Behavioural Factors Effect on Investors' Investment Performance:
A Survey from the Nigerian Capital Market
BEKWERI MARK EDEH, UMAR ABBAS IBRAHIM, FAIZA MAITALA,
CROSS OGOHI DANIEL
Department of Business Administration,
Nile University of Nigeria,
Cadastral Zone C-OO, Research & Institution Area, Airport Rd, Jabi 900001, Abuja,
NIGERIA
Abstract: - Behavioural finance theory posited that the actions of individual investors have demonstrated that
people appear to respond to and perceive the same information differently, generating psychological biases that
are defined as Behavioural Factors. It is against this backdrop that this study empirically examines the effect of
behavioural factors on investment performance. This study examines behavioural factors (Heuristics, Prospects,
Herding, and Market) that influence stock investors’ performance in Nigeria’s capital market. Three hundred
and eighty-four (384) respondents were sampled by an online survey method through a questionnaire from
active investors using the top ten brokerage firms in Nigeria. Data were examined and analyzed by STATA
software using the structural equation model technique (SEM) as the statistical tool. The data revealed a
considerable positive link between behavioural factors indicators and investment performance. The study,
therefore, recommends that NSE should continuously share information, and train the investors, which is
geared towards positively influencing investment decisions. Through this information, investors will be in a
position to make wise investment decisions. NSE should also evaluate the influences of prior events in relation
to the specific counter under investigation. More so the effect of the learning process should be clearly
evaluated to ensure that there is maximum benefit for all parties involved in selling and buying a security share.
Key-Words: - Behavioural factors; investment performance; Investment decision; Capital market
Received: June 24, 2022. Revised: November 5, 2022. Accepted: November 22, 2022. Available online: December 14, 2022.
1 Introduction
Behavioural finance is a field of study that analyses
how investors' illogical or emotional behaviour
affects stock prices, [1]. The power of behavioural
finance is made clear when it is seen that a
company's stock price fluctuates day by day even
though there hasn't been any change in the
fundamental elements of the business that should be
the cogent drivers. In a practical sense, investors
should concentrate on a firm's fundamental changes
to make their predictions, which will in turn affect
the stock price of that company. But the investors
prefer to use their behavioural, psychological, and
emotional elements when making decisions, [2].
However, the way in which these investors trade in
and out of a particular stock of a company causes
price fluctuations, which exposes the financial
system and the state of the economy to risk.
Investment is the acquisition of goods or assets with
the hope of future growth in income or value.
Investments carry larger risks than savings do, thus
the individual investor will want higher returns from
their investments, [3]. Investors have challenges in
making long-term financial decisions for reasons
such as lack of financial complexity, inability to
self-regulate, and lack of foresight. Individual
investors can use a team of investment professionals
under the direction of a portfolio or fund manager.
These individuals work full-time on studying the
markets, market trends, and individual stocks.
Understanding investors’ decision-making, requires
one to study the behavioural factors which influence
the decisions and performance of the investors.
These factors are heuristic factors; (that is,
representation, overconfidence, anchoring,
gambler’s fallacy, and availability bias); prospect
factors; (that is, level of mental stress and regret
aversion); herd factors; (that is, grazing and risk);
market factors; (that is, market prices, stock
preferences and changes in consumer reactions). It
is against these factors that the researcher intends to
carry out research on the influence of behavioural
factors on investment performance in the capital
market in Nigeria.
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2 Problem Formulation
Numerous psychological research has examined the
ways in which people consistently commit
behavioural thinking mistakes, including
overconfidence, placing too much emphasis on
recent experience, representativeness, availability
bias, gambler's fallacy, etc., [4]. This popularity
could lead to misrepresentation. The study of the
psychological and social factors that affect investing
performance is known as behavioural finance. The
number of businesses applying to list on the stock
exchange in Nigeria has significantly increased in
recent years. Investors on the other hand have
responded absolutely as it is demonstrated by
recurrent oversubscriptions for shares. However, a
lot of investors have had to deal with the agony of
losses as a result of overconfident behaviour and
following the crowd. In [5], [6], the authors
highlighted a clear lack of consensus among
financial researchers questioning the strength of
behavioural finance theory. This lack of agreement
shows that the idea of behavioural finance is still up
for discussion. However, in [7], the authors stated
explicitly that excess research has been undertaken
in the secondary markets; there is minimal evidence
of studies on the effect of behaviour determinants on
investment success with reference to Nigeria's
capital market.
