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Eurasian Journal of Social Sciences, 3(1), 2015, 13-19
DOI: 10.15604/ejss.2015.03.01.002
EURASIAN JOURNAL OF SOCIAL SCIENCES
http://www.eurasianpublications.com
† I am grateful to participants of the 14th EBES conference for valuable comments and suggestions, but
reserve to myself the responsibility for any errors.
BEHAVIORAL BIASES OF INDIVIDUAL INVESTORS: THE EFFECT OF
ANCHORING†
Salma Zaiane
FSEG Tunis, Tunisia. Email: zaiane_salma@yahoo.com
Abstract
The objective of this paper is to investigate the presence of the anchoring bias in the financial
decision making of individual investors. A survey study is carried out to find out how the studied
bias affects the investment behavior on the Tunisian stock market. The survey is for exploratory
purpose and it is based on multiple factorial correspondence analyses. The results reveal that
Tunisian investors do not suffer from the anchoring bias.
Keywords: Behavioral Finance, Anchoring, Individual Investors, Emergent Market
JEL Classification: G12
1. Introduction
The scandals that have occurred in recent years and the crashes and successive financial
crises that characterize modern economies, including the current financial meltdown from the
subprime, lead us to question the functioning of financial markets. Researchers try to
understand the attitudes of investors, often influenced by mental routines, errors in judgments or
even emotional factors. Obviously, this leads one to doubt the efficiency of financial markets,
that is to say, their ability to control the policies of the firms and to allocate the capital optimally.
Kahneman and Tversky (1974; 1979) propose an alternative study focusing on behavioral
evidence in total opposition to the rationality of investors which follows the theory of financial
markets. Indeed, investors are not fully rational and their demand for risky financial assets is
affected by their beliefs or their feelings, which are clearly not justified by economic
fundamentals. They are thus prey to several biases that affect their logical reasoning, and push
them to commit errors in thinking.
Empirical work and recent experimental research have confirmed that the errors of
judgments made by individuals affect the behavior of security prices on financial markets. In
fact, investors do not necessarily follow objective notions of financial loss or gain calculated
mathematically. A key way, in which investors are victims, is the anchoring bias according to
which people tend to rely on the first piece of information offered (the "anchor") in making
judgments or taking decisions.
In this paper, we seek to better understand the human behavior that governs the
dynamics of financial markets, studied through investor anchoring on the Tunisian stock market.
For that purpose, we use a questionnaire developed and administered to a Tunisian sample of
individual investors. The rest of the paper is organized as follows: Section II presents a review
Salma Zaiane / Eurasian Journal of Social Sciences, 3(1), 2015, 13-19
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of the literature of the anchoring bias, and Section III presents the assumptions of our work.
Empirical validation is described in Section IV and Section V is devoted to present the empirical
results and their interpretation. Finally, Section VI contains the summary and the conclusion.
2. Literature Review
Anchoring describes the common human tendency to rely too heavily, or „anchor‟ on one trait or
piece of information when making decisions. When presented with new information, the
investors tend to be slow to change or the value scale is fixed or anchored by recent
observations. They are expecting the trend of earning is to remain with historical trend, which
may lead to possible under reactions to trend changes.
“In many situations, people make estimates by starting from an initial value that is
adjusted to yield the final answer. The initial value, or starting point, may be suggested by the
formulation of the problem, or it may be the result of a partial computation. In either case,
adjustments are typically insufficient (Slovic and Lichtenstein, 1971). That is, different starting
points yield different estimates, which are biased toward the initial values. We call this
phenomenon anchoring (Tversky and Kahneman, 1974, p. 1128).
According to Esch et al. (2009), anchoring refers to a biased judgment of a stimulus
based on an initial assessment of another stimulus and an insufficient adjustment away from
that initial assessment”. This means that an earlier presented value affects people when they
are to estimate an unknown quantity, which then will be close to the value that was considered
before the estimation. An example of the anchoring effect is how you get influenced by the
asking price when buying a house (Kahneman, 2011). A higher asking price will influence you to
value the house higher than you would have done if the asking price was lower. According to
Kahneman (2011), any number that you are asked to consider as a possible solution to an
estimation problem will induce an anchoring effect.
Numeric judgments under uncertainty are the most observed anchoring effects, since a
lot of studies have been done in this field (Esch et al. 2009). However, the anchoring effect of a
judgment does not have to be a numeric one (Cohen and Reed, 2006), but is a general
phenomenon (Soman and Chattopadhyay, 2007). Hence, every time individuals form an image
about a stimulus while another stimulus is present, this image may be subject to anchoring
effects (Esch et al. 2009).
Anchoring is produced by two different mechanisms, where one occurs in System 1 and
one in System 2. In System 1, anchoring is an automatic manifestation, which occurs by a
priming effect. In System 2, anchoring instead occurs in a conscious activity of adjustment.
However, there is in most cases no corresponding subjective experience in anchoring. This
effect is therefore often perceived by people as unbelievable (Kahneman, 2011).
