ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
by
Paul D. Sonkin
New draft: December 20, 2018
Copyright © 2018 by Paul D. Sonkin
Correspondence concerning this article should be addressed to Paul D. Sonkin.
Contact: psonkin@pitchtheperfectinvestment.com
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
2
Abstract
The holy grail of manager selection is to identify those individuals who will outperform the
market over the long term. Formal academic inquiry in the past has focused on the study of
correlational attributes such as social networks, specialization and pedigree. In contrast,
investigation into cognitive aspects of portfolio managers - how they perceive, assess, evaluate
and process information to arrive at an investment decision – might allow us to isolate and
identify causal factors in outperformance. The thesis discussed in this paper, that transfer and
analogical reasoning in other domains can explain the mechanism by which portfolio managers
analyze companies, is a first step in demystifying the analyst’s cognitive process. Different
mechanisms of transfer have been documented by the empirical studies in different fields
discussed in this paper. We have shown conceptually that the field of security analysis shares the
same underlying structures as these other domains.
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
1
Introduction
The ultimate goal, the multi-trillion-dollar question, that individual investors as well as
allocators at pension funds, endowments and sovereign wealth funds are trying to figure out is
which portfolio manager1 will outperform the market over the long term. In attempts to answer
this question, previous academic research has primarily focused on factors that appear to
correlate with performance including, but not limited to, psychopathy (Ten-Brinke, Kish, &
Keltner, 2018), educational diversity (Tan & Sen, 2017), social networks (Cohen, Frazzini, &
Malloy, 2010), personality (Noe & Vulkan, 2018), specialization (Kostovetsky & Ratushny,
2016) and skill (Ericsson & Andersson, 2005). While these factors document positive
correlation, they have not established causality. What has been neglected in this body of research
is an examination into the actual cognitive process of managers – how they perceive, assess,
evaluate and process information to arrive at an investment decision.
One could argue that investor’s cognitive process has been addressed through extensive
work in behavior finance, including the work of three Nobel lautarites - Richard Thaler, Daniel
Kahneman and Robert Shiller. There are books written by them (Akerlof & Shiller, 2010;
Kahneman & Egan, 2011; Thaler & Sunstein, 2008) and numerous others (Lifson & Geist, 1999;
Mackay, 1869; Montier, 2009; Peterson, 2011; Peterson & Murtha, 2010; Zweig, 2007) on both
individual and group investor psychology. But these works focus mainly on how heuristics and
emotions like fear and greed can result in subpar investment results. They do not address
explicitly how the manager perceives and evaluates information to arrive at an investment
decision.
1
The terms “portfolio manager,” “money manager,” “investment manager,” and “analyst” will be used
interchangeably but in this context all refer to the same job function. The domains of “portfolio management” and
“security analysis” will also be used interchangeably.
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
2
The belief is that if we can understand the cognitive process of managers, that we can
isolate factors that differentiate the small minority of star managers that outperform from the vast
majority that underperform. It should be noted that that minority is extremely small. According to
the latest Standard & Poors SPIVA US Scorecard, over the past 15 years, 92.4% of large cap
managers, 95.1% of mid cap managers and 97.7% of small cap managers failed to outperform
the market (Soe & Liu, 2018).
Identifying causal factors for outperformance has wide implications not only in the
selection of investment managers but also in hiring, training and teaching new entrants to
the industry. There are few papers which explicitly discuss mechanisms of analogical transfer in
the domain of security analysis. (Olsen, 2002) examines investment decision-making from a
naturalistic decision perspective and (Gregan-Paxton & Cote, 2000) state that, “…the analogical
reasoning literature provides a theoretical support for arguing that investors frequently utilize
existing knowledge for generating predictions about a company’s future” (p. 307). Sonkin &
Johnson (2017) discuss how a portfolio manager builds-up schemas or checklists of investment
likes and dislikes through many years of trial and error, which they use to, “…judge new
investment candidates quickly. The criteria in the templates allow the manager to recognize
patterns and act as a mental shortcut to reduce the time and energy needed to make and
investment decision.” ( p. 342) While Sonkin & Johnson discuss the criteria managers use to
evaluate new investment candidates, they fall short as they do not explain the actual mechanism
of the analyst’s cognitive process works.
