual funds

– High cash positions in mutual funds provides liquidity for future stocks purchases or protection from future mutual fund withdrawals

– Bull market when MFCR values are higher

– Bear market when MFCR values are lower



• On Balance Volume– Tracks the volume to price change relationship

as a running total– Up-volume occurs when stock closes higher and

is added to running total; down-volume occurs when stock closes lower and is subtracted from running total

– Direction of indicator is more important than actual value

– Used to confirm price trends– Bull market when OBV values are higher– Bear market when OBV values are lower


Using Technical Analysis

• Charting– Shows visual summary of stock activity over

time

– Easy to use and to understand

– Use to spot developing trends


Using Technical Analysis

• Chart Formations– Looking for patterns, or formations, that

historically meant that stocks were going up or down

– Buy when stocks break through a “line of resistance”

– Sell when stocks break through a “line of support”


Figure 9.6 Some Popular Chart Formations


Using Technical Analysis (cont’d)

• Moving Averages– Tracks data (usually stock price) as average

value over time

– Used to “smooth out” daily fluctuations and focus on underlying trends

– Usually calculated over periods ranging from 10 to 200 days


Figure 9.7 A 100-Day Moving Average Line


Table 9.1 Using Behavioral Finance to Improve Investment Results

Documents

Market Efficiency and Behavioral Finance