Forty years of psychological anchoring studies have found the anchoring bias to be
fairly robust against experimental variations (Furnham and Boo, 2011). Contrasting this view,
recent economic field experiments on anchoring in price valuations find only moderate effects
(Simonson and Drolet, 2004; Bergman et al. 2010; Tufano, 2010; Alevy et al. 2011; Fudenberg
et al. 2012; Maniadis et al. 2014). These results support the notion of market conditions
correcting irrational consequences of individual heuristics. Therefore, rationality-increasing
teamwork as a ubiquitous form of decision-making in actual markets might be an additional filter
for biased decisions previously overlooked in experimental studies (Meub and Till, 2014).
3. Empirical Studies
3.1. Objective
The aim of our empirical studies is to test the existence of the anchoring bias on a sample of
individual investors on the Tunisian stock market, to study if they are victims of this bias in
making their decisions. For that, we conducted a questionnaire survey. Indeed, the psychology,
which can be defined as "the science of behavior”, must be taken into account by a method of
investigation which can well describe the characteristics of the investor. The questionnaire
Salma Zaiane / Eurasian Journal of Social Sciences, 3(1), 2015, 13-19
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appears to be a useful tool in determining how individual errors affect aggregate behavior. We
will particularly understand how the decisions of many individual investors are incorporated into
prices on financial markets.
3.2. Data
The subjects are targeted on the individual private stock investors in Tunis1. We addressed our
questionnaire to 150 Tunisian investors2. We used two methods of data collection (face to face
interviews and mail survey). We got a response rate of 83% and a final sample of 125 investors.
The survey was conducted in July 2008. The face-to-face interviews3 allowed us to respond
directly to questions that respondents were asked about the issue itself. It also allowed us to
better control the representativeness of the sample. Furthermore, we avoided expressing any
opinion or any form of approval or disapproval, to avoid influencing the respondent.
3.3. Profile of Respondents
Table 1 reports summary statistics for our sample of investors grouped by gender, age,
education and business position. 73.6% of the subjects who responded to the questionnaire
were men. This is easily understood since the number of men is higher than the number of
women investing in the Tunisian stock market. A greater number of subjects (35.2%) were
aged around 35~49 while 30.4% were aged between 25 and 34 years. 44% of the subjects
have a bachelor degree while 44.8% have a master degree and above. We remark according to
our sample, that the higher the degree of education, the more we invest in the stock market.
Moreover, the proportion of executives is very high. In fact, they represent almost half of our
sample (48%). Finally, most of the respondents belonged to the middle-income class with a
monthly income between 600 and 2000 dinars4.
Table 1. Profile of respondents
Variables
Response (in %)
Gender
Male
73.6
Female
26.4
-
-
-
-
Age
<25
12.8
25-34
30.4
35-49
35.2
50-60
12.8
>60
8.8
Education*
low
11.2
Middle
44.0
High
44.8
-
-
-
Income**
Low
23.3
Middle
58.4
High
18.4
-
-
-
Business
position
Merchant,
Artisan,
Entrepreneur
6.4
Executive,
Higher
intellectual
profession
48.0
Middle
management
20.8
Employee
8.0
Student
9.6
Retired
7.2
Notes: *The education of low: high school or lower; middle: bachelor; high: master and above.
**The income of low: < 600 dinars; middle: [from 600 dinars to 2000 dinars]; high: > 2000 dinars.
1 We note that commercial agents working at the front offices in stock market intermediary houses help as
to contact the investors.
2 Several questionnaires were omitted since too many questions had been left unanswered.
3 Face to face interviews represent 70% of total interviews. We chose to perform our investigation on the
big Tunis (Tunis, Ben Arous, Ariana), because the population of the big Tunis is heterogeneous and
diversified and therefore, it gives us a greater depth of information.
4 100 Tunisian Dinars = 54.15 US Dollars as of 14/12/2014.
Salma Zaiane / Eurasian Journal of Social Sciences, 3(1), 2015, 13-19
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3.4. Methodology
For our study, we used the “Sphinx” software (trial version, V5). This allowed us to design the
questionnaire, to register the responses, and especially to process and analyze the data. We
did not take missing data into consideration. Indeed, the terms "no answers" do not appear in
the results: It could be either a deliberate refusal to answer certain questions or accidental
omissions.
The anchoring bias is studied through the following four questions. For each question,
one response modality is considered symptomatic of the psychological bias. If we accumulate
three typical responses, we confirm the presence of the latter. We create a code for each
question (variable) and each modality. This involves defining a label, that is to say an abstract in
a smaller number of characters. Each theme is associated with a number. For example, the first
question is associated with the code "Loss value1”. The coding variable is given in Table 2.
