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11
Cognitive Bias and their Implications on the
Financial Market
Márcia Longen Zindel, Thilo Zindel, Marcelo Grangeiro Quirino
Abstract— Behavioral Finance is a science that encompasses the
knowledge of finance, economics and cognitive psychology in
order to understand the investment decision making process. The
main objective of this paper is to demonstrate that the emergence
of behavioral finance contributes to a better understanding about
the decision making process. Behavioral finance presents
evidence that this process can be triggered by cognitive illusions,
heuristics and cognitive
biases,
resulting
in
misleading investment decision-making, which is not based on
rationality. In general, the goal of learning about the cognitive l
biases and the decision-making process is being able to
recognize situations in which these particular errors can manifest
themselves. This way, it can help investors to avoid mistakes in
the process of asset allocation and, consequently, improve future
performance. It provides a better theoretical foundation of the
investor´s behavior, one can better understand the dynamics of
financial markets and avoid actions of euphoria and panic
that can produce serious economic consequences, as evidenced
by recurring financial crises in history.
Index Term— Behavioral Finance, Cognitive Illusions,
Heuristics, Cognitive Biases, Financial Market.
I. INTRODUCTION
The environment of financial decision making is frequently
characterized by its complexity and uncertainty. This context
makes investors prioritize their intuition over rationality
postulated by modern finance theories. These theories are
based on assumptions that the investor is rational, risk-averse
and uses the utility curve to maximize his well-being
Markowitz (1952) [1], Fama (1970) [2], Sharpe (1963) [3].
Traditional and modern finance are concerned about finding
rational solutions for decision problems caused by investor´s
behavior through the development of assumptions and tools
Baker and Nofsinger (2002) [4]. Behavioral finance, in turn,
refers to a new science that encompasses finance concepts and
cognitive psychology, with the primary objective to
understand and predict systematic financial market
implications of the psychological process of decision making
Olsen (1998) [5]. Behavioral finance is what Thaler (1998)
[6], calls an open-minded-finance, because it studies the
possibility that some agents in the economy behave sometimes
Márcia Longen Zindel-Department of Production Engineering
Undergraduate Program, Faculty of Technology, University of Brasilia,
Brasil. (email: marcialz@unb.br)
Thilo Martin Zindel- is with the CEFTRU (Center for Interdisciplinary
Studies in Transport), Faculty of Technology, University of Brasília,
Brasil. (email: thilozeros@yahoo.com)
Marcelo Grangeiro Quirino: is with the CEAM (Multidisciplinary Center
for Advanced Studies), (e-mail: marcelograngeiroquirino@gmail.com).
less than completely based on rationality. According to
MostafaSadeghnia; Abdolhamidhooshmand and Habibniko
(2013) [7] behavioral finance can be summarized as follows:
a. the combination of classical and finance economics and
psychology and decision sciences; b. attempts to explain the
causes of exceptions in the financial literature; c. examines
how investors commit systematic or mental errors in their
judgments.
Considering this, the main objective of this paper is to
demonstrate that the process of investment decision making
can be triggered by cognitive illusions, heuristics and
cognitive biases, resulting in the financial markets, in bad
decision-making, not based on rationality.
II. CRITICISM OF THE TRADITIONAL FINANCE THEORY
One of the first models of decision making formulated at
the beginning of the 19th century was the principle of the
Homo Economicus. According to this principle, decision
makers are: (1) fully informed about all the possible options
for their decisions and all the possible outcomes of their
decision options, (2) infinitely sensitive to subtle differences
between decision options and , (3) fully rational as to their
choice of options Edwards (1954) [8].
Such thinking influenced the assumptions of modern
finance that financial markets are efficient, economic agents,
which are rational and obey the axioms of expected utility
theory to make decisions. According to Fama (1965) [9] an
efficient market is the market where there are large numbers
of rational profit maximizers actively competing, with each
trying to predict future market values of individual securities,
and where important current information is almost freely
available to all participants. Rationality in this context means
that investors use all available information in a logical and
systematic manner to make optimal choices, given the
alternatives available and the objectives to be achieved.
