This document summarizes a research study on herding behavior of investors in the Pakistan stock market. The study examines how factors like information, overconfidence, market sentiments, experience, and national culture influence herding behavior. The literature review discusses theories of herding behavior and relevant past studies. The research methodology section outlines the study's design, including a sample of 384 investors, data collection via online questionnaires, and analysis using PLS-SEM. The results found that information, market sentiments, experience, and national culture have a significant positive relationship with herding behavior. However, overconfidence did not have a significant influence. The study provides insight into factors that affect herding behavior of investors in Pakistan's stock market.

1. Herding Behavior of
Investor in Pakistan
Stock Market
Mohammad Ali Jinnah University
1
Presented by: Ismat Mohiuddin
(SP20-MSMG-0022)

2. INTRODUCTION
2
Traditional finance scholars make their investment decision on the
ground rules of traditional finance theories that assume individual
investors behave with perfect rationality. In other words traditional
finance assumes that people are not affected by biases or emotions
and developed its models based on this assumption. According to
the traditional finance, a rational investor always tries to maximize
his utility or return from his investment for a given level of risk.
Behavioral finance is an area of study focused on how
psychological influences can affect market outcomes.
Herding: Herding behavior can be defined as the tendency that a
group of investors follow the actions of the others and ignore their
own belief and information which makes prices to deviate from
their fundamentals.

3. PROBLEM STATEMENT
Behavioral finance is the rapidly evolving field in finance, therefore it
has a huge grey area to explore more, herding is one of the key term in
the behavioral finance on which several researches has been conducted,
few empirical studies have been focused on variables of herding
behavior among investors in the context of Pakistan (Ahmed et al.,
2019; Javaira & Hassan, 2017; Kiran et al., 2020) hence the Pakistan
Stock Exchange is classified as the emerging stock market in Asia, as
the market is mainly denominated by the key players so the movement
of these large players have a significant impact on the rest of the
investor which surely gives a certain possibility for investor herding in
the stock market, and to study this herding phenomenon has always
been a big challenge for the research, so the crux of this article is to
resolve this puzzle and have some significant contribution.
3

4. Research Questions
4
Does overconfidence effect herding behavior among investors in PSX?
Does information effect herding behavior among Investors in PSX?
Does market sentiment effect herding behavior among investors in PSX?
Does experience effect herding behavior among investors in PSX?
Does national culture effect herd behavior among investors in PSX?

5. Research Objectives
5
To examine the influence of overconfidence on herding behavior of investors in
PSX.
To examine the influence of information on herding behavior of investors in PSX.
To examine the influence of market sentiment on herding behavior of investors
in PSX.
To examine the influence of experience on herding behavior of investors in PSX.
To examine the influence of national culture on herding behavior of investors in
PSX.

6. Literature Review
6
Prospect theory
(Kahneman & Tversky, 1979)
Prospect theory is a behavioral model that shows how individuals decide Investment
choices that contain risk and uncertainty. Prospect theory was developed
by Framing risky choices and indicates that people are Loss-Averse; since individuals
dislike losses more than equivalent gains, they are more willing to take risks to avoid a
loss.
Information cascade
theory
(Bikhchandani & Sharma, 2001)
Information cascade theory (Bikhchandani & Sharma, 2001) found that the gaps in the
information hold by each investor will reason herding behavior. This known as
information cascade, where investors examine other investor’s practices, used it as their
own investment choice and negligence their own information.
Better-than-average-effect
Alicke, M. D., & Govorun, O. (2005)
The better-than-average effect Refers to a social judgement that individuals accept that
their capacities and abilities better than others. An investor may show overconfidence
refuse to follow the stock market trend and believes that he can make best investment
decision. Because of Success in past investment, an investor may ignore significant
data or other’s opinions and only based on their data and experience.

