Chapter 9
Technical Analysis, Market Efficiency,
and Behavioral Finance
Market Price Behavior
 Learning Goals
1.
Discuss the purpose of technical analysis and why
market performance is important to stock valuation.
2.
Describe approaches to technical analysis, such as
the Dow Theory, moving averages, charting and
indicators of the technical condition of the market.
3.
Compute and use technical trading rules.
4.
Explain the idea of random walks and efficient
markets and note the challenges these theories hold
for the stock valuation process.
2
Market Price Behavior

Learning Goals
5.
Describe the weak, semi-strong, and strong versions
of the efficient market hypothesis and explain what
market anomalies are.
6.
Demonstrate a basic understanding of how
psychological factors can affect investors’ decisions,
and how behavioral finance presents a challenge to
the concept of market efficiency.
3
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
4
Technical Analysis
 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
5
Big Picture Technical Indicators
 The Dow Theory

Market’s performance is based upon longterm price trend (primary trend) in overall
market

Used to signal end of both bull and
bear markets

An after-the-fact measure with no
predictive power
6
Big Picture:
Technical Indicators
 Trading Action

Looks at minor trading characteristics in market over
long periods of time

Assumes the market moves in cycles and these
cycles repeat themselves

Trading rules are formed from patterns:
 January indicator
 Presidential election indicator
 Super Bowl indicator
7
Big Picture
Technical Indicators
 Confidence Index

Looks at ratio between yields on high-grade
corporate bonds compared to low-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
8
Market Technical Indicators
 Market Volume

Pure supply and demand analysis for
common stocks

Strong market when volume goes up

Weak market when volume goes down
9
Market Technical Indicators
 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
10
Market Technical Indicators
 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
11
Market Technical Indicators
 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
12
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
13
Trading Rules and Measures
 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
14
Trading Rules and Measures
 The Trading Index (TRIN)

Combines advance-decline line with trading volume

Used as signal to buy or sell stocks
Number of up stocks
Volume in up stocks
TRIN 

Number of down stocks Volume in down stocks

Bull market when TRIN values are lower

Bear market when TRIN values are higher
15
Trading Rules and Measures
 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
MFCR  Mutual fund cash position  Total assets under management

Bull market when MFCR values are higher

Bear market when MFCR values are lower
16
Trading Rules and Measures
 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
17
Using Technical Analysis
 Charting

Shows visual summary of stock activity over time

Easy to use and to understand

Use to spot developing trends

Major types
 Bar Charts
 Point-and-Figure Charts
 Chart Formations
18
Using Technical Analysis
 Bar Charts

Shows changes in stock price over period
of time

Often used to compare current stock price with
moving average

When current price goes above or below a
moving average, indicates significant
price change
19
A Bar Chart
20
Using Technical Analysis
 Point-and-Figure Charts

Only shows significant changes in stock
price patterns

Up patterns are shown as an “X” and down
patterns are shown as an “O”
21
A Point-and-Figure Chart
22
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”
23
Some Popular Chart Formations
24
Using Technical Analysis
 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
25
A 100-Day Moving Average Line
26
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 could be an indication that markets are
highly efficient and respond quickly to changes
in the current situation
27
Random Walks
and Efficient Markets
 Efficient Market: a market in which securities
reflect all possible information quickly and
accurately
 Efficient Market Hypothesis: markets have
a large number of knowledgeable investors
who react quickly to new information, causing
securities prices to adjust quickly and
accurately
28
Random Walks and Efficient Markets
 To have an efficient market, you must have:

Many knowledgeable investors active in analyzing
and trading stocks

Information is widely available to all investors and is
free and or easy to obtain

Events, such as labor strikes or accidents, tend to
happen randomly

Investors react quickly and accurately to new
information, causing prices to adjust
29
Levels of Efficient Markets
 Weak Form
 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
 Abnormally large profits cannot be consistently earned
using public information

Any price anomalies are quickly found out and the
stock market adjusts
30
Levels of Efficient Markets
 Strong Form

There is no information, public or private, that
allows investors to consistently earn
abnormally high returns
31
Market Anomalies
 Calendar Effects
 Stocks returns may be closely tied to the time of year
or time of week
 Examples: January effect (small stock prices go up
during Jan), weekend effect (Monday’s Open is Lower
than Friday Close)
 Small-Firm Effect
 Size of a firm impacts stock returns
 Small firms may offer higher returns than larger firms,
even after adjusting for risk
32
Market Anomalies
 Earnings Announcements
 Stock price adjustments may continue after earnings
adjustments have been announced (Lots of adjustment
prior to announcement)
 Unusually good quarterly earnings reports may signal
buying opportunity
 P/E Effect
 Uses P/E ratio to value stocks
 Low P/E stocks may outperform high P/E stocks, even
after adjusting for risk
33
Technical vs. Fundamental:
So Who is Right?
 There is growing consensus that markets
may not be perfectly efficient, but they
may be at least reasonably efficient
 Individual investor must determine
which approach has merits for their
investing decisions
34
Investor Behavior and Security Prices
 Overconfidence
 Investors tend to be overconfident in their judgment,
leading them to underestimate risks
 Biased Self-Attribution
 Investors tend to take credit for successes and
blame others for failures

Investors will follow information that supports their
beliefs and disregard conflicting information
35
Investor Behavior and Security Prices
 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
36
Investor Behavior and Security Prices
 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
37
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
38
Behavioral Finance at Work in the Markets
 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
39
Behavioral Finance at Work in the Markets
 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
40
Using Behavioral Finance to Improve
Investment Results
 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
41
Review
 Goals
1.
Discussed the purpose of technical analysis and why
market performance is important to stock valuation.
2.
Described approaches to technical analysis.
3.
Computed and used technical trading rules.
4.
Explained the idea of random walks and efficient
markets.
42
Review
 Goals
5.
Described the weak, semi-strong, and strong versions
of the efficient market hypothesis and explained what
market anomalies are.
6.
Showed a basic understanding of how psychological
factors could affect investors’ decisions, and how
behavioral finance presents a challenge to the concept
of market efficiency.
43
The End!
44
Chapter 9
Additional Chapter Art
Figure 9.2 Some Market Statistics
46
Table 9.1 Using Behavioral Finance to
Improve Investment Results
47