According to Shiller (2003) [10], the Efficient Market
Hypothesis (EMH) as a theoretical framework dominated
academic circles during the '70s, encouraging the publication
of several papers on asset pricing models based on rational
expectations. Among them, An Intertemporal Capital Asset
Pricing Model (1973) [11], by Robert Merton, Asset Prices in
an Exchange Economy (1978) [12], by Robert Lucas, The
Theory Consumption Betas (1979) [13], by Douglas Breeden
and the book A Random Walk Down Wall Street (1973) [14],
by Burton Malkiel. Efficient Market Hypothesis advocates the
efficiency of the financial market in terms of the
overwhelming information, news, or communication involved.
According to Fama (1970) [2], efficient markets are markets
where ‗there are large numbers of rational profit maximizers
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actively competing, with each trying to predict future market
values of individual securities, and where important current
information is almost freely available to all participants‘.
The 1980s were dedicated to an important academic debate
about the consistency of the models of efficient markets,
mainly on the excess volatility.
The assumption about the efficiency of markets has a long
history in research on finance. However, according to Shiller
(2003) [15], from the beginning there has always been a
tension on the hypothesis, a feeling that there was something
wrong with it. One of the main criticisms of the traditional
paradigm which views decision-making as a fully rational
process of finding an optimal choice given the information
available was stated by Herbert Simon (1955) [15], in his
article A Behavioral Model of Rational Choice. In the article
Simon (1955) [15], states: ´Our rationality is bounded, and our
acting is constrained´. According to Simon (1955) [15], the
dream of rationality as embodied in the Homo economicus of
economics and psychology required a decision maker to be a
supremely skilful actor, whose behaviour could reveal
something of the requirements the environment placed on him
but nothing about his own cognitive make-up..
Simon (1955) [15], proposed that human rationality is
limited by both internal (mental) and external restrictions
(environment) and that these limits rather than being seen as
separate must fit together like the blades of scissors.
According to him, tthese two blades – the two sources of
bounds on our rationality – must fit together closely for
rationality to cut. While the external bounds may be more or
less immutable from the actors standpoint, the internal bounds
comprising the capacities of the cognitive system can be
shaped, for instance by evolution or development, to take
advantage of the structure of the external environment.
Thus, according to Simon (1955), the mind can take
advantage of this connection to make good decisions for the
use of mental mechanisms whose internal structures using the
structures of external information available in the
environment. From this perspective, according to him, "We
can see the bounded rationality with a positive outcome of the
two types of bounds fitting together‖. Simon points out: The
human behavior is intendedly rational, but only limitedly so.
(Simon, 1955, p. 24).
Subsequently, many studies have been conducted
questioning the traditional paradigm of unlimited rationality
and demonstrating abnormalities in financial markets. Among
the most cited are: the study of Paul Slovic (1972) [16],
called On the Individual Perception of Risk; Amos Tversky
and Daniel Kahneman in (1974) [17], On Heuristic Rules
(heuristics driven bias) and Mental Structures (decision
frames) in (1979) [18], On the Impossibility of Informational
Efficient Markets by Sanford Grossman and Joseph Stiglitz
(1985) [19], Judgment under uncertainty: heuristics and
biases by Tversky and Kahneman (1974) [20], and Does the
Stock Market overreact? by Werner De Bondt and Richard
Thaler (1985) [21]. The discovery of these studies and other
abnormalities in the financial market led to the publication of
a special issue of the Journal of Financial Economics in June
1978.
In the mid-1985, there was sufficient evidence on the
validity of the hypothesis on market efficiency. The various
12
studies cited confirmed that the main assumptions of rational
behavior were not entirely correct. Furthermore, it would be
necessary to understand other models of human behavior to
grasp the process of decision making of investors, as it was
being studied in the social sciences Shiller (2003) [22].
III. THE EMERGENCE OF BEHAVIORAL FINANCE
According to Baker (2010) [23], Behavioral Finance emerged
in 1980s as a response to emerged failures of the core
economic models that explain anomalies in financial markets.