7. Literature Review
7
Information Information is divided into Three parts
1.Source of Information
(Nair et al.,
2017)
Study results Revealed that there is a positive relationship between herd behavior and source
of information by using the OLS analysis. They recommend that investors are having a
higher propensity in showing herd behavior when they acquire relevant data through verbal
Communication in comparison with other sources of information.
2.Information Uncertainty
(Dr.
Taqadus
Bashir et
al., 2014)
Found a positive relationship between information and herding behavior among investors.
Based on the ANOVA and logistic regression (LOGIT) result, they point out that when the
information uncertainty decreases, the herding phenomenon starts to decrease in the market
as well.
3.Information Asymmetry
(Ramli et al.,
2016)
Examine Information asymmetry effect on herding behavior in Indonesian Capital Market
(IDX) by using VEC Model found that significant influence of Information asymmetry on
herding.)
Overconfidence
(Adielyani &
Mawardi,
2020)
Examine the impact of overconfidence, herd behavior, and risk tolerance to the stock
investment choices. Collected data from 98 respondents was taken using purposive sampling
technique. The information gathered through web-based questionnaire. The technique for
information examines used multiple linier regression with the help of (SPSS) version 22. The
outcomes showed that the overconfidence, herding behavior, and risk tolerance showed a
positive and significant impact on stock investment choices of millennial investors in
Semarang city.

8. Literature Review
8
Market
Sentiment
(K. H. Choi
& Yoon,
2020)
Examine the association between herding behavior and investor sentiment, study analyzes the
KOSPI and KOSDAQ Collected Data from Informax between January 2003 and December
2018 Results Reveled that investor sentiment is confirmed to be one of the significant
components that can cause herding behavior in the Korean securities exchange Stock market.
Experience
(Risal &
Khatiwada,
2019)
Examine the attitudinal variables affecting herding behavior to deal with the changes, bubbles,
and bursts in the Nepali capital market. Data collected from 407 responses. Regression
analysis have been done to analyze the data. The outcome from the Study revealed the
significant relationship of hasty decision with herd behavior. This may be as a result of
inexperience.
National
culture
(Blasco et al.,
2017)
Examine whether herding is linked to a group of variables associated with cultural,
institutional, financial, economic, educational and technological factors that are likely to affect
investors’ behavior and decisions and found that masculinity and individualism have
significant negative impact on herding behavior of investor whereas uncertainty avoidance ,
Power distance, long-term orientation and indulgence are insignificant.

9. Conceptual Framework
9

10. ALTERNATIVE HYPOTHESIS
𝑯𝟏: There is a significant effect of information on herding of investors in Pakistan stock market.
𝑯𝟐: There is a significant effect of Overconfidence on herding behavior of investors in Pakistan stock market.
𝑯𝟑: There is a significant effect of Market sentiments on herding behavior of investors in Pakistan stock market.
𝑯𝟒: There is a significant effect of Experiences on herding behavior of investors in Pakistan stock market.
𝑯𝟓: There is a significant effect of National cultures on herding behavior of investors in Pakistan stock market.
10

11. 11
Research Methodology
Target Population
Type of Research
Sample Size
Research Design
Data Collection
Data Analysis
Descriptive & Correlational Research (Stangor & Walinga, 2014)
384 (Krejcie & Morgan 1970)
Total Number of investors in PSX
Quantitative research
Primary Data Collection Through
Online Google Forms.
PLS -SEM
Questionnaire
Adapted from
Hui, C. L., Yew, C. L., Chong, F. Z., Lin, J. K. S., & Han, S. Z. (2018).

12. 12 Path Model Results with Algorithm

13. Results
Cronbac
h's
Alpha
rho_A
Composite
Reliability
Average
Variance
Extracted
(AVE)
EXP 0.738 0.810 0.801 0.450
HB 0.795 0.795 0.859 0.550
INF 0.771 0.790 0.835 0.423
MS 0.840 0.851 0.887 0.611
NC 0.725 0.731 0.811 0.417
OC 0.818 1.250 0.837 0.511
13
Discriminant Validity(Fornell-Larcker Criterion)
EXP HB INF MS NC OC
EXP 0.671
HB 0.549 0.742
INF 0.505 0.621 0.651
MS 0.428 0.681 0.630 0.782
NC 0.571 0.673 0.614 0.649 0.676
OC 0.488 0.241 0.323 0.269 0.353 0.715
Construct Reliability and Validity
Internal consistency: Composite reliability (CR) should be higher than 0.70
Indicator reliability: The indicator's outer loadings should be higher than 0.5 (J. F. Hair et
al., 2011)
Convergent validity: The AVE should be higher than 0.50 In some cases less than 0.50 is
also acceptable
Discriminant validity: Square Root of AVE> inter-construct Correlation. (Fornell Larcker
criterion)

