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Hindsight bias and investment decisions making empirical evidence form an emerging financial market

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Abstract

We studied the hindsight bias and investor decision making by employing the novel approach asset selection effect and sign of return effect. The study investigated the hindsight bias and investor decision making through questionnaires. The respondents are divided into three groups namely bank financial managers, stock market investors and students. The statistical significance of the asset selection effect and sign of return effect is tested by proportional z-test. Furthermore, the correlation of the memory error and recall error is also determined. The overall perceived error (hindsight bias) relationship is checked with the confidence in recall and confidence in estimate. We found strong evidence of hindsight bias in all respondents groups and its worst consequence on investment decision making. The bank financial managers were found less exposed to hindsight bias in comparison to stock market investors in asset selection effect. However, in sign of return effect the financial managers were more hindsight biased than the stock market investors. The relationship of hindsight bias and confidence in recall and confidence in estimate also confirms that all the respondents were hindsight biased and more confident in their estimate and less confident in their recall. All the respondents claim that they knew the phenomenon all along are wrong in their estimate. The respondents were unable to learn from previous errors and unable to detect their errors in estimate and recall. This error in prediction leads the investor to bear the risk above their accepted level which is harmful to their wealth.
International Journal of Research Studies in Management
2013 October, Volume 2 Number 2, 77-88
© The Authors
Hindsight bias and investment decisions making empirical
evidence form an emerging financial market
Hussain, Muntazir
International Islamic University Islamabad, Pakistan (muntazirjan@gmail.com)
Shah, Syed Zulfiqar Ali
International Islamic University Islamabad, Pakistan (zulfiqar.shah@iiu.edu.pk)
Latif, Khalid
International Islamic University Islamabad, Pakistan (Khalidlatif382@yahoo.com)
Bashir, Usman
International Islamic University Islamabad, Pakistan (bbashir.usman@gmail.com)
Yasir, Muhammad
International Islamic University Islamabad, Pakistan (yasirfw@hotmail.com)
Received: 24 January 2013 Revised: 6 April 2013 Accepted: 28 April 2013
Available Online: 22 May 2013 DOI: 10.5861/ijrsm.2013.323
ISSN: 2243-7770
Online ISSN: 2243-7789
Abstract
We studied the hindsight bias and investor decision making by employing the novel approach
asset selection effect and sign of return effect. The study investigated the hindsight bias and
investor decision making through questionnaires. The respondents are divided into three
groups namely bank financial managers, stock market investors and students. The statistical
significance of the asset selection effect and sign of return effect is tested by proportional
z-test. Furthermore, the correlation of the memory error and recall error is also determined.
The overall perceived error (hindsight bias) relationship is checked with the confidence in
recall and confidence in estimate. We found strong evidence of hindsight bias in all
respondents groups and its worst consequence on investment decision making. The bank
financial managers were found less exposed to hindsight bias in comparison to stock market
investors in asset selection effect. However, in sign of return effect the financial managers
were more hindsight biased than the stock market investors. The relationship of hindsight bias
and confidence in recall and confidence in estimate also confirms that all the respondents
were hindsight biased and more confident in their estimate and less confident in their recall.
All the respondents claim that they knew the phenomenon all along are wrong in their
estimate. The respondents were unable to learn from previous errors and unable to detect their
errors in estimate and recall. This error in prediction leads the investor to bear the risk above
their accepted level which is harmful to their wealth.
Keywords: hindsight bias; asset selection effect; sign of return effect; estimate error; recall
error; overall perceived error
Hussain, M., Shah, S. Z. A., Latif, K., Bashir, U., & Yasir, M.
78 Consortia Academia Publishing
Hindsight bias and investment decisions making empirical evidence form an emerging
financial market
1. Introduction
Since the emergence of behavioral finance two basic debates are the focus of researcher in the context of
investment decision making. Are the investor rational and market are efficient? These are conflicting areas where
behavioral finance contradicts with standard finance. Thaler (2005) argues that the contradiction in these subjects
and question of rationality is raised based on two assumptions. The first assumption is that the investors are very
much capable of absorbing and taking new information and set their selves accordingly. The investor decision is
free of cognitive and emotional biases. The second assumption is the normality of investor choices. Nofsinger
(2001) if the investor is rational and market is efficient then why the global financial crises 2008 and global
recession happened where the major economist were failed to understand the nature of phenomena and unable to
tackle the problem? The work of psychologists Daniel Kahneman and Amos Tversky (1974) has created the
platform to apply the psychology to finance. The investors are not perfectly rational. The question of rationality
was answered simple way, “the application of psychology to finance that we call the behavioral finance”. The
investment decisions are subject to cognitive and emotional biases that make the investor to take the worst
decisions. Bernstein (1998) it is the impact of human cognitive and emotional errors that creates the bad decision
and leads the investor to excessive risk. Parikh (2011) argues that the excessive risk the investors take due to the
involvement of biases. These biases create mistakes and other investor takes advantage of these mistakes.