This approach is based on the concept of explaining behavior
through biases of belief information and non-standard
preferences to make an argument for irrational behavior
among agents that can explain persistent mispricing of assets
and other anomalies. Shefrin (2002) [24], affirm that
Behavioral finance flourished when the advances made in
psychology called the attention of economists. Among the
major studies, those by Paul Slovic (1969) [25], stand out:
Analyzing the Expert Judge: A Descriptive Study of a
Stockbroker's Decision Processes on brokers, published in the
Journal of Applied Psychology in 1969; plus the
Psychological Study of Human Judgment: Implications for
Investment Decision Making, published in The Journal of
Finance in 1972.
However, it was the articles of Amos Tversky and Daniel
Kahneman which most impressed researchers in the area of
finance. The first Judgment under Uncertainty: Heuristics and
Biases, published in the Science Journal in (1974) [17], and
Prospect Theory: An Analysis of Decision under Risk,
published
in
Econometrica
in
(1979)
[26].
In the article Judgment under Uncertainty: Heuristics and
biases (1974) [17], Kahneman and Tversky describe three
heuristics used to access probabilities and predict values. In
the article Prospect Theory: An Analysis of Decision under
Risk, Tversky and Kahneman (1979) [26], presented a critique
of expected utility theory as a descriptive model of decision
making in risky situations and developed an alternative model
called Prospect Theory.
Later on in 1985, two other articles were published, which
became essential for the emergence of behavioral finance. The
first by Werner De Bondt and Richard Thaler (1985) [21],
titled Does the Stock Market overreact? In this article the
authors apply the heuristic of representativeness by Tversky
and Kahneman (1974) [17], in market pricing, discovering
that investors exaggerate both to good and bad news.
However, they argue that the hype leads investors who lost in
the past to underestimate prices and past winners to
overestimate them.
In the article by Hersh Shefrin and Meir Statman (1985).
[28], called The Disposition to Sell Winners too Early and
Ride Losers too Long: Theory and Evidence, the authors
apply Kahneman and Tversky´s notion of framing to holding
losses, calling the phenomenon disposition effect. They argued
that investors are predisposed to hold losing stocks for too
long and sell winning stocks too early.
After 1987, some scholars in Finance and Psychology such
as: De Bondt, Thaler, Tversky, Kahneman, Shefrin, Statman,
Shiller, among others, began to review the assumptions
advocated by traditional finance and study phenomena related
to volatility, abnormalities, exaggeration, loss aversion,
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cognitive biases and heuristics, thereby strengthening the
emergence of the field of behavioral finance.
According to Macedo (2003, p.59) [31],
"Behavioral
finance mixed concepts of economics, finance and cognitive
psychology in an attempt to build a more detailed model of
human behavior in financial markets. Thaler (1998) [32],
defines behavioral finance as the study of how humans
interpret and act on the information to make investment
decisions.
For Fuller (2000) [33], Behavioral Finance is a relatively
new field in economics that is evidenced among professional
investors and can be characterized as an integration of
classical economics and finance with the psychology and
science of decision making, an attempt to explain what causes
some abnormalities that are observed in finance literature.
In brief, Behavioral Finance is a new understanding of the
financial markets that emerged in part as a response to the
difficulties encountered by traditional paradigms. It requires
that some financial phenomena are better understood using
models in which agents are not fully rational.
The studies conducted by Behavioral Finance have focused on
understanding the cognitive illusions and their implications on
the behavior of decision makers. As such, cognitive illusions
can influence the financial market, as it will be shown below.
3.2 Heuristics
According to studies by Amos Tversky and Daniel
Kahnemann (1974) [27], heuristics are mental shortcuts which
lighten the cognitive load to make decisions, but can lead to
biases in the process of decision making. The heuristics
according to them are the means by which agents find
excellent solutions, taking into account the costs of making
fully rational decisions, since the presence of limitations on
the exercise of full and unlimited rationality is plain human
nature. The cognitive biases are systematic judgment errors, or
rather, are mental errors caused by the simplification of
information processing strategy, which often causes a
distortion in the way individuals perceive reality. ―However,
the use of heuristic rules can be based on incorrect
assumptions leading agents to commit systematic errors in
decision making, People rely on a limited number of heuristic
principles which reduce the complex tasks of assessing
probabilities and predicting values to simpler judgmental
operations. In general, these heuristics are quite useful, but
sometimes they lead to severe and systematic errors‖.