A money manager’s sole purpose is to earn an investment return greater than the market.
If a manager cannot beat the market, an investor would be better off putting their money in lowcost index funds. The only way a manager can beat the market is by identifying a genuine
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
3
mispricing (a mistake made by the market) by which they develop a variant perspective – a view
that is different from consensus expectations. There are only three ways that this can be
accomplished: through an information advantage (knowing something the market does not
know), an analytical advantage (looking at the same data set available to all other investors but
drawing a different conclusion that proves to be correct) or a cost or trading advantage (the
ability to trade when others cannot or will not) (Sonkin & Johnson, 2017). The concept of
transfer relates primarily to an analytical advantage. The successful manager has the ability to
view a particular situation (the target), recognize that it matches a specific past situation (the
source) or an amalgam of past situations (schematized source) and then map to the target to
ensure they are correct. The faster or more accurately a manager can perform this process, the
more successful they will be. Therefore, the concept of transfer is a critical element in
understanding the cognitive process of successful portfolio managers.
Thesis
Transfer is evidenced in many domains that have similar problem-solving structures to
security analysis including medical diagnosis (Lubarsky, Dory, Audétat, Custers, & Charlin,
2015), bridge (Charness, 1979) and chess (Chase & Simon, 1973). This paper explores how
analogical transfer can explain the mechanism by which portfolio managers access existing
knowledge and applying that knowledge to new situations they encounter. In this paper, the case
for a conceptual model of transfer for security analysis will be laid-out and provide a basis for
anticipated future empirical research.
Analogical Mapping and Transfer
Analogical reasoning is a core element of cognition. “Spearman (1923) once claimed that
all intellectual acts involve analogical reasoning.” [emphasis original] (Novick, 1988, p. 510).
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
4
Individuals make sense of the world by organizing objects into familiar categories. One way of
forming categories is by analogy, which is the process of understanding a new situation by
comparing it to a familiar situation. The familiar situation is called a base or source analog.
The new or unfamiliar situation is known as the target analog (Gentner & Holyoak, 1997) shown
in Figure 1.
Figure 1: Source and target situations
The study of how individuals reason by analogy through using previously acquired
knowledge to bear on a new situation is known as “transfer.” Reasoning by analogy involves
identifying similarities in the relational systems between two situations and making
extrapolations based on these similarities (Gentner & Smith, 2012). In their 2012 paper, Gentner
& Smith discuss a set of mechanisms that are present in all types of analogical reasoning.
Retrieval is the ability to view a target and access a similar source present in the individual’s
knowledge base. Mapping is the process of aligning the relational systems and projecting
between the target and base. Evaluation is performed after the mapping is completed to judge the
appropriateness of the pairing. Figure 2 adds mapping and retrieval to Figure 1.
Familiar situation
Source
Copyright © 2018 Paul D. Sonkin
Retrieval
Mapping
New or unfamiliar
situation
Target
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
5
Figure 2: Retrieval and mapping added
The ability to use previously acquired knowledge to bear on new situations can have
impediments. If an individual has never encountered a similar situation, they have no knowledge
base to retrieve from, or map to, as shown in Figure 3:
Retrieval
Source
Mapping
New or unfamiliar
situation
Target
Figure 3: No past source to retrieve from or map to
Even if the individual has the knowledge stored in their memory, they might not be able
to retrieve that knowledge if they do not realize the relevance to previous situations. For retrieval
to occur, the individual must not only have a similar source analog but also must notice the
similarity of the source to the target. In a study involving the “Dunker’s Radiation Problem,”
Gick & Holyoak (1980) asserted that if the source and target are drawn from different domains,
the correspondences between situations will not be obvious. The study showed that transfer
frequency was low when the surface features of the source and target problems were
substantially different even though the underlying relationships were analogous. In this study,
subjects first read a story about a military problem and its solution that was intended to serve as
an analogous solution to a subsequent medical problem. The solution was identical for the
military problem (a dispersion solution) but the surface features were different (soldiers attacking
a castle vs. radiation attacking a tumor) see Figure 4. In one experiment, only 20% of the
subjects produced the dispersion solution. This result highlights the fact that retrieval can be
impeded when surface features are dissimilar even though underlying structures are the same.