2.1 Objectives of the Study
The major purpose of this research is to determine
the effect of behavioural factors on investment
performance in the capital market.
Other distinct goals are to:
Examine the effect of behavioural factors
(heuristic, prospect, herd, market) on the investors’
investment performance in Nigeria’s capital market.
a) Examine the mediating role of the investors’
age and type of investment with behavioural
factor on the investment performance in the
Nigerian capital market.
2.1.1 Conceptual Framework
1.0 Conceptual Framework
Independent Variables
Figure 2.2: Conceptual Model
Heuristic Factor
Overconfidence
Anchoring Bias
Availability Bias
Prospect Factors
Lost Aversion
Regret Aversion
Mental Accounting
Investment Performance
Age
Type of Investors
Market Factors
Prize Change
Customer
Performance
Market information
Moderating Variables
Dependent Variables
Fig. 1: Conceptual Model
Source: Researcher, 2021
2.2 Review of Related Literatures
This chapter explains the findings of various
researchers on investment performance. Behavioural
finance posits that an individual is irrational in his
thought process, [6]. Behavioural finance refers to
the application of psychology to finance. It can be
defined as the study of the effects of investors’
psychology and the financial market. Behavioural
factors have been pulling their weight in trying to
expatiate its importance as regards how an
investment can perform better. Behavioural factors
mean many different things to different people,
according to their professional backgrounds, [7].
Many people believe that these factors influence
decisions made by investors. There are four major
factors in behavioural finance these are Heuristics,
Prospects, Herd, and Market factors. These factors
help to explain the uncertainty in making choices
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when it comes to investment and the decisions the
individual investor has to make.
2.2.1 Heuristic Factors
“Heuristic explains how investors make decisions,
come to judgments and solve problems, typically
when facing complex problems or incomplete
information when making investment decisions in
the stock market. The heuristic bias sways investors
from reality to a place of oblivion (out of touch with
reality-the facts) where they are heedless and take
decisions by trial and error from which they develop
a “rule of thumb”.
Overconfidence is a behavioural factor where
investors overvalue or overrate their abilities, skills,
and acquired knowledge, on which they rely or
depend to make, ‘supposedly’ flawless investments
or financial decisions. In [8], author surmised that
overconfidence is believed to be a determining
factor for success for the investor.
An anchoring heuristic describes an anchoring
heuristic as a common human tendency to rely too
heavily on, or “anchor” on one trait or piece of
information when making decisions. It is also when
an investor tries to reduce risks or ambiguity with
some reference points and reaches a conclusion or a
decision through appropriate adjustment, [9]. When
presented with new information, the investor tends
to be slow to change because his value is fixed or
anchored on recent observations, [10].
2.2.2 Prospect Factor
The prospect factor suggests that a choice among
risky prospects is inconsistent. This factor expounds
that an investor value gains and losses differently. If
two equal choices are given to an investor, one in
terms of potential gains and the other in terms of
potential losses, the chances are that the investor
would choose the former i.e., where the gain is,
[11], and change in the value of stock leads an
investor to loss or risk aversion.
Loss Aversion is when investors are discrepant or
discordant towards risk. Loss-averse investors try to
maximize their wealth and achieve a maximum
level of utility and most of the time, investor
behavior negates the expected utility theory’s
premise, [12].
Regret Aversion is behavioural factor found
amongst investors when making an investment
decision when a prospect paints a picture of a profit
and loss. Investors exhibit regret aversion when they
make the wrong choice or make negative decisions
in stock trading, [13]. In aversion to regret investors
will ignore taking action or making any decisions if
they feel their decision may be wrong. Regret
Aversion is not only the feeling of the wrong action
but, sometimes investors feel regret for inaction (not
taking actions)
2.2.3 Herd Factor
This significant factor suggests that investors make
identical/similar investment decisions or selections
to one another, following a group of investors'
decisions mindlessly, or both. This is the most
common mistake where investors tend to follow the
investment decisions taken by the majority. That is
why, in financial markets, when the best time to buy
or sell is at hand, even the person who thinks he
should take action experiences a strong
psychological pressure refraining him because of
pressure from or influence by peer investors. When
an investor adheres to the herd, shutting down or
ignoring his or her reasoning and opinions as he or
she automatically imitates the behavior and
movement of the group in the stock exchanges, [14].