(Kahneman and Tversky, 1974, p. 1124) [27].
These authors describe three heuristics that are used in the
process of decision making under uncertainty: (a) the
representativeness heuristic, which is usually employed when
individuals are asked to judge the likelihood of an object or
event A, belonging to a class or process B, (b) the availability
heuristic for examples or scenarios, which is often used when
people are asked to calculate the frequency of a class or the
plausibility of a particular development, and (c) adjustment or
anchoring, which is usually applied to numerical prediction
when a relevant value is available (Kahneman & Tversky,
13
1974, p. 1131) [27]. The following heuristics are presented in
detail.
3.2.1. Representativeness Heuristic
Kahneman and Tversky (1974) [27],
suggest that the
representativeness heuristic is used when subjects judge the
probability of an uncertain event in accordance with: (a) how
similar or representative of the population to which it
originates it is, and (b) the degree to which it reflects the
salient features of the process by which it is generated (such as
random).
According to these authors the reasons why individuals use
the representativeness heuristic is when they fail to understand
the concept of basic estimates, the prevalence of an event or a
feature within its population of events or characteristics.
Another reason is the insensitivity to the sample size, because
it is believed erroneously that small samples of events, people,
etc. are similar in all respects to the entire population from
which the sample is extracted. People tend to underestimate
the likelihood that the characteristics of a small sample of a
population inadequately represent those of the entire
population. ―We also tend to use the representativeness
heuristic when we are very aware of anecdotal evidence based
on a very small sample of the population‖ (Kahneman and
Tversky, 1974, p. 1124) [27].
They claim: ―This approach to the judgment of probability
leads to serious errors, because similarity, or
representativeness, is not influenced by several factors that
should affect judgments of probability .... If people evaluate
probability by representativeness, therefore, prior probabilities
will be neglected‖ (Kahneman and Tversky, 1974, p. 1124)
[27].
3.2.2 Availability Heuristic
According to Kahneman and Tversky (1974) [27],
individuals use the availability heuristic when making
judgments on the basis of how easily they can use the memory
of what they perceive as relevant circumstances of a
phenomenon. The availability heuristic occurs because people
have a strong tendency to focus their attention on a particular
fact rather than the entire situation, only because this
particular fact is more present in their minds Brabazon, (2000)
[34], Tversky and Kahneman, (1974) [27], "Availability is a
useful clue for assessing frequency or probability, because of
instances of large classes (Kahneman and Tversky, 1974, p.
1127) [27]. However, the use of the availability heuristic can
lead to the occurrence of some cognitive biases, as shown
below:
- Biases due to the recoverability of examples: judging the size
of a trial class by the ease of recovery due to the occurrence of
a
greater
number
of
examples.
- Imagination biases - judging the possibility of occurrence of
events that are not stored in the memory by generating
responses based on certain rules.
According to Tversky and Kahneman, (1974) [27], another
cognitive bias that can occur as a result of the availability
heuristic is illusory correlation. Because it causes people to
seek correlations between information that they are more
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familiar with or which is more present in their minds. This
may contribute to exaggerated highs or lows of the stock price
or
in
the
market
Brabazon
(2000)
[35].
The illusory correlation is the tendency to view events or
specific attributes and specific categories as belonging
together, because we have a pre-disposition to do so. For
events, we can see spurious relations of cause and effect. In
the case of attributes, personal losses may be used to form and
use stereotypes Fuller (2000) [36].
3.2.3 Anchoring and Adjustment
Anchoring and adjustment are tools, used by the brain to
solve complex problems for the initial selection of a
quantifiable estimate that will be slowly adjusted to the correct
answers as new information is being received. However,
according to Kahneman and Tversky (1974, p. 1128) [17],
"Such
adjustments
are
typically
insufficient".