According to standard finance the investor are rational and market are efficient. The standard finance
suggest that investment decision are determined by interest rates, income, consumption, level of economic
activity, cost of capital goods, technological change, public policy, and many others. No doubt the investor the
work of standard finance can’t be ignored however, to check the balance approach of behavioral finance and
standard finance would lead to better decision. Thus appealing approach to explain investment behavior
practically is to consider the psychological factors that affect the investment decision. Pompian (2006)
mentioned twenty two biases in his famous book “behavioral finance and wealth management” that effects
investment decisions. In our study we have investigated one of the factors that effects the investment decision is
called the Hindsight bias. This study was first conducted by Fischoff (1975) to define and analyze the hindsight
bias. According to this study, person tendency to distort a previous judgment in the direction of the new
information, after learning the real outcome of a situation or correct answer to question. Individuals after
receiving final information claim to have known it all along. Once the event has passed, they seem more
understandable and also more predictable than they seemed at the beginning.
In investment work we often face with the situation where we think that certain event is predictable even if
it is not. Such events we often see in stock market investment. Where investor predicts certain stock would
increase in value. Later on when the real event happens our prediction goes wrong and we come across excessive
risk. Due to such irrational predictions we often see stock market crashes and boom. Such events may cause
extraordinary losses to one investor and gain to other.
Learning from past experience and ability to recall is one of the basic approaches the investor follows while
doing investment decisions. In order to invest, the investor search out the information and financial data. The
data is arranged and transformed in meaningful way to carry the investment decision. In order to do so they
perform various cognitive tasks and involve the memory recall process (Fischhoff, 1975). We are going to find
whether this recall and cognitive process is free of omission and errors? How does the acquisition of final
knowledge effect investment decisions? More formally whether the investors are hindsight biased or not and
what is the impact of hindsight bias on investment decisions?
Hindsight bias and investment decisions making empirical evidence form an emerging financial market
International Journal of Research Studies in Management 79
In psychological literature we can see three types of theories that explain the hindsight bias. The popular
theories are named “Just World Theory”, “Impression Management Theory”, and “Cognitive Explanation
Theory”. The cognitive explanation theory is one of the most appropriate to explain the hindsight bias in the
special case. That they people do wrong prediction of event or claim that they “Knew the event all along”. They
claim that event was predictable even if it was not. The errors in memory and recall cause the people to learn
from their experience even after the realization is given.
According to economic theory investor are “Bayesian decision-makers” they assume that the investor update
their information when they are presented the new information. They recall their initial information and update
their information accordingly. The investors can recognize their error and learn from past and decide accordingly
in future investment decisions. One of the fundamental assumptions in these theories is that the investors
compare the new information with the previous expectation. They are able to compare the new and previous
expectation. Economic theories suggest that arranged and transformed information the investor use for the
purpose investment is free of omissions and errors. Furthermore, the investors are efficient in performing these
cognitive tasks and easily manage this information. They also assume that the recall they made is error free. The
similar assumptions are also followed by standard rational choice theory that states that the investors are efficient
in determining relevant information and very much capable of separating the relevant information from
irrelevant. Investors are able to process the information accurately. “The representative investor is assumed to
understand the economy and the process determining asset prices; the individual investor frequently does not”
(Keynes, 2006). However this is ideal case and practically these cognitive tasks and recall process involve the
error and omission (Biais & Weber, 2008).
One of the primary objectives of this study is to check empirically these recall errors and omission that lead
to hindsight biasness. How the hindsight bias can impact investor decision making. How the final information
can impact the investment decision. The study is of extreme significance it can lead the investor to take
excessive risk. When the investment appreciate, hindsight biased investors tend to rewrite their own memories to
portray the positive developments as if they were predictable. Over the time, this rationale can cause excessive
risk taking. Furthermore, hindsight investors make incorrect forecast which can lead him to undiversified
portfolios investment. The hindsight investor will lose the lesson to learn from past and show aggressive
behavior in investment.
Our contribution lies in two aspects. First we have studied the practical respondents (Islamabad Stock
Exchange Investors and Financial Managers of banks) where majority of literature related to Pakistan is taking
only students as target respondents. Further, we have compared the biasness of students with the investors. We
have incorporated the new angle of measuring the hindsight bias in two different aspects i.e., hindsight in asset
selection, sign of return effect. We have applied Fischhoff (1975) procedure which is for the first time used to
check hindsight bias in this context. Finally the study is organized in four different sections, the section 2
contains literature review, following by model and methodology is given in section 3, the results and conclusion
is given in section 4.
2. Literature review
Past experiences and data is one of the tools which investor use to predict the event happening in future.
Most of investor feels confident to predict the future event to happen base on the personal erroneous cognition.
Investor thinks that the event was predictable even if it was not. The investor take decision on such erroneous
beliefs and cognition (biases) which leads them to bad decision. Such phenomenon is studied in behavioral
finance and psychology literature called the hindsight bias. This bias effects the investment decision. Such
evidence is quoted in literature in the following words.