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
Different Surface
Features
6
Same Underlying
Structure
Figure 4: Surface features and underlying structure of Dunker’s Radiation Problem
Another study by Gick & Holyoak (1983) involving Dunker’s Radiation Problem showed
that retrieval significantly increased after subjects were given a hint. In various manipulations of
the problem, more subjects were able to solve the problem after they were given a hint (merely to
use the prior story to solve). For example, in one experiment, a total of 88 subjects were given
the problem under varying conditions. Before being given a hint, only 26 were able to solve the
problem. After being given the hint, an additional 40 subjects were able to solve the problem.
The fact that transfer was significantly enhanced by the hint highlights the impediment caused by
the dissimilar surface stories. In effect, the hint revealed to the subject the underlying structure
and removed the barrier to retrieval and mapping created by the differing surface features.
The reverse situation—when surface features are similar but underlying relationships are
different—can also create issues with transfer, especially for novices. For example, Chi,
Feltovich, & Glaser (1981) investigated the differences in categorization and representation of
physics problems by novices and experts. In one study, they asked eight advanced PhD students
(experts) and eight undergraduate students (novices) to categorize 24 different physics problems
into groups based on the similarities of the solutions. They found that novices categorized the
problems based on surface features (such as a spring or inclined plane) whereas experts classified
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
7
on according to major physics principles relating to the problem (such as Newton’s Second
Law).
Similarity serves as an organizing principle by which people categorize, classify and
generalize. The more features that the source and target have in common, the more similar they
are (Tversky, 1977). The relationship is shown in Figure 5, which was derived from Gentner &
Markman, (1994). However, as we discussed previously, what is important is recognizing the
similarity of the underlying relationships rather than the similarity of surface features.
More Similarity
Source
Less Similarity
Source
Target
Target
Figure 5: Source and target similarity
When a source is retrieved from memory the mapping process assesses how two
situations are similar. Structure mapping theory (Gentner, 1983), (Gentner & Smith, 2012) holds
that analogical mapping requires the aligning of two situations based on their common relational
structure or higher order relations rather than surface features. The basic goal of analogical
mapping is to focus attention on alignable differences while deemphasizing non-alignable ones
(Holyoak, 2012).
“Mapping” Analogical Transfer to Portfolio Management
As previously mentioned, successful managers have the ability to view a new idea (the
target), retrieve a suitable source from past experience and then align and map similar higherorder relations. To help clarify this process to the reader, we will use the process of analogical
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
8
mapping to explain the process of analogical mapping. For the reader, the new or unfamiliar
target is the domain of security analysis and the source or familiar situation is the process of
medical diagnosis. While the two domains have very different surface features, we will show a
common underlying structure.
The source analog will be a pediatrician diagnosing an illness. Through their long years
of education, the pediatrician builds-up a comprehensive knowledge base about many different
conditions such as strep throat. From seeing hundreds and hundreds of cases of strep throat, the
doctor develops a schema for what a typical case of strep throat looks like. Although, the doctor
probably has a few individual concrete cases of strep throat in their memory that they remember
in detail. If a new patient (“the target situation”) comes in to the doctor’s office, the first thing
the doctor will ask is something like, “So what is going on?” The patient then might say they
have symptoms of a sore throat and a fever. The doctor will use these surface features to develop
a problem representation, which is constructed instantly based on what the doctor perceives and
their prior knowledge (Chi et al., 1981). The symptoms will act as a retrieval cue for the
appropriate source analog. The doctor then maps a set of similarities that align the elements of
the source and the target (Gick & Holyoak, 1980; Holyoak, 2012).