The tendency to anchor (anchoring and adjustment) can cause
investors to use a certain mental anchor mark to buy or sell a
stock. This anchor could be a price, achieved at a determined
time before a sale or purchase or a forecast of an analyst. Once
the anchor is formed, investors tend to give little value to new
information, even if it changes the profile of the company.
According Kahneman and Tversky (1974) [17], the use of
the availability and adjustment heuristic leads to the
occurrence
of
the
following
cognitive
biases:
- insufficient adjustment bias - the bias is caused by
insufficient adjustments to the final anchor in relation to what
was
established
by
the
initial
anchor.
- bias in the evaluation of conjunctive and disjunctive eventsthis bias is displayed by individuals when they tend to
overestimate the probability of conjunctive events and
underestimate the probability of disjunctive events.
- anchoring bias in assessment of subjective probability
distributions -this bias is due to subjective assessments of
quantitative values.
3.3 Cognitive illusions caused by mental structures
As previously mentioned, the process of decision making is
also influenced by mental structures, i.e., by how the choices
are presented. The following section presents some cognitive
illusions caused by mental structures:
3.3.1 Frame Dependence
According to Shefrin (2002, p.21.) [29], "Frame is the form
used to describe a decision problem". Framing is a heuristic in
which people tend to draw conclusions based on the structure
in which a situation was presented. According to Ritter (2003,
p. 33) [28], it is the notion that the way of how a concept is
presented matters". The concept of frame dependence means
that the way people behave depends on how their decision
problems were structured.
3.3.2 Prospect Theory
The prospect theory by Daniel Kahnemann and Amos Tversky
(1979) [26], promotes evidence of frame dependence. The
14
Prospect Theory makes a critique of expected utility theory as
a descriptive model of decision making under risk, and
develops an alternative model. Thus, for Kahneman and
Tversky (1979) [26], prospect theory is an alternative theory
of choice, in which the value is assigned to gains and losses
rather than final goods, in which probabilities are replaced by
decision weights. The value function of prospect theory is
normally concave for gains and commonly convex for losses
and is generally steeper for losses than for gains. The weights
in the decisions are generally lower than the corresponding
probabilities, except in intervals of low probabilities, as shown
in Figure 2. Therefore, the great weight given to low
probabilities may contribute to the attractiveness in the fields
of insurance and gambling Kahneman and Tversky (1979, p.
263) [26].
Fig. 1. Hypothetical Value Function of Prospect Theory. [26]
Source:
In summary, the prospect theory demonstrates that
individuals tend to choose the options that demonstrate risk
aversion when faced with a choice that involves potential
gains. Specifically, we tend to choose options that offer a
small but certain gain, rather than a larger but uncertain gain,
unless the gain is much more uncertain or only modestly lower
than the right one. On the other hand, one tends to choose the
options that demonstrate risk seeking when faced with choices
involving potential losses, meaning one tends to select options
that offer a great but uncertain los instead of a certain but
minor loss, unless the uncertain loss is tremendously larger or
only slightly smaller than the right one.
According to Plous (1993) [29], contrary to the expected
utility theory, prospect theory believes that the choice
preferences in a decision making process will depend on how
a problem is structured. If the reference point is defined by an
outcome perceived as a gain, then the resulting function value
is concave and decision makers tend to be risk averse. On the
other hand, if the reference point is defined by a result
perceived as a loss, function value is convex and decisionmakers are predisposed to risk.
3.3.3 Disposition effect
The disposition effect is based on studies conducted by the
prospect theory by Shefrin and Statman (1985) [30]. It is
considered a psychological effect related to a predisposition of
individuals to determine the initial value (purchase price) of
investments from its point of reference, in order to assess
whether the sale of the investments will generate gains or
losses. However, the disposition effect also posits that
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investors tend to hold stock portfolios with low performances
for a long time and sell very rapidly the ones with positive
performances Shefrin and Statman (1985) [30].