Numerous studies have been conducted on impact of hindsight bias on investing decision. Like Tversky and
Kahneman (1974a) stated that investor limited principles of life experiences are better to use but these can lead
Hussain, M., Shah, S. Z. A., Latif, K., Bashir, U., & Yasir, M.
80 Consortia Academia Publishing
to biases in investment. One of the biases he studied is the hindsight bias which lead the poor investment
performance. Biais and Weber (2008) studied the hindsight bias and concluded that hindsight biased investor the
ex-post recollection of the initial belief will be closer to the realization than the true ex-ante expectation. Buksar
and Conolly (1988) concluded that one should learn from past experience and should adjust oneself to the new
situation but hindsight biased investors loose this learning and don’t learn from past experiences.
In addition, Vein, Biais, and Weber (2008) studied hindsight bias and concluded that investors were not able
to remember their initial answer (initial experience). This can lead the investors to poor performance of
investment by underestimating the volatility. The level of exposure to these biases is dependent to other factors
as well like gender, experience as well. Like Lewellen, Lease, and Schlarbaum (1977) men are more
overconfident. Kaustia, Alho, and Puttonen (2008) concluded that the level of experience reduce the anchoring
bias. Frederick (2005) stronger cognitive ability can enhance the investment decision making.
The first study conducted to check hindsight bias was (Fischhoff, 1975; Fischhoff & Beyth, 1975). Fischhoff
(1975) finds that receipt of outcome knowledge affects subject’s judgments in the direction predicted by the
tendency to perceive reported outcomes as having been relatively inevitable. This tendency was called as
creeping determinism but is nowadays better known as hindsight bias. Fischhoff (1975) concludes that
unperceived creeping determinism can seriously impair our ability to judge the past or learn from it. In a more
recent study Biais and Weber (2008) present that for hindsight biased investor the ex-post recollection of the
initial belief will be closer to the realization than the true ex-ante expectation. Such investors also fail to
remember how ignorant they were before observing outcomes and answers. The hindsight biased people don’t
learn from past errors. The similar study was conducted by (Camerer, Loewenstein, & Weber, 1989).
Hindsight bias is not affecting only in unconscious way, like in ex-post evaluation of ex-ante decision, but
also when subject is aware of the bias. Buksar and Conolly (1988) find that student subjects working on a
strategic choice case, both alone and in groups were unable to ignore what they had been told about the actual
results of a choice. As a result, they distorted their evaluations of the original decision and the factors influencing
it. Behavior caused by Hindsight bias is also recognized in studies observing other biases. Camerer et al. (1989)
who study judgmental errors in economic settings, find that asymmetric information is not always beneficial for
the better-informed agent, which violates the common assumption of economic analyses. This effect is known as
curse of knowledge.
Camerer et al. (1989) noted the course of knowledge may also influence individual decision making under
uncertainty. Exaggerating the predictability of events intensifies the regret people feel when choices yield
outcomes worse than those that would have resulted from forgone options. This is in line with hindsight bias as
people thinking behind this goes like I knew this would happen, why I did not act correctly. Baron and Hershey
(1988) present the similar results that the course of knowledge suggests that outcome information will be
overused; principals will tend to think that ex-ante optimal decisions with unfavorable outcomes were
non-optimal and that non-optimal decisions with favorable outcomes were optimal. Camerer et al. (1989)
suggest that investor will be excessively penalized for negative outcomes and insufficiently rewarded for
favorable results.
Buksar and Conolly (1988) also presented that when outcomes are poor, then, people's evaluations of earlier
decisions tend to be biased in an unflattering direction. “I should have known it all along they feel, puzzled at
their poor decision making. Traditional way to justify market rationality is to state that even though some
investors are irrational, markets in total are rational as the individual irrationalities are random and thus on
average cancel each other out. Camerer et al., (1989) found that hindsight bias in markets was half as large as
bias in individual judgments. Their data suggest that the error-correcting power of markets derives not from the
feedback they provide, but from the disproportionate activity of more rational traders. Hindsight bias is also
affecting performance evaluation in principal agent relation. (Mangelsdorff & Weber, 1998; Madarasz, 2008)
shows that, in a principal agent relationship, the hindsight bias will prevent the principal from correctly
Hindsight bias and investment decisions making empirical evidence form an emerging financial market
International Journal of Research Studies in Management 81
evaluating the performance of the agent. Biais and Weber (2008) tested the hindsight bias and come to
conclusion that biased principals fail to remember what was known when the agent’s decision was taken.
Measuring the level other psychological factors and its relationship with the hindsight bias are also studied
in the literature. Bradley (1981) concluded that expertise and high level of knowledge reduce hindsight bias.
