Psychological Factors Affecting Investors Decision Making

Psychological Factors Affecting Investors Decision Making

Christy Dominic#1, Dr. Ambuj Gupta*2

CHRIST (Deemed to be University), India

Abstract—A study was conducted to investigate the psychological variables affecting investment decision

making. The main objective of this article is to explore the psychological variables or biases which determine the

investment decision making. Furthermore, this paper also investigates the influence of Anchoring, Gamblers

Fallacy, Herd Behaviour and Overconfidence on investment decision making. The results of this study would help

financial advisors to understand which psychological factors they should concentrate on to improve their service

with clients. This would also help individual investors in understanding which all psychological factors influence

the investment decision the most and how to avoid them for making better decision. Data was collected using

survey, responses were collected through judgement sampling. Correlation and Regression are used to test the

hypotheses and conceptual framework. The results deduced that all four psychological factors are significant to

investment decision making. The results demonstrate that having good amount of Overconfidence in a investor

will make him Risk Seeker and also having least amount of Overconfidence will make him Risk Averse. It was

followed by Anchoring, Gamblers Fallacy and Herd Behaviour accordingly. Therefore, by mitigating

Overconfidence Bias in investors can certainly influence investment decision. Financial advisors will understand

the high importance of psychological factors and will understand their clients better which will help them in

providing better services to their clients. The limitation of this study is that it only talks about four biases but there

several more biases which could influence investors decision making.

Keywords— Overconfidence, Anchoring, Gamblers Fallacy, Herd Behaviour, Risk Averse, Risk Seeker

I. INTRODUCTION

Nowadays, investing in financial markets is becoming part of life as financial literacy among

individual investors have improved and technology involved in in this process has also seen a

drastic improvement. Investment decisions must be taken on the basis of its company data and

analysis to ascertain its financial position in the future, however sometimes it is made, not out

of logic but according to the current news or mood. (Chhapra, Kashif, Rehan, & Bai, 2018) .

This paper explores the impact of psychological factors such as Overconfidence, Anchoring,

Gamblers Fallacy and Herd Behaviour on decision making of an investor. The paper

thoroughly focuses on the various claims of researchers for the need to recognize the

psychological biases faced by investors and also to circumvent these psychological biases

while making investment decision. In this regard, the paper can provide guidelines for the

financial advisors and also the investors to understand the importance of these psychological

factors in decision making. It can also be helpful to improve the customer service provided by

the financial advisors by making them understand where customers want them to focus. In

behavioural finance, emotions and feelings of the investor while making investment decision

are studied so as to ascertain the influence of these psychological factors on investment

decision making process. Researchers are trying hard to study the behaviour of the investors

but individual investors are trying to know about their behaviour because of herding behaviour

which plays an important role which can dominate other reasons. Urge of individual investors

to follow the pattern followed by others, lead to herding behaviour (PrechterJr, 2001).

(Muhammad, 2009) According to economic researchers, investors are assumed to be rational

while deciding on buying or selling of stocks. Making use of all information available about

the future of the company as well as general market trends in the economy is an expectation

Journal of Xi'an University of Architecture & Technology

Volume XII, Issue IV, 2020

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from a rational investor. Also it is assumed that stock prices will stick to fundamental values

and will not change unless there is an unforeseen change in the news in the market. Therefore,

these researchers have ended up saying that economy taken as a whole tends towards “general

equilibrium” and financial markets are well balanced. In reality however, according to

researchers, investors fail to follow rationality and behave irrationally by giving weightage to

certain psychological biases. To be more specific, investors becomes victims of their emotion

and the unpredictability of the crowd, as a result stock prices goes above or below intrinsic

value of the company because they make certain irrational expectation on performance of the

company (Shiller, 1999). Some investors tends to make decision based on their feelings rather

than the doing proper fundamental analysis of the company. According to (Markowitz, 1952),

investors are risk averse and tend to be rational as they take risk according to return they are

getting. But in reality, Investors take many decision which are irrational such as buying stocks

due to intuition and not fundamental value, making investment decisions according to the

crowd and make decisions based on past performance not by future predictable data.