3.3.4 Mental accounting
Kivetz (1999) [31], believes that mental accounting refers to
the set of cognitive operations used by individuals to organize,
evaluate and monitor financial activities. According to Ritter
(2003) [28], people sometimes separate decisions which in
principle should be combined. For example, many people have
a household budget for food and another one for
entertainment. At home, for example, with the household
budget, one does not eat lobster or shrimp because it would be
more expensive than fish. However, in a restaurant, one orders
lobster or shrimp, even if it turns out to be more expensive
than a simple fish dish. If one does not assess the problem
separately, one could realize that it would be cheaper to eat
shrimp or lobster at home than in a restaurant.
Kivetz (1999. p. 249) [31], states that: "evidence suggests
that the principles of mental accounting often regulate the
purchase and consumption of luxuries and that reasons may
play an important part in this process. In particular, buying
and consuming luxury goods tends to call for reasons and
justification and can evoke intra-personal conflict that might
be resolved with the aid of mental accounting. Moreover,
reasons can serve as important building blocks in the
formation and grouping of mental accounts".
3.3.5 Regret bias
Regret is the emotion, the feeling experienced by people for
not taking the right decision. According to Shefrin (2002)
[24], it is more than the pain of a loss; the pain is associated
with feeling, responsible for the loss. Regret can easily affect
the decisions that people make. According to him, someone
who feels intense regret, does not have a strong preference for
variety, always thinks ahead, and may follow the same route
to work every day in order to minimize a possible future
regret.
In the January 1998 issue of Money magazine, Harry
Markowitz was asked what motivated his personal choice on
asset allocation. He said that it was not exactly the quest for a
risk/return trade-off, his intention was to minimize future
regret. According to Shiller (1997) [32], regret theory can
apparently help explain the fact that investors often give in to
the urge to sell stocks that have lost value and accelerate the
sale of shares that have gained value.
For Shefrin and Statman (1985) [30], the regret bias can be
interpreted as the reason why investors avoid selling stocks
that have dropped in price, in order to not finalize the mistake
they committed and to not feel the pain of regret. They sell the
stocks that have risen so they do not feel regret for failing to
do
so,
before
the
stocks
drop
afterwards.
15
information on a company. As a consequence, prices will
fully reflect the new information only gradually. For Montier
(2002) [33], this is a tendency to cling stubbornly to a vision
or foresight. Once the position has been established, most
people find it very difficult to change this view. Change
occurs only in a very slow manner, this trend creates the effect
of underreaction to events. According to Shiller (1992) [34],
conservatism is a combination of overconfidence with
anchoring and anchoring-adjustment leading investors and
analysts to adapt slowly to the arrival of new information.
3.3.7 Overoptimism
Optimism according to Montier (2002) [33], is the mood or
attitude associated with a positive outlook towards the future.
According to Lovallo and Kahneman (2003) [35], optimism
generates more enthusiasm than realism, making a proper
assessment of reality on the part of investors more difficult.
Such bias can cause investors to be less resilient when faced
with difficult situations and challenging objectives.
Montier (2002) [33], believes that excessive optimism
stems from a number of cognitive biases such as illusion of
control - when individuals feel they have more control of the
situation than they really have. Self-attribution bias occurs
when the positive results of certain situations are assigned to
their own skills and poor results are attributed to bad luck.
Margaret Matlin and David Stang (1978) [36], conducted
hundreds of studies showing that human beings are extremely
optimistic. They even discovered that some aspects of human
cognition such as language, memory and thought are
selectively positive. For example, people use more positive
words than negative ones when they write or speak. In
memories, they recall positive experiences faster than negative
ones, plus most people assess themselves positively in a
particular way, more positively than others do.
3.3.8 Sunk Cost Fallacy
A cost is sunk when it cannot be recovered. According to
Friedman et. al. (2007) [37], once a cost is sunk, it has no
effect on the (balances/paybacks) incremental of future
decisions and consequently plays no role in rational choice.