Investors tend to think that it is unlikely that a large
group could be wrong. This could make him follow
the herd under the illusion that the herd may know
something he does not.
2.2.4 Market Factor
Changes in market prices, stock preferences,
customer reactions, etc. all have an impact on
investor decisions. This may cause an investor to act
excessively or insufficiently in response to market
conditions. An investor's response and decision to
invest can be influenced by changes in fundamental
values, market knowledge, and pricing. Decisions
regarding market investments. In [15], the authors
likewise advised that investors must consider market
information to make rational decisions. Changes in
fundamental values, market price, and market
information can lead to the reaction of an investor
and his decisions to invest in the market.
2.2.5 Age and Investment Performance
Investment performance depends on various factors.
Those can be broadly categorized into economic
factors, political factors, social factors, and personal
factors. Personal factors indicate the demographic
features of investors. In [16], the author indicated
that the performance of investments of female
investors is higher than the performance of male
investors and older investors outperform younger
investors in both female and male groups.
2.2.6 Investment Type and Performance
Using data from Finland, this study analyzes the
extent to which past returns determine the
propensity to buy and sell, [17]. It also analyzes
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whether these differences in past-return-based
behavior and differences in investor sophistication
drive the performance of various investor types. We
find that foreign investors tend to be momentum
investors, buying past winning stocks and selling
past losers. Domestic investors, particularly
households, tend to be contrarians. The distinctions
in behavior are consistent across a variety of past-
return intervals.
2.3 Empirical Literature Review
2.3.1 Studies that found Mixed Results
Exact research identified with value choice
procedure in Malaysia directed by, [18],
demonstrated nonpartisan data had all the earmarks
of being the most significant factor the Malaysian
financial specialists, trailed by bookkeeping data,
social importance, and advocates‟ suggestions in the
value determination process. Nonpartisan data was
emphatically associated while bookkeeping data
was contrarily connected with anticipated return.
The investigation reasoned that the speculation
choice of speculators did not depend on a single
incorporated factor.
Studied herd behavior in a laboratory
financial market with financial market professionals,
[19]. The study combines the advantage of the
controlled experiment with that of observing the
behavior of professionals, who are engaged in the
day-by-day activity of trading, pricing, and
analyzing financial assets. This study compares two
treatments, one in which the price adjusts to the
order flow so that Herding should never occur, and
one in which event uncertainty makes Herding
possible. In the first treatment, subjects seldom, in
accordance with both the theory and previous
experimental evidence on student subjects. In the
second treatment, the proportion of Herding
decisions increases, but not as much as theory
suggests; moreover, contrarianism disappears
altogether.
Investigated the impact of behavioural factors on
individual investors' investment decisions and
performance in the Pakistani stock market, [20].
This research focuses on behavioural finance
theories that already exist. The study's data was
gathered through a questionnaire at the Pakistan
Stock Exchange. The findings confirmed that
behavioural factors such as heuristics, prospects,
markets, and herding all have a significant impact
on investors' decisions in Pakistani stock markets.
However, one limitation of the study is that it did
not look at specific indicators within each
behavioural factor dimension. In-depth research into
certain behavioural factor dimensions would
improve the knowledge of behavioural factors in
finance. As a result, the current study aims to look
into the impact of behavioural determinants on
investment decisions on the Nigerian stock
exchange.
2.3.2 Studies that found Positive Results
Some studies were found to have positive effects on
the impact of behavioural factors on the investor’s
investment performance. The authors in [21],
analyze how systematic differences in investors’
investment objectives and strategies affect the
portfolios they select and the returns they earn. The
analyses in this study draw on transaction records of
a sample of clients (65,325 individual accounts with
over nine million trades from January 2000 until
March 2006), from the largest online broker in The
Netherlands. The data were obtained through an
online questionnaire. The results might be useful for
policymakers. It is found that investors who rely on
fundamental analysis have higher aspirations and
turnover, take more risks, are more overconfident,
and outperform investors who rely on technical
analysis. Our findings provide support for the
behavioural approach to portfolio theory and shed
new light on the traditional approach to portfolio
theory.
In [22], the author surveyed the institutional
investors at the Nairobi Stock Exchange. The work
investigated the role of behavioural finance and
investor psychology in investment decision-making.