A. Research Questions

1. Are these psychological factors influencing investment decision making?

2. What are the various aspects of investment decisions?

3. How to make a better investment decision according to the study?

B. Objectives

To highlight influence of different Psychological biases on the investment decision

making.

C. Scope of the Study

Behavioural finance is a mixture of knowledge psychology, economics and finance.

This study could be helpful for financial advisors to provide better service to their clients and

investors to understand the various behavioural biases which could help them in identifying

the behavioural biases they inherit and to avoid it to make better investment decision.

Therefore, it is important to analyse these psychological biases and find out the factors which

are influencing the investment decision.

II. LITERATURE REVIEW

Anchoring

“Anchoring is a cognitive heuristic in which decisions are made based on an initial anchor.

The concept of anchoring heuristic can be thought as the tendency to make estimates and

decisions on a known reference point, even though it may have no logical relevance at

forehand and then to adjust it insufficiently to reach a final conclusion with relative to this start

point, possibly an arbitrary value. For example if you have to judge another person´s wealth,

the anchor for your judgment may probably be your own wealth level. This shows us people

who have to make judgments under uncertainty tend to use relative thinking instead of absolute

or critical thinking.” (Fici, 2014)



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A research (Ngoc, 2014), was undertaken at Securities’ Companies in Vietnam to investigate

the various behavioural factors which had an effect on the decisions taken by individual

investors. The author took a survey and 188 individual investors responded. In this study five

behavioural factors of individual investors are taken into consideration. They are “Herding,

Market, Prospect, Overconfidence-gamble’s fallacy, and Anchoring-ability bias.” The author

recommended to investors that they should be careful before making any investments but any

prior loss should not hinder them from investing later.

(Le Phuoc Luong & Doan Thi Thu Ha , 2011) Conducted a study on the individual investors

investing/trading in Ho Chi Minh Stock Exchange to explore the behavioural factors which

were influencing their decisions. They also analysed the relationship between the investments’

performance and these behavioural factors. The hypotheses were made on the basis of the

already existing theories related to behavioural factors. Questionnaires were used to collect

data and the responses were analysed via SPSS and AMOS. Some semi-structured interviews

were also conducted with some of the managers of the Exchange so that the authors could

understand these behaviours better. The results of the study showed that five behavioural

factors had an effect on individual investors’ of the Exchange. These factors are “Herding,

Market, Prospect, Overconfidence-gamble’s fallacy, and Anchoring-ability bias.” The market

factor has more significance than other factors in the study.

A study (Fici, 2014), was conducted to explore the behavioural biases in investment decisions.

The aim of this thesis was to find out the dependency between five identified behavioural biases

and individual investors. The behavioural biases that were examined are anchoring, herding

behaviour, overconfidence and hindsight bias and gambler fallacy. A 27 question questionnaire

was prepared as survey method. The survey was filled by 104 participants. Participants were

finance professionals and individual investors. As a statistical method, Pearson Chi-Square test

was used to conclude if hypothesis are approved or rejected.

Gamblers Fallacy

“The gambler's fallacy also known as the Monte Carlo fallacy is inaccurate understanding of

probability that an individual assumes a certain random event is less likely to occur following

a series of events. This assumption that what occurs on average will be corrected in the short

term is incorrect because past series of events do not change the certain fixed probability. For

example, after serious of 10 coin tosses that have landed heads-up, it is very tempting for a

person to expect the next coin more likely toss to land tails-up. But the probability of a fair

coin to land tails up is always 50 percent and is statistically independent and all previous coin

tosses has no effect on future outcomes of the next coin toss.” (Fici, 2014)

(Boda & Dr. G., 2018), Examined the linkage between investor’s psychology and investment

decision making. This article uses a historical perspective to report the various factors which

affect the psychology and financial decisions made by individual investors. This study focuses

on the rationality of the investor to understand the psychology behind the investment decision

by explaining psychological and emotional factors that affect investing. Description,

comparison, several methods of analysis and synthesis were used to study the psychology of

investors. Graphical visualization was used to reveal the results. The results showed that while

predicting the market movements, the investors’ moods and sentiments cannot be ignored.