Table 2. Coding variable
Loss value
When you lose money on a value you :
Loss value1 : never reinvest on it
Loss value2 : Try to regain with it quickly
Loss value3 : look from time to time to see
the evolution of its price without doing
anything
Information after
analysis
If the day after you bought a security you
learn information that challenges your
analysis, you :
Information after analysis1 : abandon
your analysis and, if appropriate, resell the
security
Information after analysis2 : wait till
another information comes consolidate one
or the other of the positions
Information after analysis3 : put in
perspective the scope of the information
First idea
You think in stock exchange the
first idea:
First idea1 : is always good
First idea2 : should never be followed
First idea3: is often good when it comes to
selling and bad when it comes to buying
Comparison
Over the long term, you prefer to buy a
security that will be
undervalued compared to:
Comparison1 : its direct competitor
Comparison2: its sector
Comparison3: the overall market
Table 3 summarizes the anchoring symptoms that will be developed later.
Table 3. Anchoring symptoms
Code
Presence of the representativeness bias
Loss value1
Under-reaction to new information
Information after analysis3
Importance of the first intuition
First idea1
Presence of the confirmation bias (numerical anchoring)
Comparison1
After this coding, the data were entered on the Sphinx software. Finally, we presented
the results of the analysis.
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4. Results
Tables 4, 5, 6 and 7 report the results of the univariate analysis of the various variables of the
anchoring bias. The symptomatic modality of the bias is set in gray.
Table 4. Loss value Table 5. Information after analysis
Loss value
Number
of
citations
%
Information after analysis
Number
of citations
%
Loss value1
14
11.5%
Information after analysis1
31
25.0%
Loss value2
44
36.1%
Information after analysis2
53
42.7%
Loss value3
64
52.5%
Information after analysis3
40
32.3%
Total
122
100%
Total
124
100%
Table 6. First idea Table 7. Comparison
First idea
Number of citations
%
Comparison
Number of citations
%
First idea1
44
37.6%
Comparison1
10
8.1%
First idea2
29
24.8%
Comparison2
46
37.1%
First idea3
44
37.6%
Comparison3
68
54.8%
Total
17
100%
Total
124
100%
We note from Table 4 that only 11.5% of the respondents prefer not to invest in a
security that decreases substantially without any reason. In contrast, the majority of the subjects
(52.5%) preferred to watch the evolution of its price from time to time without doing anything.
This is not consistent with the representativeness bias that stipulates that past events are
typical and representative of the future.
Table 5 shows that 42.7% of the respondents, when they learn information that calls
into question their analysis, expect other information to come consolidating one or the other
position. In contrast, 32.3% of the subjects put the scope of that information into perspective.
This does not confirm the results of Bernard and Abarbanell (1992) and Barberis, Shleifer and
Vishny (1998) that argue that the anchoring is at the origin of the under-reaction of investors to
new information.
We note from Table 6 that 37.6% of the respondents consider that while trading the first
idea is always good. The investor sentiment seems to be influenced by the first intuition
(Bazerman, 2004; Chapman and Johnson, 2002; Epley, 2004). In Fact, They tend to
overestimate the information that are in line with their first idea and to underestimate those that
oppose it. Thus, they will more likely buy the security, when they had a favorable first
impression and vice versa. In contrast, 37.6% of them assume that the first idea is often good
when it comes to selling and bad when it comes to buying. Therefore, buying and selling
decisions are not controlled by objective assessments, with the risks that entail (Mangot, 2004).
Table 7 shows that the majority of respondents (54.8%) prefer to buy undervalued
securities as compared to the overall market over the long term. In contrast, only 8.1% of them
consider the price of the competitor as an anchor. They present the numerical anchoring bias. It
is a declination of numerical confirmation bias. It reflects the tendency to focus on a number and
then use it as a reference when making an estimate (Mangot, 2004). This reasoning can be
misleading. The less we know the market price, the more vulnerable it is to numerical anchor.
Thus, the numbers (PER in this case) can affect the valuation of securities (Thomas and
Morwitz, 2007). Therefore, we can get the values when the PER is lower (higher) than their
comparable to buy in a bull market (bearish). Thus, valuations may deviate considerably from
their historical standards. We conclude from the results of Tables 4, 5, 6 and 7 the absence of
Salma Zaiane / Eurasian Journal of Social Sciences, 3(1), 2015, 13-19
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the anchoring bias. Indeed, none of the symptomatic responses of the anchor bias is checked
on the four variables studied5.
5. Conclusion
Human decision making does not seem to conform to rationality and market efficiency, but
exhibits certain behavioral biases that are clearly counter-productive from the financial
perspective.
In this paper, we tested the presence of the anchoring bias on the Tunisian stock
market. For that, we administered a questionnaire to a group of individual investors, to consider
whether they are victims of this bias in their decision making. The results indicate that individual
investors on the Tunisian stock exchange don‟t suffer from the anchoring bias. In fact, they are
not subject to the representativeness and the confirmation biases. Moreover, they don‟t under-
react to new information.
Besides, another interesting study could be made from the same research framework; it
is to test the presence of other psychological biases such as herding, loss aversion and mental
accounting. Further research should also investigate anchoring in the context of an
experimental approach focusing on individual investment (Matsumoto et al. 2013). Also, further
research could examine the relation between anchoring and overconfidence (Heywood-Smith et
al. 2008).
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