The study established that behavioural factors such
as Representativeness, Overconfidence, Anchoring,
Gamblers’ Fallacy, Availability, Loss Aversion,
Mental Accounting, and Regret Aversion affected
the decisions of institutional investors operating at
the Nairobi Stock Exchange.
In [23], the author conducted research to determine
the behavioural factors influencing the following
specific objectives: to determine the effect of risk
aversion on investment decisions in the Kenyan
stock market, to determine whether prospecting
influences decision-making in stock market
investments, to determine the effect of anchoring on
investment decisions in the Kenyan stock market,
and to determine the effect of herding on investment
decisions in the Kenyan stock market. The study's
target population consisted of 17 investment banks.
The majority of the data included in the study came
from primary sources.
2.3.3 Studies that found Negative Effects
Other studies were seen to have results based on the
effect of behavioural factors on investment
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decisions. The authors in [24], who did their study
on mental accounting and false reference points
discovered that this bias is present among investors
who rely much on a particular reference point,
particularly a false view? The false reference point
is particularly attributed to regret aversion. In [25],
the author argues that people who display this bias
are trapped with fear that the decision they make
towards an investment will not be optimal. The
authors in [26], examined the impact of behavioural
biases on the Nigerian stock exchange and
discovered that there was a negative correlation
between overconfidence and the stock exchange, as
the investors are fueled with overconfidence the
market underperforms. There was also a negative
relationship between the framing and the stock
market as investors prefer to make decisions
subjectively.
The authors in [27], aimed at studying the cognitive
biases and heuristics, to which, business students are
subjected to.
The main purpose of the study was to look at how
influenced the students are, by biases, heuristics,
and framing effects. The behavioural survey was
administered to a sample of sixty-eight students at
Jacksonville University in the USA during
November 2007 by administering a questionnaire
and collecting empirical evidence about both
undergraduate and graduate business students’ own
perceptions of bias. The findings concluded that
students are less disposed to make the mistake of
being overly confident and optimistic when there is
more objectivity involved in making the assessment.
Students did not display the illusion of control
tendencies and a tendency to be subject to the
familiarity heuristic.
In [28], the author studied the factors influencing
the investor's behavior on the UAE financial market,
the results show that the six most influencing factors
in order of importance were: expected corporate
earnings, get rich quick, stock marketability, past
performance of the firm's stock, government
holdings and the creation of the organized financial
markets and the least influencing factors to be
expected losses and minimizing risks.
3 Methodology
3.1 Data Collection and Sample
Representation
The research design that was adopted for this study
is the Cross-sectional survey method. According to,
[29], Cross-sectional designs are appropriate for
measuring such complexities of the pattern of
relationships that exists among measured variables.
A cross-sectional research design would be
preferred in this study because the design is capable
of looking at the relationship between or among two
or more variables. He explained further that Cross-
sectional studies are relevant where there are many
variables that are needed to be studied
simultaneously. The study collected data from the
top ten performing brokerage firms listed in the
Nigerian Stock exchange (NSE, 2020) out of the
190 active brokerage firms in Nigeria. Using, [30],
sample determination formula, the sample size is
thus obtained to be n = 378.78 approximately 379.
This study relies solely on the primary sources of
data. A well-structured questionnaire using a five-
point Likert scale was adopted. The questionnaire
design was given to the brokers in the selected
brokerage firms for onward administration to their
respective clients. Lastly, the Structural equation
model (SEM), whereby the variables of interest
were the independent variable which is the
behavioural factor with proxies (heuristic, prospect,
herd, and market), and the dependent variable was
formulated to further test the hypothesis postulated
at a 5% level of significance.