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(Muhammad & Muhammad , 2018), conducted a study to explore the behavioural factors

which have an effect on the individual investors who are investing in the Lahore Stock

Exchange. A questionnaire which was structured and close-ended was used to conduct the

research. Two statistical techniques were used to analyse the responses. Exploratory factor

analysis was used to understand which factors had the most influence on the investment

decisions. Discriminant Analysis was used to identify the nature of the relationship shared

between independent and dependent variables.

(Dr. Isidore & Dr. P., 2018) Reviewed five behavioural biases which were shown by the

investors who were investing in the equity market. The behavioural biases were

“representativeness, anchoring, gambler’s fallacy, availability and optimism.” The authors

wrote about the effect these biases had on the investment decisions and that investors should

ensure that they are not affected by these biases while making decisions.

Herd Behaviour

“Herding behaviour can be described as tendency for individuals to act together in periods of

bubbles or crashes.” (Fici, 2014)

A study was undertaken on individual investors of equity markets to understand how these

factors, “Awareness, Demographic Factors and Perceived Risk Attitude” affected investment

behaviour (Sarkar & Dr. Sahu , 2018). A structured questionnaire was used to collect responses

from 400 individual investors which were randomly selected. The study showed that financial

awareness is more than social learning and there was only a moderate level of awareness among

the individual investors. This study also showed that the three factors- “Awareness,

Demographic Factors and Perceived Risk Attitude” had a significant relationship with the

investment behaviour of individual investors.

(YASER ALMANSOUR & AHMAD ARABYAT , 2017) Conducted research that

investigated the effect of psychological factors on risk-taking behaviour in investment

decisions. Psychological factors considered in this research are herding, heuristics, prospect,

market, self-attribution bias, and familiarity bias, in making investment decisions. The findings

in this paper indicate that all the factors except familiarity bias have a significant impact on

investment decisions.

(Mrs. S.Devi & Dr. Karthikeyan, 2018) Made an attempt to study investor’s perception

towards behavioural finance while taking investment decisions. The authors analysed the data

for Investors’ behaviour with the help of 600 respondents using a Factor analysis test. Using

the principle component analysis, the results showed that the 16 variables selected for the study

had been reduced to 5-factor models such as Regret Aversion, Market Dynamics, Logical

Analysis, Herding Bias, and Heuristic Bias. Since behavioural finance influences investors’

behaviour greatly, it is becoming a primary part of the decision-making process.

Overconfidence

“Evidence shows that people tend to be overconfident in their decisions and may overestimate

their ability to know what will happen. The belief of being more knowledgeable than they

actually are, causes investors to believe that diversification of financial portfolios is



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unnecessary. Overconfidence bias is a frequent trait and investors suffer from reduced returns,

through shortcomings of their decisions.” (Fici, 2014)

(Chhapra, Kashif, Rehan, & Bai, 2018) Undertook a study in order to find a linkage between

investors’ behavioural biases and financial decision making. The study analysed the role of

behavioural biases in investment and/or financial decisions taken by investors trading in

Pakistan Stock Exchange. Data was collected using a survey questionnaire and 250 responses

were collected by using convenience sampling technique. Behavioural biases used in the study

are “overconfidence, overthinking, herding, cognitive bias, and hindsight effect of investors.”

The impact of these behavioural biases were tested using multiple regression models. The

results indicate that investment decisions are significantly impacted by the five biases.

Mouna & Anis analysed the effect of sentiments on their investment decisions taken by small

investors (MOUNA & ANIS, 2014). This was done by examining their portfolio returns.

Logistic Regression Analysis was used to examine the relationship. 178 small investors who

were trading on Tunisian stock market were selected and were given a questionnaire. The

results showed that behavioural biases have a significant influence on the portfolio returns of

the small investors. The results also showed that “anchoring, familiarity, age, and experience”

play an important role in portfolio performance. Thus, the authors recommended that investors

should take decisions according to their financial capabilities and experience rather than

sentiments.

