1. Fin2802: Investments Spring, 2010 Dragon Tang
Lectures 11&12
Behavioral Finance and Technical Analysis
February 23&25, 2010
Readings: Chapter 12
Practice Problem Sets: 1,2,4,10, 11
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

2. Where Are We? How? Why? What? Securities Markets Institutions Trading
Delegated investment
Why?
Market efficiency Historical performance
What?
Stock
Bond
Evaluation
International
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

3. Where Are We? How? Why? What? So What? Securities Markets Institutions
Trading
Delegated investment
Why?
Market efficiency Historical performance
What?
Stock
Bond
Evaluation
International
So What?
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

4. Behavioral Finance and Technical Analysis
Objectives:
Understand the principles of behavioral finance.
Identify reasons why technical analysis may be profitable.
Use the Dow theory to identify situations that technicians would characterize as buy or sell opportunities.
Use indicators such as volume, breadth, short interest, or confidence indexes to measure the "technical condition" of the market.
Explain why most of technical analysis is at odds with an efficiently functioning stock market.
We have seen that Fundamental Analysis deals with expectations and forecast.
Today we look at Technical Analysis. This is a technique used by practitioner which focus very little on the fundamentals of a stock but try to determine the direction of a stock price in the market by looking at past patterns. Although void of almost any theoretical foundation it is used a lot by practitioner. We will briefly look at it just to have an idea of what traders do actually use. It will be a descriptive analysis. I am rather skeptical of the efficiency of all this.
Mention that nevertheless there is a Paper by Jian Wang and Andy Lo who look at the efficient of some of these strategies. Some might make sense in a context of asymmetric info.
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

5. Chapter 12: Behavioral Finance and Technical Analysis
Traditional theories (e.g., CAPM) assume rational investors
Systematic behavioral biases (anomalies) have been observed
Behavioral finance tries to incorporate some aspect of investors’ behavior and explain those anomalies using psychological principles
It is a developing and important area
Companies exploiting behavioral biases:
Lakonishok, Shleifer and Vishny (LSV)
Dimensional Fund Advisors (DFA)
Fuller and Thaler Asset Management
Case-Shiller-Weiss
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

6. Chapter 12: Behavioral Finance and Technical Analysis
Individual Behavior
Cooperation and Altruism
Bidding and the Winner’s Curse
Endowment Effect, Status Quo Bias and Loss Aversion
Mental Accounts
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

7. Figure 12-1 Loss Aversion Preference Function
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

8. Asset Returns and Behavioral Explanations
Calendar Effects
Cash Dividends
Overreaction and Mean Reversion
Controversial explanations from behavioral finance
Closed-end fund discount puzzle
Excess volatility in stock prices
Loss aversion
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

9. Chapter 12: Behavioral Finance and Technical Analysis
Limits to Arbitrage
Fundamental Risk
Implementation Costs
Model Risk
Siamese Twin Companies
Equity Carve-outs
Closed-End Funds
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

10. Chapter 12: Behavioral Finance and Technical Analysis
Figure 12.2 Pricing of Royal Dutch Relative to Shell (Deviation from Parity)
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

11. Chapter 12: Behavioral Finance and Technical Analysis
Attempts to exploit stock price patterns for profit.
Assumes prices adjust slowly to their true equilibrium values
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

12. Technical Analysis and EMH
Technical analysis clashes with the EMH hypothesis.
EMH predicts rapid adjustment of prices with the onset of new information.
Evidence for the success of technical analysis is poor.
Perspective: Expect the question, “If you’re so smart, why don’t you make the money technical analysts make?” The answer is that many people will pay for the illusion of certainty. After all, palm readers have been around for a long time.
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

13. Technical Analysis Tool-kit
Charting: The analysis of “charts” of stock price and volume with the hope of finding patterns to exploit in the markets.
The Dow Theory
Point and Figure Chart
Elliott Wave Theory
Technical Indicators
Sentiment Indicators: Market Volume (Trin Statistic); Odd-lot Trading; Confidence Index; Put/Call Ratio; Mutual Fund Cash Position
Flow of Funds: Short Interest; Credit balances in brokerage accounts
Market Structure: Moving Averages; Breadth; Relative Strength;
Let’s see what’s in the perfect technical analyst tool-kit. What kind of things these people use.
Charting is the study of past patterns.
Technical Analyst are sometimes called Chartist since they study records or charts of past stock prices and volume.
Technical indicators: indicators behind patterns used to predict future market directions.
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

