1. Market Efficiency and Behavioral Finance

2. Market Price Behavior Learning Goals
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.
Summarize the evidence which indicates that the stock market is efficient.
List four “decision traps” that may lead investors to make systematic errors in their investment decisions.

3. Market Price Behavior Learning Goals (cont’d)
Explain how behavioral finance links market anomalies to investors’ cognitive biases.
Describe some of the approaches to technical analysis.
Compute and use technical trading rules for individual stocks and the market as a whole.

4. 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.

5. 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

6. Figure 9.1 Walmart Quarterly Revenues

7. Figure 9.2 Walmart’s Stock Price

8. 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

9. Levels of EMH Weak Form EMH Semi-strong Form EMH Strong 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

10. 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.

11. Market Anomalies Calendar Effects Small-Firm Effect
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?)

12. 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

13. Figure 9.4 Post Earnings Announcement Drift

14. 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

15. 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

16. 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

17. 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

18. 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

19. 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

20. 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

21. 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

22. 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

23. 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

24. 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

25. 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

26. Market Technical Indicators (cont’d)
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

27. Market Technical Indicators (cont’d)
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

28. Market Technical Indicators (cont’d)
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

29. Figure 9.5 Basic Market Statistics
(Source: accessed August 12, 2012.)

30. 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

31. 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
Used as signal to buy or sell stocks
Bull market when highs outnumber lows
Bear market when lows outnumber highs

32. Trading Rules and Measures (cont’d)
The Arms Index or Trading Index (TRIN)
Combines advance-decline line with trading volume
Used as signal to buy or sell stocks
Bull market when TRIN values are lower
Bear market when TRIN values are higher

33. Trading Rules and Measures (cont’d)
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

34. Trading Rules and Measures (cont’d)
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

35. Using Technical Analysis
Charting
Shows visual summary of stock activity over time
Easy to use and to understand
Use to spot developing trends

36. 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”

37. Figure 9.6 Some Popular Chart Formations

38. 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

39. Figure 9.7 A 100-Day Moving Average Line

40. Table 9.1 Using Behavioral Finance to Improve Investment Results