3.2 Model Specification
The Structural equation model (SEM) or function
that includes the independent and dependent
variables for this study was computed as follows:
The model is stated as thus:
IP = ɑ + ßIHEU + ßIPRO + ßIHER + ßIMAR +
iAGE + iTYPE+ µ … equation 1
Where: Independent variable is
IP = investment performance
Dependent variables are:
HEU = heuristic factors
PRO = prospect factors
HER = herd factors
MAR = market factors
Mediating variables:
iAGE = investors age
iTYPE = investment type
ɑ = Intercept
ß = Independent variable coefficient
µ = Error terms
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Behavioural_Factor
6.2
HUF 0
ε1.35
PRF 0
ε2.94
HEF 0
ε3.61
MAF 0
ε4.38
IPF.014 ε5.44
AGE.65
1.7
IVT .79
2.1
1
.99
1.1
.98
.82
.13
.1
.21
Independent Variable-
HUF: Heuristic Factor
PRF: Prospect Factor
HEF: Herd Factor
MAF: Market Factor
Dependent Variable-
IPF: Investment Performance
Mediating Variable:
AGE: Investors Age
IVT: Type of Investment
Fig. 2: SEM Path Diagram
The Structural equation model (SEM) function
shown above will investigate the effect of the
independent variable on the dependent variable at
the same time and of the same set of
analyses. Pearson Correlation Analysis is the
statistical tool that indicates the strength and
direction of the structural linear relationship
between two random variables. The correlation will
be used to check the overall strength to establish the
regression model, individual significance of the
independent variables, and the mediating variables.
4 Analysis and Results
The Structural equation model (SEM) was used to
test the proposed model. SEM gives the opportunity
to express several parts and relationships among
variables; it portrays the model in a diagram form
for easy understanding. Models that require role
mediating, control, and intervening are better
explained by SEM. Where regression will see a
mediating variable, SEM sees the mediator as a
mediating variable. Thus it is more of an
improvement on the regression model.
4.1 Hypothesis Testing
Table 1. Correlations
HUF PRF HEF MAF IVD INR
HUF R 1
PRF R .279** 1
HEF R .249** .265** 1
MAF R .490** .652** .439** 1
BEF R 0.017 .336** .145** .251** 1
IPF R .178** .317** .560** .534** .177** 1
N 384 384 384 384 384 384
**. Correlation is significant at the 0.01 level (2-tailed).
Variable Definition:
HUF Heuristic factor MAF Market Factor
PRF Prospect Factor IVD Investors Decision
HEF Herd Factor INR Return on Investment
The table above shows the correlation coefficient
between each pair of variables. It was observed that an approximately moderate positive relationship (r=
0.490) exists between heuristic and market factor. A
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very weak positive relationship (r= 0.178) exists
between vision prospect factor and investment
performance, a weak positive relationship (r= 0.439)
exists between heuristic and market factor, a weak
positive relationship (r= 0.249) exists between
heuristic and herd factor, an approximately strong
positive relationship (r= 0.652) exists between
market factor and prospect factor, and so on.
Table 2a. Model Parameter Estimate and Summary
LR test of model vs. saturated: chi2(17) = 1203.28, Prob > chi2 = 0.0000
cov(AGE,IVT) .2139843 .0388219 5.51 0.000 .1378947 .2900738
var(Behavioural_Factor) 6.170946 .4780004 5.301733 7.182666
var(IVT) .7906405 .0579726 .6848035 .9128348
var(AGE) .6512025 .0477485 .5640309 .7518464
var(e.IPF) .4437541 .0407328 .3706887 .5312211
var(e.MAF) .375097 .0378018 .3078651 .457011
var(e.HEF) .605105 .0567711 .5034668 .7272617
var(e.PRF) .9429905 .077522 .8026592 1.107856
var(e.HUF) .3478711 .0363036 .2835226 .4268243
mean(IVT) 2.102151 .0461018 45.60 0.000 2.011793 2.192508
mean(AGE) 1.747312 .0418395 41.76 0.000 1.665308 1.829316
_cons 0 (constrained)
Behavioural_Factor .9815052 .017908 54.81 0.000 .9464061 1.016604
MAF
_cons 0 (constrained)
Behavioural_Factor 1.124137 .0216228 51.99 0.000 1.081757 1.166517
HEF
_cons 0 (constrained)
Behavioural_Factor .9931407 .0240012 41.38 0.000 .9460992 1.040182
PRF
_cons 0 (constrained)
Behavioural_Factor 1 (constrained)
HUF
Measurement
_cons .0144463 .1589769 0.09 0.928 -.2971427 .3260354
Behavioural_Factor .8189714 .0735054 11.14 0.000 .6749034 .9630394