(Chu, Im, & Jang, 2012) Conducted a study to determine the disposition effect in customer

investment behaviour due to overconfidence. The study examines the relationship between

overconfidence and investment behaviour. The study shows that investors who are

overconfident usually trade in large volumes and also show a stronger disposition effect. A

mock stock experiment was used to evaluate the hypotheses. The participants of the study

included 68 students of South Korean University and 93 office workers as well. The results

showed that overconfident individuals had an illusion of control. This means that the

overconfident individuals held a belief that they could control the movement of the stocks.

Risk Appetite

(Riaz, Hunjra , & Rauf-i-Azam, 2012) Investigated the impact of “risk propensity, asymmetric

information and problem framing” on investor’s behaviour. They developed a study model to

determine the significance of each variable on investment decisions. The results of the model

showed that presentation of available information and risk propensity has an effect on

investment behaviour.

(K. & Dr.M., 2015) Conducted a study in Coimbatore to analyse the investment behaviour of

investors in the various investment avenues in Indian financial markets. The major factors

behind an investment are – “safety of the principal amount, liquidity, income stability, and

appreciation.” Investors usually prefer to invest their money in “safe” investments to attain a

moderate profit. The conclusion of this study was that investors in Coimbatore preferred to

keep their money as bank deposits which was followed by investing in gold and silver.

(Abul, 2019) Investigated the investment behaviour in Kuwait Stock Exchange (KSE). The

psychological factors he investigated were – “excessive optimism vs pessimism, herd



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behaviour, and risk appetite.” He took a survey of 398 investors which were selected at

random and other relevant data was provided by KSE. The responses were analysed using

qualitative analysis. The study’s findings indicate that the individual investors’ decisions

have a significant impact from herd behaviour, optimism and psychology risk.

III. RESEARCH METHODOLOGY

The main objective of the research is to determine the psychological biases affecting investor’s

behaviour. The methodology has reviewed the outlined procedures and methods used to gather

data and data analysis that was utilized in the study. This study is a descriptive research design,

which is having four types of variables that affect Investors Behaviour. Those four variables:

(a) Overconfidence (b) Herd Behaviour (c) Gamblers Fallacy (d) Anchoring.

The participants were investors who actively trades in the market. The sampling technique

which was used was the Judgement Sampling technique. The questionnaire which was used

had a 5-point Likert scale so that respondents can accurately fill the questionnaire. This will

make it easy to identify which factor is more dominant and which is not. The primary data for

the research were collected with the help of a questionnaire. The survey had two parts. The

first part was designed to gather information about the psychological factors and the second

part was designed for the investor behaviour assessment. The participants were contacted via

email to ask for their participation in the study. If they choose to participate, they were given a

link to access Google form survey application to begin the assessment. The survey provided an

explanation of why the study was being conducted and along with thorough instructions to

complete the instrument. In addition, an assurance that their participation was confidential and

no individual data would be shared or reported.

IV DATA ANALYSIS

The table 1 indicates the demographic characteristics of the participants. It can be observed

that the study consists of 57% Males and 43% Females. Regarding the age of the respondents,

53.7% of them belongs to age group of (20-35) years, 27.3% belongs to age group of (36-45)

years and 19% belongs to the age group of 46 years and above. With reference to the

qualification of the respondents, 1.7% of them have UG qualification, 70.2% have pursued a

PG degree and 28.1% have done other courses.

TABLE I: DEMOGRAPHIC INFORMATION OF RESPONDENTS

SL.no. Classification Categories Frequencies Percent

1

Gender

Male 69 57

Female 52 43

Total 121 100

2

Age

20 - 35 Years 65 53.7

36 - 45 Years 33 27.3

46 and Above 23 19



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Total 121 100

3

Qualification

UG 2 1.7

PG 85 70.2

Other 34 28.1

Total 121 100

4

Annual Income

Less than 3 lakhs 65 53.7

5 lakhs to 7 lakhs 20 16.5

More than 7 lakhs 36 29.8

Total 121 100

5

Marital Status

Married 59 48.8

Unmarried 62 51.2

Total 121 100

It can also be observed that the annual income of 53.7% of the respondents are less than Rs.3

Lakhs. 16.5% have an annual income within the range of Rs.5 Lakhs to Rs.7 Lakhs and

29.8% have an annual income greater than Rs.7 Lakhs. The marital status of the participants

indicate that 59% are of them are married and 62% are Unmarried.