The sunk cost fallacy is considered a maladaptive behavior
that is manifested by the strong tendency to continue a project
once a money, effort, or time investment has been made. The
effect is considered this way, because only marginal costs and
benefits, not past costs, should be taken into account in the
process of rational decision. This tendency can lead to suboptimal economic decisions because such decisions should be
based solely on future costs and benefits and not past costs
that have already taken place. The sunk cost fallacy has been
demonstrated in various professional fields such as sports
Staw and Hoang (1995) [38], and capital markets McCarthy,
Schoorman and Cooper (1993) [39].
3.3.6 Conservatism bias
IV. CONCLUSION
The conservatism bias means that investors are too slow,
too conservative to update their beliefs in response to recent
evidence. This means that they can initially underreact to new
In general, the goal of learning about cognitive judgment
biases and the process of decision making is being able to
recognize situations in which these particular errors can
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manifest themselves. This can help the investor to avoid
mistakes in the process of asset allocation and, as a
consequence, improve future performance.
The knowledge about cognitive illusions that can affect the
decision process allows investors to avoid mistakes in the
financial decisions. Thus, knowing and letting the investors
know about cognitive illusions to which they are subject is
crucial for the improvement of investment allocation. It is
believed that only through the systematization of information
on investor behavior and the process of decision making, it
will be possible to construct appropriate tools to support
decision-making, which can contribute to economic efficiency
in the markets.
Insofar as greater theoretical support to empirical studies on
investor behavior is being proportioned, one can better
understand the dynamics of financial markets and prevent the
movements of euphoria and panic, which can produce serious
economic consequences, as demonstrated by recurrent
financial crises in market history. A better understanding of
this topic is fundamental for investors to make decisions more
efficient- and effectively.
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First A. Author
Marcia Longen Zindel has Psychology Degree from Federal University
of Santa
Catarina
(UFSC), Specialization
in Human
Resource
Management (UFSC), Master Course in Production Engineering (UFSC). PhD
in Industrial Engineering (UFSC). Took a Doctoral stage in the year of 2006
at the Institute of Economics and Management (ISEG), in the Technical
University of Lisbon in Lisbon, Portugal. Worked in companies in
various sectors of activity: Tourism, public safety, health, communication
and technology in people management. Worked as a researcher at the Center
for Personal and Behavioral Finance (NEFIP) at UFSC. Taught at the
University of Vale do Itajai (2001-2009). Worked also as a consultant for
the Institute for Financial Education Premium. Currently is a Professor
of Production Engineering Program at the University of Brasilia (UnB). And
researcher of the Center for Public Policy Research ( NP3 ) belonging to the
Multidisciplinary Center for Advanced Studies ( CEAM ) / UnB.
142603-7676-IJET-IJENS © June 2014 IJENS
IJENS
International Journal of Engineering & Technology IJET-IJENS Vol:14 No:03
17
Thilo Zindel Graduated in International Management - University of
Lethbridge, Canada, (2004).Works as a researcher at the Interdisciplinary
Centre in Transport Studies (CEFTRU)/ UnB in the financial a'rea. And is
taking a master's degree in the Post-Graduation Program in Transports at
UnB.
Marcelo Grangeiro Quirino Completed undergraduate degree in
Mathematics from the State University of Paraíba (1979 ) , Specialization in
Higher Education - Structure and Function by UnB (1997 ) , MA in Pure
Mathematics from the Federal University of Santa Catarina (1985 ) and Ph.D.
in Industrial Engineering from University Federal de Santa Catarina (2002 ) .
He is currently on Science and Technology Analyst Senior III , the Board of
the Foundation Permanent CAPES / MEC . He was assistant professor in the
Department of the Faculty of Technology : Production Engineering ,
University of Brasilia - UnB . Has experience in the areas of Mathematics and
Industrial Engineering , with emphasis on Operations Research and Strategic
Management and Process Lines of research in Decision Making ; Performance
Evaluation Systems in Multiple Criteria Decision Support in Governmental
Environment . Correlated with the areas of Administration, Accounting ,
Economics and Political Science . Researcher of the Center for Public Policy
Research ( NP3 ) belonging to the multidisciplinary Center for Advanced
Studies ( CEAM ) / UnB.
142603-7676-IJET-IJENS © June 2014 IJENS
IJENS