Another factor that reduces hindsight bias is the strong cognitive ability. Lubinski and Humphreys (1997) the
person with high cognitive ability and intelligence perform best investment decision. Such person has strong
memory power and may reduce hindsight bias. Frederick (2005) tested the subjects on the basis of cognitive
reflection test and concluded that the subjects with higher cognitive ability proved better investment decisions. In
literature we see different test for measuring the cognitive ability and expertise.
Tversky and Kahneman (1983) divide the information processing system into two parts: Interactive system
and Experimental System. Epstein (1996) used separate test to check the cognitive ability by rational
experimental inventory. This test checks both the analytical abilities and intuitive experimental processing.
Cacioppo and Petty (1982) used Need for cognition scale to measure the analytical abilities. Cacioppo (1996)
presented that the people with high need of cognition are better informed and have greater capability of
information processing and less exposed to hindsight bias. The second aspect of psychological factor that is
intuitive ability is also narrated by literature and named it as “Intuitive Experimental Processing”, which is
normally measured on the scale of “Faith in Intuition” concluded that people with high score (Faith in Intuition)
are more exposed to hindsight bias (Tversky & Kahneman, 1974b; Epstein, 1996).
Due to vital importance of the impact of this phenomenon is still hot topic of research. Such phenomenon is
studied in other fields like auditing, businesses ethics, court decisions, and many others, and its impact in
different situation. The evidence can be found the studies of (Roese & Vohs, 2010; Pezzo & Beckstead, 2008;
Mueller & Stahlberg, 2007; Nestler & Egloff, 2009; Lowe & Reckers, 2000; Anderson, Jennings, Lowe, &
Reckers, 1997; Gilibert & Banovic, 2009; Wasieleski, Whatley, & Murphy, 2009; Annunziata, 2009; Sligo &
Stirton, 1998; Wallace, Chang, Carroll, & Grace, 2009).
The most recent studies incorporate the short rum aspect of decision. Some studies have studied the impact
of hindsight on short term decision. Tchai (2012) studied the impact of hindsight bias on short term investment
found it significant that hindsight bias distort investment decision and investor take excessive risk due to
erroneous predictability of event. Goodwin (2010) studied the same phenomenon and divides the sample into
three categories, stock broker, students and professional concluded that professional were exposed to such bias.
The experience was the main factor that provides the immune to avoid such bias. Pompian (2006) studies this
phenomenon and concluded that the hindsight bias causes the investor to take excessive risk by considering that
the event is predictable even if it was not. Pezzo and Pezzo (2007) studied the phenomenon and argued that the
investors are not even prepared to accept the reality that they can’t predict the event. If they are given the true
result they would claim that they predicted the true event. They are superior in prediction and they can predict.
He concluded that such investment behavior distorts the investment decision and caused investor to take risk that
is beyond their limits. As for as the literature relating to this specific study is conducted to check the impact of
hindsight bias on investment decision; the study is an attempt to check the phenomenon with respect to Pakistan.
3. Data and research methodology
3.1 Data
The data is collected by questionnaire by targeting students major in Finance and financial Manger of banks
and stock market investors. The 55 students, 89 financial managers, and 56 stock market investors are taken as
sample. The total sample is 200. The questionnaire is distributed in two phases with one weak interval between
phases. In first phase of questionnaire the target respondents given questions related to background information
like age, sex and field experience and ten questions related to individual thinking style which are measured on
Hussain, M., Shah, S. Z. A., Latif, K., Bashir, U., & Yasir, M.
82 Consortia Academia Publishing
five scales. Further the respondents are asked to estimate return of asset based on graph. In return estimation task
the respondents are asked to choose better performance asset. In this assignment the strength of view measured
on five scales. The respondents were instructed to estimate the return of asset on 95% confidence limit. The
second phase is the memory recall phase where respondents were instructed to recall their initial answer and
classify how well they can recall. The answer and return estimate are recollected. Furthermore, in the second
phase the target respondents are given again the same return estimation task with updated information to check
how well they learn from previous experience and how they adjust to new updated information.
3.2 Measurement of Hindsight Bias
Fischoff (1975) methodology to measure and its impact on investment decisions was used in this study. The
hindsight bias is measured in two different context i.e. Asset selection effect, sign of return effect.
Hindsight Bias in Asset selection
If people are given two choices to select better performing asset (as we did) also called winner asset, the
people will remember their initial choice incorrectly and if they are presented the true result the biased investor
will remember that they chose the winner asset which may not true. The basic reason behind this test is the
biased investor are not able to detect that they have choose the wrong choice in case of winning asset (better
performing asset). This over-estimation is measured by comparing the proportion of correct answers and
respective remembered proportion. This data is available by initial selection, recollection of initial selection and
realized results of questionnaire. The proportions Z-test is used to check the statistical significance of difference
between true and remembered proportions of successful answers.