What a doctor retrieves from their knowledge base when diagnosing a patient is called an
“illness script.” A script is a more specific type of schema that represents generalized events as a
unit. The script also represents sequences of events. The classic example is the “restaurant
script.” When a person enters a restaurant, they expect to see tables, chairs, waiters and food. But
there is a sequence of events that they also expect. When they walk into the restaurant the
maître’d will greet them, take them to a table and give them menus. The waiter will then come
over and take their dinner order. (Custers, 2015) An illness script is a similar construct, when the
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
9
doctor examines a patient there are different chains of events and symptoms for different
illnesses. In the diagnosis process the doctor examines the patient (the target) and certain
symptoms act as a retrieval cue for an illness script that are mapped to the target. This basic
construct of this process for the pediatrician is illustrated in Figure 6:
Observe
surface
features
Retrieval Cue
Source
(specific instance)
Mapping
Problem
representation
Target
Schema
(illness scripts)
Figure 6: Basic construct of analogical reasoning for a pediatrician
As detailed by Chi et al. (1981), studying the analogical reasoning of novice and experts
can highlight different aspects of transfer between the two groups. In the field of medicine,
Coderre, Mandin, Harasym, & Fick (2003) performed a study of experts and novices diagnosing
gastroenterology cases. The subjects were 20 non-experts who were final year clinical clerks at
the University of Calgary and 20 experts who were specialists in the practice of gastroenterology
for over 5 years. Four different presentations of gastrointestinal illness were constructed, and
subjects were given a written test which consisted of 12 questions. The answers were scored on
two scales, the first of which was an assessment of cognitive process to ascertain whether the
subject used hypothetico-deductive reasoning (“diagnosis-to-data” method where one observes
data, generates a hypothesis then tests hypothesis), scheme-inductive reasoning (forward
thinking where characteristics are added to narrow the list of potential diagnoses), or pattern
recognition (available primarily to experts by instantly recognizing illness scripts). The second
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
10
was a measure of the accuracy of the diagnosis. The study showed that novices used hypotheticodeductive reasoning 41.7% of time versus scheme-inductive reasoning 34.6% of the time and
pattern recognition 23.8% of the time. In stark contrast, experts used hypothetico-deductive
reasoning 6.7% of the time, scheme-inductive reasoning 44.2%% of the time and pattern
recognition 49.2% of the time. In terms of accuracy, the results were presented as odds of
diagnostic success. The study concluded that when subject (both novice and expert) used pattern
recognition the odds of diagnostic success were over 10 times relative to the odds of success
when hypothetico-deductive reasoning was used.
While not explicitly labeled as transfer in the study, the underlying structure and
relationships are very similar - when subjects are experts in a specific domain, they are able to
retrieve, map and judge a new situation via pattern matching significantly more accurately than
novices using a hypothetico-deductive reasoning method. An idea for future research to explore
this phenomenon in the domain of security analysis would be to modify the study described in
the Coderre paper and replicate it with novice and experienced analysts.
Now that we have detailed the process for the pediatrician and discussed transfer in the
field of medicine, we will show that despite the differences in surface features between medicine
and portfolio management, the underlying structure is the same (see Figure 7).
When the analyst is presented with a new target, a new stock idea (in this case a company
called Applied Materials that produces capital equipment used in the production of
semiconductors) they will observe surface features such as the industry it is in, management,
valuation, return on invested capital, etc. From this set of observations, the analyst will create an
instantaneous problem representation based on what they perceive in the current situation and
their prior knowledge. The retrieval cue will search for similar situations – a source they might
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
11
have analyzed in the past. In this case the analyst might access a specific instance (KLA Tencor
another company that produces semiconductor capital equipment) but also has schemas and
scripts from other companies they have analyzed in the past.