TABLE 2: RELIABILITY ANALYSIS

SI.

No.

Variables Cronbach’s Alpha Percentage

1 Anchoring .707

2 Gamblers Fallacy .631

3 Herd Behaviour .774

4 Overconfidence .726

To have an acceptable degree of consistency Cronbach’s Alpha should be greater than 0.7 .

From the above Reliability Analysis table 2 it can be observed that the Cronbach’s Alpha the

factors pertaining to factors are 0.707 (Anchoring), 0.631 (Gamblers Fallacy), 0.774 (Herd

Behaviour) and 0.726 (Overconfidence). Most of the variables are having Cronbach’s Alpha

scores of more than 0.7. Hence, the variables have good internal consistency.



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TABLE 3: FACTOR ANALYSIS

SL. No. Variables KMO Value

1 Anchoring 0.781

2 Gamblers Fallacy 0.645

3 Herd Behaviour 0.962

4 Overconfidence 0.753

5 Risk Averse 0.721

6 Risk Seeker 0.746

From the above Factor Analysis Table 3, the accepted KMO value is .7 and higher. Since a

high KMO value shows that the sampling is adequate. The KMO value of Anchoring is .781,

Gamblers Fallacy is .645, Herd Behaviour is .962, Overconfidence is .753, Risk Averse is

.721 and Risk Seeker is .746. Since KMO values of most of the variables are higher than .7,

the sampling is adequate.

TABLE 4: REGRESSION ANALYSIS

Model R R Square Adjusted R Square Std. Error of the

Estimate

1 .636a .404 .383 .38290

From the above Regression Analysis table 4, it can be concluded that that R value is 63.6%,

R Square value is 40.4%, and Adjusted R Square value is 38.3%. Therefore, it is apparent

that 40.4% of Risk Averse is contributed by Anchoring, Gamblers Fallacy, Herd Behaviour

and Overconfidence. The influence of Factors on Risk Averse is measured using Karl

Pearson’s Correlation Coefficient. The hypotheses developed in this regard are:

H1 Anchoring have an influence on Risk Averse.

H2 Gamblers Fallacy have an influence on Risk Averse.

H3 Herd Behaviour have an influence on Risk Averse.

H4 Overconfidence have an influence on Risk Averse.



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TABLE 5: REGRESSION ANALYSIS

Model R R Square Adjusted R Square Std. Error of the

Estimate

1 .669a .447 .428 .55159

From the above Regression Analysis table 5, it can be inferred that that R value is 66.9%, R

Square value is 44.7%, and Adjusted R Square value is 42.8%. Therefore, it is apparent that

44.7% of Risk Seeker is contributed by Anchoring, Gamblers Fallacy, Herd Behaviour and

Overconfidence. The influence of factors on Risk Seeker is measured using Karl Pearson’s

Correlation Coefficient. The hypotheses developed in this regard are:

H5 Anchoring have an influence on Risk Seeker.

H6 Gamblers Fallacy have an influence on Risk Seeker.

H7 Herd Behaviour have an influence on Risk Seeker.

H8 Overconfidence have an influence on Risk Seeker .