Where p
1
= true proportion of successful answers
p
2
= the proportion of respondents who believe they answered correctly
n
1
and n
2
= sample sizes
Hindsight Bias in Sign of Return Recall
As we have given the questionnaire where the respondent to assign the sign to return they think that winning
asset (better performing asset). The sign of return can either be positive or negative which respondent have to
remember that sign which they responded in first phase of questionnaire. Hindsight biased investors normally
remember the initial sign assigned to the return incorrectly. When hindsight biased investors are presented the
true sign of estimated return they think that they have assigned correct sign which may not be the case. The test
logic is same as we applied to asset selection test but here our focus on sign instead of asset selection. Here the
overestimation of one’s success detected by comparing the actual proportion of correctly estimated sign of return
and respected remembered proportion. To test the statistical significance of difference between true and
remembered proportion correct sign of return, we use the proportional z-test. The procedure is same as asset
selection effect but only difference is the sign of return instead of asset selection.
Hindsight bias and investment decisions making empirical evidence form an emerging financial market
International Journal of Research Studies in Management 83
3.3 Estimate and Memory Error
The error in estimate is measured by difference of original estimate in first phase and real outcome
(true answers)
The error in memory recall is measured by difference of recalled estimates in phase 2 and originally
given in phase 1
The correlation of two errors (memory and estimate error)
Correlation between confidence and memory errors
Relationship between overall perceived error (hindsight bias) and error in estimate and error in recall is given by
Where “H” is hindsight bias, “CE” is confidence in estimate and “CR” is confidence in recall.
4. Results
4.1 Hindsight Bias in Asset Selection
The table 1 below shows the hindsight bias in asset selection effect. The true and remembered proportions
are calculated and their statistical significance is checked by proportional z-test. The 95% confidence interval is
used for level of significance. Our hypothesis is that the difference of two proportions is 0, means that there is no
hindsight bias. Where the difference proportion is in alternative hypothesis is not zero, means the respondents are
hindsight biased. The data analysis is divided into three groups for analysis purpose i.e. bank financial managers,
stock market investors and students. The z-statistics is given in parenthesis.
Table 1
Hindsight Bias and Asset Selection Effect
True Proportion Remembered Proportion
Error= Difference of true
and remembered
Bank Finance Managers 0.63
(N=166)
0.67
(N=158)
0.04
(0.72)
Stock Market Investors 0.44
(N=258)
0.59
(N=107)
0.15***
(2.62)
Students 0.45
(N=164)
0.55
(N=102)
0.1**
(2.67)
Note. * p Value significant at 5%. ** p Value significant at 10%
In case of all respondents there is error in true and remembered proportions but z-statistics is not significant
in all the categories. The stock market investors are highly hindsight biased where the difference is 0.15 and
highly significant at 95% level of significance. The results are in accordance to literature where the stock market
investors are more exposed to hindsight bias. One of example is stock market bubble and crashes in 1990 and
1920 in American stock exchanges. We found the less evidence of hindsight bias in bank financial managers
which is also not significant. Furthermore the students are more hindsight biased which is also significant. The
students’ hindsight bias is to less experience in field of financial decision and knowhow of financial decisions.
Whereas the bank financial managers are highly experienced and related to private sector banks are less exposed
to hindsight bias.
One of the factors that could explain the less hindsight bias in bank financial managers is their expertise
Hussain, M., Shah, S. Z. A., Latif, K., Bashir, U., & Yasir, M.
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level. As we found in literature that hindsight bias is reduced by level of expertise. Second reason the bank
financial manager is less exposed to hindsight bias is the private ownership and audit system in Pakistan. In
private banking sector of Pakistan the true audit measure and true responsibility towards the bank operation and
minimum chances of error is expected by the owners.
4.2 Hindsight Bias in Sign of Return Effect
The test procedure is same for the sign of return effect. The true and remembered proportion of sign of
return is tested by proportional Z-test. The level of significance is 95%. The test results are given below.
Table 2
Hindsight Bias and Sign of Return Effect
True Sign Assigned
Proportion
Remembered Sign
Assigned Proportion
Error= Difference of the
two
Bank Financial Managers 0.11
(N=166)
0.23
(N=121)
0.12****
(2.64)
Stock Market Investors 0.19
(N=145)
0.26
(N=65)
0.07
(1.12)
Students 0.24
(N=117)
0.23
(N=78)
0.1
(0.14)
Note. * p Value significant at 5%. ** p Value significant at 10%
The results in table 2, shows that the bank financial managers are more exposed to the hindsight bias in sign
of return task. This is statistically significant at 95% level of significance. The investors and students are less
exposed to hindsight bias in sign of return task. One conclusion we can draw that the bank financial managers
were more exposed to erroneous prediction of sign of return.
4.3 Correlation in Estimate Error and Recall error and Regression Results
The data has divided into three parts on the basis three main categorize of respondents that is financial
managers, stock market investors and students. The correlation is measured on the basis of estimate error and
memory recall error for each respondents group. The correlation between the estimate error and memory recall
error is 0.7955, 0.60 and 0.69 for financial managers, stock market investors and students respectively.