14. Charting: The Dow Theory
Uses price and volume trends to predict stock prices.
Identifies primary, secondary, and tertiary trends.
Predicts support and resistance price levels.
Dow theory -- A technique that attempts to discern long- and short- term trends in stock market prices.
The primary trend is the long-term movement of prices, lasting from several moths to several years.
Secondary or intermediate trends are caused by short-term deviations of prices from the underlying trend line. (These deviations are eliminated via corrections when prices revert back to trend values).
Tertiary or minor trends are daily fluctuations of little importance.
Support level -- A price level below which it is supposedly unlikely for a stock or stock index to fall.
Resistance level -- A price level above which it is supposedly unlikely for a stock or stock index to rise.
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

15. Figure 19-2 Dow Theory Trends
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

16. Figure 19-3 Dow Jones Industrial Averages in 1988
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

17. Charting: Elliott Wave Theory
Stock prices can be described by a set of wave patterns
Long-term and short-term wave cycles are superimposed on each other
By interpreting the cycles, one can predict broad movements
Kontradieff wave theory: Market moves in cycles of 50yrs…yeah right!
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

18. Figure 19-4 Point and Figure Chart for Table 19-2
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

19. Table 19-2 Stock Price History
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

20. Figure 19-5 Point and Figure Chart for Atlantic Richfield
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

21. Figure 19-6 Candlestick Chart
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

22. Chapter 12: Behavioral Finance and Technical Analysis
Charting: A Warning
A Warning:
Seeing patterns that don’t exists
After the fact, one can always find patterns and trading rules that would have generated enormous profits
What has worked in the past may not work in the future.
Show coin toss pattern.
Show movie about who wins the superbowl.
Perspective: An old exercise that Burton Malkiel has used might be helpful here. Have the students construct a chart of a hypothetical stock’s price changes using coin tosses. Start with a stock price of $50. Let the price rise by a dollar if a head is tossed. Let the price fall by a dollar if a tail is tossed. Construct these charts for 30 to 50 “days” (one toss per day). With 15 or more students in the class, the chances are good for getting some ”classic” patterns. (See A Random Walk Down Wall Street).
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

23. Figure 19-7 Actual and Simulated Stock Prices for 52 Weeks
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

24. Chapter 12: Behavioral Finance and Technical Analysis
Figure 19-8 Actual and Simulated Changes in Weekly Stock Prices for 52 Weeks
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

25. Technical Indicators: Sentiment Indicators
Market Volume: Higher volume gives strong confirmation to price trend.
Trin>1: Bear Market; Trin<1: Bull Market
Odd-lot Trading (less than 100 shares): Small investors tend to miss key market turning points.
- Odd-lot buying heavy Þ investors should be bearish.
- Odd-lot selling heavy Þ investors should be bullish.
Market advances are a more favorable omen of continued price increases when they are associated with increased trading volume (see homework problem 2). Market reversals are considered more bearish when associated with higher volume.
The trin statistic is the ratio of the average volume of a declining issue divided by the average volume of an advancing issue.
Odd-lot trading – Assumes that small investor are stupid! The theory that net buying of small investors is a bearish signal for a stock.
Assumption is that odd-lot traders don’t know what they are doing.
Odd lot is fewer than a round lot of 100 shares.
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

26. Technical Indicators: Sentiment Indicators
Confidence Index:
Closer to 100% Þ investors should be bullish
Away from 100% Þ investors should be bearish.
Put/Call Ratio: Ratio normally hovers around 65%.
Rising ratio Þ investors should be bearish?
Rising ratio Þ investors should be bullish?
Mutual Fund Cash Positions
More cash Þ bearish?
Confidence index -- Ratio of the yield of top-rated corporate bonds to the yield on intermediate grade bonds.
When bond traders are optimistic about the economy, the yield spread will narrow and the confidence index will approach 100%.
Put/Call ratio is the outstanding put options to outstanding call options. Typically this hovers around 65%.
A change in the ratio can be given a bullish or a bearish interpretation.
A rising ratio is taken as a sign of broad investor pesssimism and a coming market decline.
Contrarian investors believe that a good time to buy is when the rest of the market is bearish because stock prices are then unduly depressed. Therefore, they would take an increase in the Put/Call ratio as a ginal of a buy opportunity.
Before Sept 11, for airline stocks a 250% put/call ratio has been observed. SEC is investigating.
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

27. Technical Indicators: Flows of Funds
Short Interest: The volume of short selling
High volume Þ investors should be bearish.
Low volume Þ investors should be bullish. or
High volume Þ investors should be bullish.
Low volume Þ investors should be bearish.
Credit Balances in Brokerage Accounts
High balance Þ bullish
Short interest -- The total number of shares currently sold short in the market.
Can take alternate interpretations.
An investor who is bullish because the volume of short selling is high is focusing on the fact that short sells must eventually be covered.
An investor who is bearish because the volume of short selling is high is focusing on the fact that short-sellers tend to be the larger and more sophisticated investors.
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