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TABLE 6: CORRELATION

From the above correlation table, it can be inferred that Overconfidence is having most

influence on with Risk Seeker. Furthermore, it can also be observed that maximum degree of

correlation is witnessed between Risk Seeker and Overconfidence at 54.5% followed by

Anchoring at 32.5%, Gamblers Fallacy at 18% and Herd Behaviour at 11.4%. Therefore, the

Correlation Herd

Behaviour

Overconfidence Anchoring Gamblers

Fallacy

Risk

Averse

Risk Seeker

Herd Behaviour Pearson

Correlations 1 -.166 -.085 .167 -.148 .114

Sig. (2-tailed) .069 .355 .068 .106 .214

N 121 121 121 121 121 121

Overconfidence Pearson

Correlations -.166 1 .092 .290** -.497** .545**

Sig. (2-tailed) .069

.315 .001 .000 .000

N 121 121 121 121 121 121

Anchoring Pearson

Correlations -.085 .092 1 .370** -.343** .325**

Sig. (2-tailed) .355 .315

.000 .000 .000

N 121 121 121 121 121 121

Gamblers Fallacy Pearson

Correlations .167 .290** .370** 1 -.269** .180*

Sig. (2-tailed) .068 .001 .000

.003 .048

N 121 121 121 121 121 121

Risk Averse Pearson

Correlations -.148 -.497** -.343** -.269** 1 -.607**

Sig. (2-tailed) .106 .000 .000 .003

.000

N 121 121 121 121 121 121

Risk Seeker Pearson

Correlations .114 .545** .325** .180* -.607** 1

Sig. (2-tailed) .214 .000 .000 .048 .000

N 121 121 121 121 121 121



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hypotheses H1, H2, H3 and H4 are accepted. Also, it can also be observed that maximum

degree of negative correlation is witnessed between Risk Averse and Overconfidence at -

49.7% followed by Anchoring at -34.3%, Gamblers Fallacy at -26.9% and Herd Behaviour at

-14.8%. Therefore, the hypotheses H5, H6, H7 and H8 are accepted.

Fig. 1. Conceptual Framework

From Fig.1, we can see the psychological factors affecting Investment Decision.

V. CONCLUSION

1) Discussion

The present study makes us understand the relationship between psychological factors

(Anchoring, Gamblers Fallacy, Herd Behaviour and Overconfidence) and Investment

Decision. Careful attention to psychological factors such as Anchoring, Gamblers Fallacy,

Herd Behaviour and Overconfidence can lead to better Investment Decisions. The findings

suggest that all the psychological factors has a direct effect on Risk Seeker and indirect effect

on Risk Averse. The results demonstrate that investor having good amount of Overconfidence

in a investor will make him Risk Seeker and also having least amount of Overconfidence will

make him Risk Averse followed by Anchoring, Gamblers Fallacy and Herd Behaviour

accordingly. Therefore, by avoiding overconfidence can certainly lead to better investment

decision.

2) Suggestions

Mistakes are common among investors and they make it time and time again. Rectification

of this mistakes can be done with the use of behavioural finance. Others might not realize

that they use limited knowledge for making investment decision. When the awareness is

spread among them then they will identify the biases they have and will take steps to fix it.

Using technical analysis will help in making better investments as it uses charts and graphs

to predict future price movements. With the help of these charts we can identify certain

investing patterns which can be analysed and be used for future predictions. Overconfidence

can be avoided by understanding the fact that financial markets are highly dynamic. Even

best of financial advisors with access to the best predictive models, underperform at times.

Therefore, sticking to reality is always very important. Also keeping track of one’s

performance and also looking back at the mistakes will make a overconfident investor realize

that he does not know everything and can make a mistake at times. To avoid anchoring bias



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the investors must make decisions according to the logic and not getting stuck on one price

or a past event. Fundamental analysis of the company should be made use of while making

decision of buying shares of that company and not the historical prices. Gamblers Fallacy

can be avoided by focusing more on data which can predict future and not worrying about the

past events. Investors must understand that financial markets are not Casinos. Therefore,

investment decisions should be based on logic and analytics. We can avoid Herd Behaviour

by being aware that herd investment are based on fears of other people and this will make

you more resistant to herd behaviour. Investors must take decisions based on the

fundamentals and not according to people. Before planning to invest into certain investment,

you must do research and do fundamental analysis and not follow the crowd if they are going

against the fundamentals.

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Psychological Factors Affecting Investors Decision Making