Confirming that increase of one error is increasing the other error. The regression results as expected the
coefficients of (CE) is positive and (CR) is negative confirming the strong hindsight bias. The respondents are
more confident in estimation as predicted in literature. The hindsight biased responder will have overconfidence
in estimate as “I knew it all along” and unconfident in recall.
5. Conclusion
The study presents the cognitive explanation of investment decision making. The hindsight bias and its
impact are measured in two different aspects that is hindsight bias in asset selection and sign of return. The study
is conducted in two phases by dividing the sample into three main groups, i.e. bank financial managers, stock
market investors and students. The hindsight bias is measured in by comparing the true and recalled estimates of
questions in different phases of survey. The difference is called the “error” or hindsight bias whose significance
is checked by proportional z-test. Furthermore the correlation is checked among different error to check the
relationship of one error with other. Finally the regression results are given to note the overall perceived error
(hindsight bias) and its relationship with the confidence in recall and confidence in estimate.
In two different aspects of hindsight bias (asset selection effect and sign of return effect) the three groups
(banks financial Mangers, Stock Market Investors and Students) are hindsight biased. However, we found strong
impact of hindsight bias in asset selection effect that stock market investor are more exposed to the hindsight
bias, whereas, in sign of return effect the bank financial managers are more exposed to hindsight effect. In both
Hindsight bias and investment decisions making empirical evidence form an emerging financial market
International Journal of Research Studies in Management 85
scenarios the respondents had given the wrong estimate and predictions by exposing themselves to bear higher
risk. They think that they knew the phenomenon all along which is not the case. The respondents were unable to
learn from previous errors when they were given true results; confirming that the hindsight bias respondents are
unable to learn from their previous experiences. In real investment scenario the investor will bear the excessive
risk by saying “I knew it along”.
Finally the correlation and regression results confirm that the respondents are hindsight biased and more
confident in their estimate and unconfident in their recall confirming the strong evidence of hindsight bias.
Where the hindsight biased respondent claim that he know the phenomenon all along which is not the case and
bear the over-optimal risk which is harmful in real life investment.
5.1 Recommendations
The recommendations are presented to minimize the hindsight bias not to remove completely. The hindsight
bias can be overcome by continuous education. To educate the investor to council before they go for major
predictions. The investor may council advisors. Most of hindsight biased investor argues that the positive
outcome of the event was predictable. To avoid this mistake that they will predict the same outcome in future is
mistake. Put the real grounds of available data in consideration. The proper fundamental and technical analysis is
recommended before taking any step of stock investment. The temporary increase or decrease can be deceptive
and it is needed to check all available information before any forecast is made. Don’t rely only on your
prediction powers.
The advisor should be counseled when investor think that “I knew it all along” that this would happen in
future. To avoid past investment mistake the advisor must remind the investor the past experience with the
investor bad decision. Take the all available information resource to judge your decision. The fear of future loss
may cause the investor to run from market and lose the available opportunity. The predicted loss may be able to
be turned to profit if proper analysis is made. If the analysis of information suggests to not going for the
investment then investor should leave otherwise take decision. Concluding the recommendation the proper
education for the investor is essential and investor must consider the fundamental and technical analysis and all
available information resource to predict the future loss or gain.
5.2 Practical applications
The phenomenon is of practical importance especially for the stock market investors. This behavior of
investor causes the stock market bubble and crashes. The investors think that event is predictable even if it was
not predictable. They take risk beyond their optimal by predicting certain activity. They did not take the
appropriate information. They did not update their information and hence loose important information and
expose themselves to risk. If we recall US stock market and investor behavior during 1993; 2003 we would see
that investor predictions were wrong related to the increased stock prices. The temporary stock bubbles were
associated with future increase in stock prices; the investor loose badly after the erroneous prediction. The
investors who are victim of such bias think that they can predict the future market trends better than other. Such
belief causes the investor to take bad decision regarding investing in stocks. The investor invests aggressively
and under estimate the risk.
The investor victim of such bias may not able to learn from past errors as they even don’t want to recall their
previous experiences. If there is temporary boom in the market the hindsight investor may predict that future
stock prices will appreciate and hold the losing stocks for the sake of profits which they feels may increase in
future. Furthermore this temporary appreciation in stock prices may inspire the hindsight biased investor to
admire their money manager for their good performance which is not due to their efforts. This admiration may
cause the money manager to act aggressively. The well-known example of such event is “aggressive growth tech
fund in 1990. Conversely the hindsight investor may blame the good manager for the poor performance. It is
Hussain, M., Shah, S. Z. A., Latif, K., Bashir, U., & Yasir, M.
86 Consortia Academia Publishing
might possible that poor performance is not due to their managerial skills. The famous example of such activity
is “Small cap Value Fund Managers”.