Observe
surface
features
Retrieval Cue
Source
(specific instance)
Mapping
Problem
representation
Target
Schema
(and scripts)
Figure 7: Basic construct of analogical reasoning for a portfolio manager
It is important to highlight where differences between a novice and an expert might
differ. If the analyst was a relative novice, they might use KLA Tencor as a source and map to
the surface features (the fact that they are both semiconductor capital equipment companies). On
the other hand, an expert will most likely look to the similarities in underlying structure to other
companies in their schema and perhaps map to firms producing capital equipment in other
cyclical industries such as Caterpillar, Emerson Electric or Illinois Tool Works. This situation is
similar to the previously discussed study Chi et al. (1981) where novices mapped back to surface
features like springs and planes while experts mapped back to underlying physics principles.
Also, like an experienced gastroenterologist in the study previously discussed, the experienced
analyst would likely use pattern matching to identify a similar situation (cyclical capital
equipment) rather than a hypothetico-deductive which would likely be used by a novice.
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
12
In Figure 8 below, we align the two situations using structural mapping theory based on
their common relational structure or higher order relations. We see that while the surface features
between medicine and security analysis are quite different, the underlying structure is the same.
The analyst, like the pediatrician, observes features of the target, creates a problem
representation, which produces a retrieval cue that maps the target to pre-existing sources in the
analyst’s knowledge base.
Observe
surface
features
Retrieval Cue
Source
Mapping
(specific instance)
Problem
representation
Target
Schema
(illness scripts)
Observe
surface
features
Retrieval Cue
Source
Mapping
(specific instance)
Problem
representation
Target
Schema
(and scripts)
Figure 8: Mapping pediatrician to portfolio manager
This analysis shows (by using analogical mapping) that the process an analyst uses to
evaluate new situations is similar to the analogical reasoning performed by a doctor diagnosing
an illness. It provides a conceptual framework to guide future empirical research in the domain
of security analysis.
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
13
Conclusions and Further Study
The holy grail of manager selection is to identify those individuals who will outperform
the market over the long term. Formal academic inquiry in the past has focused on the study of
correlational attributes such as social networks, specialization and pedigree. In contrast,
investigation into cognitive aspects of portfolio managers - how they perceive, assess, evaluate
and process information to arrive at an investment decision – might allow us to isolate and
identify causal factors in outperformance.
The thesis discussed in this paper, that transfer and analogical reasoning in other domains
can explain the mechanism by which portfolio managers analyze companies, is a first step in
demystifying the analyst’s cognitive process. Different mechanisms of transfer have been
documented by the empirical studies in different fields discussed in this paper. We have shown
conceptually that the field of security analysis shares the same underlying structures as these
other domains.
A next step for future research would be to modify these studies and create a body of
empirical research examining the mechanism of transfer in the field of security analysis.
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
14
References
Akerlof, G. A., & Shiller, R. J. (2010). Animal spirits: How human psychology drives the
economy, and why it matters for global capitalism. Princeton university press.
Charness, N. (1979). Components of skill in bridge. Canadian Journal of Psychology, 33(1), 1–
16.
Chase, W. G., & Simon, H. A. (1973). Perception in chess. Cognitive Psychology, 4(1), 55–81.
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Catagorization and representation of physics
problems by experts and novices. Cognitive Science, 5(2), 121–152.
Coderre, S., Mandin, H., Harasym, P. H., & Fick, G. H. (2003). Diagnostic reasoning strategies
and diagnostic success. Medical Education, 37(8), 695–703.
Cohen, L., Frazzini, A., & Malloy, C. (2010). Sell-side school ties. Journal of Finance, 65(4),
1409–1437.
Custers, E. J. F. M. (2015). Thirty years of illness scripts: Theoretical origins and practical
applications. Medical Teacher, 37(5), 457–462.
Ericsson, K. A., & Andersson, P. (2005). The Enigma of Financial Expertise : Superior and
Reproducible Investment Performance in Efficient Markets by, 2005, 1–58.
