Chapter 4
PERCEPTIONS ABOUT
RISK AND RETURN
Behavioral Corporate Finance
by Hersh Shefrin
McGraw-Hill/Irwin
Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved.
Representativeness
Risk and Return
 In practice, managers appear to rely on
representativeness when forming
judgments about risk and return.
 They are prone to view the stocks of
good companies as representative of
good stocks.
 As a result, they come to judge that risk
and return are negatively related.
1
Unisys and Intel
Comparative Data
April 2000
Beta
Market value of equity ($billions)
Book value of equity ($billions)
Book-to-market equity
Balance sheet retained earnings ($billions)
Prior 6 month return
Prior 1 year return
Prior 3 year return
Past 5 year growth rate of sales
Unisys
1.33
$8.003
$2.088
0.26
($1.62)
-67.6%
92.8%
60.2%
0.8%
Intel
1.04
$441.860
$36.103
0.08
$25.22
215.6%
222.3%
56.2%
21.2%
 Unisys just reported a decline in sales, yearover-year.
 Analysts were predicting that Intel sales would
grow by 10%.
2
Rate Intel and Unisys
 Quality of company
 Financial
soundness
 Long-term
investment value
 Expected return
over next 12 months
 Perceived risk
 Intel is a better
company than
Unisys.




Past 5 year sales
Market cap
Retained earnings
component of book
equity
Similarly Intel does
better on the other
variables.
3
Risk and Return
 Managers who rely on representativeness
judge Intel stock to be a better stock than
Unisys stock.
 Managers who rely on representativeness
view the stocks of financially sound
companies as safe stocks, and the stocks of
companies that are not financially sound as
risky stocks.
 Managers who rely on representativeness
view Intel as a safer stock than Unisys.
4
Perceived Relationship
Between Risk and Return
Expected Return vs Beta
10.0%
9.5%
9.0%
Expected Return
 Traditional finance
teaches that risk and
return are positively
related, that higher
expected returns are
associated with higher
risk.
 Representativeness
induces managers to
view the relationship as
going the other way.
8.5%
8.0%
7.5%
7.0%
0.5
1.0
1.5
2.0
2.5
3.0
beta
Exhibit 4-2
Scatter plot displaying
assessments of investment
professionals.
5
Affect Heuristic Reinforces
Representativeness
 People assign affective labels or tags to
images, objects, and concepts.
 Imagery is important, e.g. adding “dot.com” to
name of firm in second half of 1990s.
 The affect heuristic is a mental shortcut that
people use to search for benefits and avoid
risks.

Benefits are associated with positive affect,
whereas risks are associated with negative affect.
6
Perceived Risk and
Firm Characteristics
 Executives associate low book-to-market equity
and high market capitalization to both good
stocks and good companies.
 Executives view stocks associated with



low betas,
large market capitalization, and
low book-to-market equity
to be less risky than stocks associated with



high betas,
small market capitalization and
high book-to-market equity.
7
Analysts
 Unlike executives, analysts treat the
relationship between beta and expected return
as being positive.
 Holding beta constant, analysts expect smaller
capitalization stocks to earn higher returns than
larger capitalization stocks.
 Analysts expect growth stocks to earn higher
returns than value stocks.
 Analyst target prices are excessively optimistic.
8
Financial Executives and the
Market Premium
 Financial executives appear to believe that at
the level of the market, expected returns and
risk are negatively related.
 The higher the market return has been in the
prior quarter, the higher their forecasts of the
equity premium over the subsequent year.
 The higher the market return has been in the
prior quarter, the lower are their forecasts of
market volatility over the subsequent year.
9
S&P 500
Rolling Dice?
 Is the market hotter if it's recently been hot?
 Is the market colder if it's recently been cold?
 Based on data going back to 1926 when the
S&P 500 index was formulated, the probability
of an up-year is about 2/3.
 The probability is about the same after upyears as after down-years.
 It's almost like rolling dice.
10
Two Fallacies
Professional Investors
Forecasted Change in S&P 500 vs Prior Change in S&P 500
1990 - 2003
Expected Return UBS/Gallup Survey vs Prior Return S&P 500
25%
18%
16%
20%
Forecasted Change in S&P 500
14%
Expected Return
12%
10%
8%
6%
15%
10%
5%
4%
0%
2%
-30%
-20%
-10%
0%
10%
20%
30%
40%
0%
-40%
-30%
-20%
-10%
0%
10%
20%
30%
40%
Prior One-year Return S&P 500
Individual investors
exhibit the hot hand
fallacy.
50%
-5%
Change in S&P 500 Prior Year
Investment
professionals exhibit
gambler's fallacy.
11
Wall Street Analysts and
Executives

For individual stocks, analysts believe in
short-term reversals, not momentum.
Given the evidence for momentum, analysts
appear to exhibit gambler's fallacy.
Executives engaging in legal insider trading
exhibit gambler's fallacy.



This leads them to sell growth stocks and buy or
hold value stocks.
12
Project Discount Rates
 In theory, managers discount project cash
flows at a rate that reflects the systematic risk
of those flows.

If those flows comprise a series of components, all
featuring different levels of risk, then in theory
managers should discount each component
separately, using its own discount rate.
 Survey evidence from FEI indicates that in
practice, most managers use a “one size fits
all” heuristic.
13
Debiasing
 Carefully identify both the base rate
information and the singular information.
 Use statistical forecasting techniques, and
contrast the outcomes with forecasts based on
intuitive judgments.
 Based on the contrast, ascertain whether the
intuitive judgments fail to make appropriate
use of either base rate information or singular
information.
14