5.3 Future direction of research
So far we have tested the hindsight bias in two different angles that is hindsight bias in asset selection effect
and sign of return effect. The further research could be done to search whether the hindsight bias is reduced with
the level of expertise? Introduce the expertise as new variable and to check its impact on hindsight bias while
dealing in investment decisions. Furthermore as overconfidence bias where the investor is victim of prediction
over-confidence and certainty over-confidence and more close to hindsight bias can be studied to check the
possible impact of over-confidence and hindsight bias with introducing the level of expertise as additional
variable.
6. References:
Anderson, J. C., Jennings, M. M., Lowe, D. J., & Reckers, P. M. J. (1997). The mitigation of hindsight bias in
judges evaluation of auditor decisions. Journal of Practice & Theory, 16, 20-39.
Annunziata, A. (2009). Retrospective bias in expert evidence: Effects on patient and doctor safety. Emergency
Medicine Australasia, 21, 80-83. http://dx.doi.org/10.1111/j.1742-6723.2009.01155.x
Bradley, J. (1981). Overconfidence in ignorant experts. Bulletin of the Psychonomic Society, 17, 82-84.
Bukszar, E., & Connolly, T. (1988). Hindsight bias and investment performance. Working Paper # 476 IDEI
Telehouse.
Bernstein, P. L. (1998). Against the Gods: The remarkable story of risk. USA: John Wiley & Sons Inc.
Camerer, C. F., Loewenstein, G., & Weber, M. (1989). The curse of knowledge in economic settings:
Experimental analysis. Journal of Political Economy, 97, 1232-1254. http://dx.doi.org/10.1086/261651
Cacioppo, J. T., Petty, R. E., Feinstein, J. A., & Jarvis, W. B. G. (1996). Dispositional differences in cognitive
motivation: The life and times of individuals varying in need for cognition. Psychological
Bulletin, 119(2), 197-253. http://dx.doi.org/10.1037/0033-2909.119.2.197
Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology,
42(1), 116-131. http://dx.doi.org/10.1037/0022-3514.42.1.116
Epstein, S., Pacini, R., Denes-Raj, V., & Heier, H. (1996). Individual differences in intuitive–experiential and
analytical–rational thinking styles. Journal of Personality and Social Psychology, 71(2), 390-405.
http://dx.doi.org/10.1037/0022-3514.71.2.390
Fischhoff, B. (1975). Hindsight foresight: The effect of outcome knowledge on judgment under
uncertainty. Journal of Experimental Psychology: Human Perception and Performance, 1(3), 228-299.
http://dx.doi.org/10.1037/0096-1523.1.3.288
Fischhoff, B., & Beyth, R. (1975). I knew it would happen remembered probabilities of once future
things. Organizational behavior and Human Performance, 13, 1-16.
http://dx.doi.org/10.1016/0030-5073(75)90002-1
Frederick, S. (2005). Cognitive reflection and decision making. Journal of Economics Perspectives, 19(4), 25-42.
http://dx.doi.org/10.1257/089533005775196732
Gilibert, D., & Banovic, I. (2009). Effect of training in psychology on the causal interpretation of a clinical
case. European Journal of Psychology of Education, 24, 373-385.
http://dx.doi.org/10.1007/BF03174767
Goodwin, P. (2010). Why hindsight can damage foresight. The International Journal of Applied Forecasting, 17,
5-7.
Keynes, J. M. (2006). General theory of employment, interest and money. Atlantic Publishers.
Lewellen, W. G., Lease, R. C., & Schlarbaum, G. G. (1977). Pattern of investment strategy and behavior
among individual investors. Journal of Business, 50(3), 296-333. http://dx.doi.org/10.1086/295947
Lubinski, D., & Humhreys, L. (1997). Incorporating general intelligence into epidemiology. Intelligence, 24(1),
Hindsight bias and investment decisions making empirical evidence form an emerging financial market
International Journal of Research Studies in Management 87
159- 201. http://dx.doi.org/10.1016/S0160-2896(97)90016-7
Lowe, D. J., & Reckers, P. M. J. (2000). The use of foresight decision aids in auditors judgments. Behavioral
Research in Accounting, 12, 97-118.
Madarasz, K. (2008). Information projection: Model and applications. Working Paper, Berkeley.
Mangelsdorff, L., & Weber, M. (1988). Hindsight bias in principal agent context. The Organization Changing
Markets, 25, 461-678.
Mueller, P., & Stahlberg, D. (2007). The role of surprise in hindsight bias: A meta-cognitive model of reduced
and reversed hindsight bias. Social Cognition, 25, 165-184.
http://dx.doi.org/10.1521/soco.2007.25.1.165
Nestler, S., & Egloff, B. (2009). Increased or reversed? The effect of surprise on hindsight bias depends on the
hindsight component. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35(6),
1539-1544. http://dx.doi.org/10.1037/a0017006
Nofsinger, J. R. (2001). Investment madness: How psychology affects your investing and what to do about it.
USA: Pearson Education.