28. Market Structure Indicators
Moving Averages
Average price over some historical period (5 weeks or 200 days)
When current price crosses the average a trading signal occurs
Bullish signal when the current price rises above the moving average
Bearish sign when the current price falls below the moving average
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

29. Technical Indicators: Market Structure
Moving Average: Average over a given interval,
continuously updated.
Price
Price
And
M.A.
Bullish Signal
Bearish Signal
When the market price breaks thorugh the moving average line from below, it is taken as a bullish signal .
When prices fall below the moving average, it is considered time to sell.
MA piercing price from below: bullish signal (shift from falling to raising)
Price piercing MA from above: bearish signal (shift from raising to falling)
Two popular moving averages are the 200-day and the 53 -week moving averages.
Moving Average
Time
Averaging interval
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

30. Figure 19-10 Moving Average for Microsoft
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

31. Figure 19-11 Moving Averages
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

32. Technical Indicators: Market Structure
Breadth: The spread between the number of advancing issues and the number of declining issues.
Advances > declines Þ bullish
Advances < declines Þ bearish
Relative Strength: or
Persistent Rising ratio Þ bullish.
Persistent Falling ratio Þ bearish.
Breadth -- The extent to which movements in broad market indexes are reflected widely in movements of individual stock prices.
To see how widespread is the advance or decline. I.e. to see whether the advance or decline is dominated by only one or few stocks or is more pervasive.
Some analysts use cumulative breadth data each day (see Table 17.1, page 488).
Relative strength -- Recent performance of a given stock or industry compared to that of a broader market index.
Computed by calculating the ratio of the price of the security to a price index for the industry. A rising ratio implies the stock has been outperforming the rest of the industry. If relative strength is assumed to persist over time, this would be a signal to buy the stock.
The relative strength of an industry relative to the whole market can be computed by tracking the ratio of the industry price index to the market price index.
Relative strength is used a lot in mutual fund industry.
Jagadeesh and Titman (1993) show some evidence of support for relative strength strategy. They built momentum portfolios (winner - losers) based on a six-month base performance and noticed that over the next 24 months the portfolio was earning abnormal returns.
“Momentum”
Strategies
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

33. Chapter 12: Behavioral Finance and Technical Analysis
Figure Cumulative Difference in Returns of Previously Best and Worst Ranking Stocks in Subsequent Months
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

34. Chapter 12: Behavioral Finance and Technical Analysis
Value Line System
Widely followed with some evidence of superior performance
Value Line System is predominately a technical system
Earnings momentum
Relative stock prices
Ratios of moving averages
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

35. Chapter 12: Behavioral Finance and Technical Analysis
Figure Record of Value Line Ranking for Timeliness (without adjustment for change in rankings)
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

36. Chapter 12: Behavioral Finance and Technical Analysis
Value Line System
Paper vs actual performance indicates that the system is difficult to implement
Value Line Fund has not shown superior performance
High turnover costs are associated with the strategy
Evidence shows prices react quickly to reported ranking changes
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

37. Technical Analysis and Market Efficiency
Reaction time and length of trends
EMH Þ new information is quickly reflected in prices.
Technical analysis Þ long-lived trends play out slowly and predictably.
A useful technical rule would be invalidated once the mass of traders attempt to exploit it (self-destructing Patterns)
Can Technical Analysis work in Efficient Markets?
Technical analysis is based on ideas totally at odds with the foundations of the efficient markets hypothesis. The EMH postulates that investors will act on new information so quickly that prices will nearly always reflect all publicly available information. Technical analysis posits the existence of long-lived trends that play out slowly and predictably.
Once a useful technical rule (or price pattern) is discovered, it ought to be invalidated once the mass of traders attempt to exploit it. In this sense price patterns ought to be self-destructing.
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

38. A New View of Technical Analysis
EMH: Public information is available to all;
Price reflect all available information
Study by Brown and Jennings (RFS, 1989):
Many investors have private information
Sequence of past price can be useful in the inference of information held by other traders
Prices reveal as well as reflect information
This is a new theory, Brown and Jennings (RFS, 1989) which tries to reconcile technical analysis with the usual assumptions of rational traders participating in efficient markets.
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang

39. Chapter 12: Behavioral Finance and Technical Analysis
Summary
Principles of behavioral finance, individual behavior, behavioral explanations
Technical analysis is the search for recurring patterns in stock prices; Technical analysis assumes prices adjust slowly
Charting: The Dow Theory
Point and Figure Charts
Elliott Wave Theory
Technical Indicators: Sentiment Indicators
Flow of Funds
Market Structure
New theories of information dissemination
Chapter 12: Behavioral Finance and Technical Analysis
Fin 2802, Spring 10 - Tang