Gentner, D. (1983). Structure-Mapping : A Theoretical Framework for Analogy. Cognitive
Science, 7(2), 155–170.
Gentner, D., & Holyoak, K. J. (1997). Reasoning and learning by analogy - Introduction.
American Psychologist, 52(1), 32–34.
Gentner, D., & Markman, A. B. (1994). No Difference Without Similarity. Psychological
Science, 5(3), 152–159.
Gentner, D., & Smith, L. (2012). Analogical Reasoning. Encyclopedia of Human Behavior:
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
15
Second Edition (2nd ed., Vol. 1). Elsevier Inc.
Gick, M. L., & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology, 12(3),
306–355.
Gick, M. L., & Holyoak, K. J. (1983). Schema induction and analogical transfer. Cognitive
Psychology, 15(1), 1–38.
Gregan-Paxton, J., & Cote, J. (2000). How do investors make predictions ? Insights from
analogical reasoning research. Journal of Behavioral Decision Making, 13(3), 307–327.
Holyoak, K. J. (2012). Analogy and Relational Reasoning. In The Oxford Handbook of Thinking
and Reasoning (pp. 234–259). Oxford: Oxford University Press.
Kahneman, D., & Egan, P. (2011). Thinking, fast and slow (Vol. 1). Farrar, Straus and Giroux
New York.
Kostovetsky, L., & Ratushny, V. (2016). Returns to Specialization: Evidence from Health
Mutual Fund Managers. Ssrn.
Lifson, L. E., & Geist, R. A. (1999). The Psychology of Investing (Vol. 70). John Wiley & Sons.
Lubarsky, S., Dory, V., Audétat, M.-C., Custers, E., & Charlin, B. (2015). Using script theory to
cultivate illness script formation and clinical reasoning in health professions education.
Canadian Medical Education Journal, 6(2), e61-70.
Mackay, C. (1869). Memoirs of extraordinary popular delusions and the madness of crowds.
George Routledge and Sons.
Montier, J. (2009). Behavioural investing: a practitioner’s guide to applying behavioural
finance. John Wiley & Sons.
Noe, T., & Vulkan, N. (2018). Naked aggression: Personality and portfolio manager
performance. PLoS ONE, 13(2), 1–16.
Copyright © 2018 Paul D. Sonkin
ANALOGICAL TRANSFER AS A MECHANISM IN SECURITY ANALYSIS
16
Novick, L. R. (1988). Analogical Transfer, Problem Similarity, and Expertise. Journal of
Experimental Psychology: Learning, Memory, and Cognition, 14(3), 510–520.
Olsen, R. A. (2002). Professional Investors as Naturalistic Decision Makers : Evidence and
Market Implications, 3(3), 161–167.
Peterson, R. L. (2011). Inside the investor’s brain: the power of mind over money (Vol. 295).
John Wiley & Sons.
Peterson, R. L., & Murtha, F. F. (2010). MarketPsych: how to manage fear and build your
investor identity. John Wiley & Sons.
Soe, A. M., & Liu, B. (2018). SPIVA® U.S. Scorecard (pp. 1–31). S&P Dow Jones Indices
LLC.
Sonkin, P. D., & Johnson, P. (2017). Pitch the Perfect Investment. New York: John Wiley &
Sons.
Tan, E. K. M., & Sen, A. (2017). Does educational diversity of managers matter for the
performance of team-managed funds? Accounting and Finance, 1–37.
ten Brinke, L., Kish, A., & Keltner, D. (2018). Hedge Fund Managers With Psychopathic
Tendencies Make for Worse Investors. Personality and Social Psychology Bulletin, 44(2),
214–223.
Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving decisions about health, wealth, and
happiness. Springer.
Tversky, A. (1977). Features of Similarity. Psychological Review, 84(4), 327–352.
Zweig, J. (2007). Your money and your brain: how the new science of neuroeconomics can help
make you rich. Simon and Schuster.
Copyright © 2018 Paul D. Sonkin