Pezzo, M., & Pezzo, S. P. (2007). Making sense of failure: A motivated model of hindsight bias. Social
Cognition, 25(1), 147-165. http://dx.doi.org/10.1521/soco.2007.25.1.147
Pezzo, M., & Beckstead, J. (2008). The effects of disappointment on hindsight bias for real world outcomes.
Applied Cognitive Psychology, 22, 491-506. http://dx.doi.org/10.1002/acp.1377
Pompian, M. (2006). Behavioral finance and wealth management. Hoboken, NJ: Wiley.
Parikh, P. (2011). Value investing and behavioral finance. New Delhi: Tata Mcgraw Hill.
Roese, N., & Vohs, K. (2010). The visualization trap. Harvard Business Review, 88(5), 26.
Sligo, P., & Stirton, N. (1998). Does hindsight bias change perceptions of business ethics. Journal of
Business Ethics, 17, 111-124. http://dx.doi.org/10.1023/A:1017946415414
Tchai, T. (2012). The hindsight bias effect in short-term investment decision-making. Universal Journal
of Management and Social Sciences, 2(11), 201-212.
Thaler, R. H. (2005). Advances in behavioral finance, Vol. II. USA: Princeton University Press.
Tversky, A., & Kahneman, D. (1974a). Judgment under uncertainty: Heuristics and biases. Science, 185,
1124-1130. http://dx.doi.org/10.1126/science.185.4157.1124
Tversky, A., & Kahneman, D. (1974b). Extensional versus intuitive reasoning: The conjunction fallacy in
probability judgment. Psychological Review, 90, 293-315.
http://dx.doi.org/10.1037/0033-295X.90.4.293
Vein, B. J., & Hershey, J. C. (1988). Outcome bias in decision evaluation. Journal of Personality and
Social Psychology, 54, 569-579. http://dx.doi.org/10.1037/0022-3514.54.4.569
Wallace H. M., Chang, M., Carroll, P. J., & Grace, J. (2009). I knew it all along, unless I had to work to learn
what I know. Basic and Applied Social Psychology, 31, 32-39.
http://dx.doi.org/10.1080/01973530802659844
Wasieleski M.., Whatley, M., & Murphy, S. (2009). The hindsight bias and attitudes toward police deception in
eliciting confessions. North American Journal of Psychology, 11, 285-296.
Hussain, M., Shah, S. Z. A., Latif, K., Bashir, U., & Yasir, M.
88 Consortia Academia Publishing
... Se a pessoa considera que já sabia de um resultado há tempos, ou seja, superestima sua habilidade de previsão, ela será mais relutante em considerar ideias novas para atacar um problema. Pesquisas mostram que aqueles que apresentam maior viés apresentam piores resultados na área de decisões financeiras (Louie, Chandrasekar & Wu, 2014;Muntazir,Syed,Khalid,Usman &Muhammad, 2013) e estudos indicam que empreendedores superestimam suas previsões de sucesso, muito acima dos resultados estatísticos reais (Roese & Vohs, 2012). ...
... Uma vez que há fortes evidências na literatura que confirmam a presença do viés retrospectivo no cotidiano de pessoas comuns e especialistas (Motavalli & Nestel, 2016;Muntazir et al., 2013), e, além disso, diante das implicações negativas que esse fenômeno acarreta, surge o questionamento de como é possível superar essa falha cognitiva, a fim de se evitar erros e aumentar a eficiência nas tomadas de decisões. Uma dessas estratégias é levar o tomador de decisões a cogitar o oposto, ou seja, elaborar diferentes explicações para o desfecho (Arkes, 2013;Kahneman, 2012). ...
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... Hindsight bias -The existence of the hindsight bias had been indirectly referred to by historians and philosophers (Hexter, 1961) and has been proved to exist in experiments, where people attempt to rationalize the past after the outcome has occurred (Baruch Fischhoff & Ruth Beyth, 1975). If the decision-maker believes that the past was foreseeable, and holds no surprises, they may ignore the opportunity to improve their comprehension (Fischhoff, 1975).When the past outcome was adverse, even the professionals believed that such result was more foreseeable (Strohmaier et al., 2020); financial managers are no exception, being excessively confident of the power of their estimation (Hussain et al., 2013). Research into the hindsight bias reveals that the people's retrospective adjustments to the probability of a certain outcome may be affected by their familiarity with the process itself (Christensen-Szalanski & Willham, 1991). ...
... (R. H. Thaler & Johnson, 1990) 4. Hindsight (Fischhoff, 1975) HN1 Outcomes of any decisions always seem obvious and predictable to me after they have occurred. (Hussain et al., 2013) 1. Status Quo (Samuelson & Zeckhauser, 1988) SQ1 r I try to experiment with new ideas irrespective of their outcome or the type of benefits they produce. (R) (Kahneman et al., 1991) SQ3 I always stick to the existing conditions even when a change would 2. Recency (Fudenberg et al., 2013 (Roberts et al., 2005) Cons3 I lead a highly disciplined life and maintain a rigorous daily routine. ...
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