14. Results
EXP HB INF MS NC OC
Experience (EXP)
Herding Behavior (HB) 0.575
Information (INF) 0.553 0.765
Market Sentiments(MS) 0.436 0.826 0.768
National culture (NC) 0.720 0.853 0.790 0.842
Overconfidence(OC) 0.716 0.211 0.318 0.272 0.420
HB(VIF) HB (f2 )
EXP 1.797 0.072
HB
INF 1.968 0.042
MS 2.147 0.128
NC 2.378 0.063
OC 1.332 0.020
14
HTMT Ratio Collinearity Statistics (VIF) & F Square
HTMT Ratio should be less than 0.85 (Kline, 2011)
VIF Value should be less than 3
f2: >=0.02 is small; >= 0.15 is medium;>= 0.35 is large.(Cohen, 1977)

15. 15
Beta-
Coefficient
T Statistics P Values
EXP -> HB 0.226 4.743 0.000 Accepted
INF -> HB 0.181 4.051 0.000 Accepted
MS -> HB 0.331 8.048 0.000 Accepted
NC -> HB 0.244 5.175 0.000 Accepted
OC -> HB -0.103 1.821 0.069 Rejected
R2
Adjuste
d R2
Q² (=1-SSE/SSO)
Herding Behavior 0.602 0.597 0.322
Results
The structural model results show
that all variable has significant
positive relationship with
behavior Except Over confidence.
R2 =It represents the proportion of
the variance for a dependent
variable that's explained by an
independent variable.
Q²=Model has predictive relevance
for this model

16. 16
CONCLUSION, DISCUSSION & RECOMMENDATION FOR
FUTURE RESEARCH
Over time, an increasing number of investors in the stock market. Despite this, investors are hesitant to put
their money into an uncertain business area. Herd mentality is seen as a human intuition that occurs
frequently in humans while making decisions. So the main objective of this study is to find out the factors
that effect on investor and create herding. To achieve the objective taken information, overconfidence, market
sentiments, national culture and experience as independent variable and herding behavior as dependent
variable.
Data collected through questionnaire by using simple random sampling technique. PLS-SEM software is used
for data collection and results illustrates that information, market sentiment ,national culture and experience
have significant impact on herding behavior.
• Information: Result is supported by prior researches of (Komalasari, 2016; Nair et al., 2017; Ngai et al.,
2017; Ramli et al., 2016)
• Market sentiments: The result also supported by (Aharon, 2020; Berisha & Pavlovska, 2015; K. H. Choi
& Yoon, 2020; Economou et al., 2018; Huang & Wang, 2017; Humayun Kabir & Shakur, 2018; Jlassi
& Naoui, 2015; Litimi, 2017; Tauseef, 2020).
• Experience Results also consistent with the study of (Sabir et al., 2019) they also found that past
experience has a positive effect on herding in PSX. On the other hand, it is contradict from the study of
(Nguyen & Schuessler, 2012)

17. 17
• Overconfidence This results is consistent with (Gul & Khan, 2019), they found that
overconfidence has insignificant association with herd behavior in Pakistan stock market.
Results are contradict with the study of (Adielyani & Mawardi, 2020).
• National culture This results is similar with the past studies of (Asta Vasiliauskaitė, 2017;
Blasco et al., 2017; Lobão & Maio, 2019; Munkh-Ulzii, Moslehpour, et al., 2018).
Recommendations for future study:
• This study only focus in four types of cultural dimensions, future study also advised to use
more dimensions of culture.
• Future studies are suggested to use different techniques of research for collection of data
except questionnaire, e.g., individual meeting, phone and mail survey.
• Future studies are suggested to conduct this research on different types of investors like
institutional or retail investors and a comparative study can be conducted between developed
and developing countries.
• This study is only focused on primary data so future studies can also be conducted on both
primary and secondary data.

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