IVT .100146 .0520668 1.92 0.054 -.001903 .202195
AGE .1283295 .0486084 2.64 0.008 .0330587 .2236002
IPF
Structural
Coef. Std. Err. z P>|z| [95% Conf. Interval]
OIM
( 5) [MAF]_cons = 0
( 4) [HEF]_cons = 0
( 3) [PRF]_cons = 0
( 2) [HUF]_cons = 0
( 1) [HUF]Behavioural_Factor = 1
Log likelihood = -3691.2302
Estimation method = ml
Structural equation model Number of obs = 372
Table 2b. Model Parameter Estimate and Summary
LR test of model vs. saturated: chi2(17) = 1203.28, Prob > chi2 = 0.0000
cov(AGE,IVT) .2139843 .0388219 5.51 0.000 .1378947 .2900738
var(Behavioural_Factor) 6.170946 .4780004 5.301733 7.182666
var(IVT) .7906405 .0579726 .6848035 .9128348
var(AGE) .6512025 .0477485 .5640309 .7518464
var(e.IPF) .4437541 .0407328 .3706887 .5312211
var(e.MAF) .375097 .0378018 .3078651 .457011
var(e.HEF) .605105 .0567711 .5034668 .7272617
var(e.PRF) .9429905 .077522 .8026592 1.107856
var(e.HUF) .3478711 .0363036 .2835226 .4268243
mean(IVT) 2.102151 .0461018 45.60 0.000 2.011793 2.192508
mean(AGE) 1.747312 .0418395 41.76 0.000 1.665308 1.829316
_cons 0 (constrained)
Behavioural_Factor .9815052 .017908 54.81 0.000 .9464061 1.016604
MAF
_cons 0 (constrained)
Behavioural_Factor 1.124137 .0216228 51.99 0.000 1.081757 1.166517
HEF
_cons 0 (constrained)
Behavioural_Factor .9931407 .0240012 41.38 0.000 .9460992 1.040182
PRF
_cons 0 (constrained)
Behavioural_Factor 1 (constrained)
HUF
Measurement
_cons .0144463 .1589769 0.09 0.928 -.2971427 .3260354
Behavioural_Factor .8189714 .0735054 11.14 0.000 .6749034 .9630394
IVT .100146 .0520668 1.92 0.054 -.001903 .202195
AGE .1283295 .0486084 2.64 0.008 .0330587 .2236002
IPF
Structural
Coef. Std. Err. z P>|z| [95% Conf. Interval]
OIM
( 5) [MAF]_cons = 0
( 4) [HEF]_cons = 0
( 3) [PRF]_cons = 0
( 2) [HUF]_cons = 0
( 1) [HUF]Behavioural_Factor = 1
Log likelihood = -3691.2302
Estimation method = ml
Structural equation model Number of obs = 372
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4.2 Discussion of Findings
H01: There is no significant effect of heuristic
factors on the investors’ investment performance in
the Nigeria capital market. As observed from the
model summary table above, heuristic factors as a
measure of behavioural factors are seen to have a
coefficient of 1.000 with a p-value (0.000) which is
less than 0.05 (5%) level of significance. This thus
implies that there is a significant positive effect of
the heuristic factor on the investor’s investment
performance. Hence, the null hypothesis which
states that ‘‘There is no significant effect of
heuristic factors on the financial performance of
investors in Nigeria's capital market’’ is rejected.
This finding also supports the study of, [31], who
investigated behavioural contextual factors on the
Colombo stock exchange and found heuristics had a
significant influence on individual investors’
performance. Other research works that align with
this conclusion are the works by, [32], [33], [34],
which reveal that heuristics factors influence
investment performance positively.
H02: There is no significant effect of prospect
factors on the investors’ investment performance in
the Nigeria capital market. The second factor which
is the prospect factor shows a model parameter
coefficient of 0.9931 with a p-value of 0.000 which
is positive and significant.” This thus shows that
with a unit increase in the investors’ prospect factor,
there will be a corresponding 0.993 unit increase in
the investment performance of the investors.
Furthermore, the null hypothesis will be rejected as
stated and we conclude that there is the prospect
factor has a significant and generalizable effect on
investment performance.
This finding also supports the study of, [20], [31],
[35], which reveals that prospect factor influence
investment performance positively.
H03: There is no significant effect of herd factors on
the investors’ investment performance in the Nigeria
capital market. The third variable which is the herd
factor was also used to explain the financial
performance of the investor in Nigeria's capital
market. The herd factor shows a coefficient of 1.124
this is thus a positive effect on the investor’s
financial performance. This effect is also seen to be
significant since it returns a p-value of 0.000 which
is less than the 5% level of significance. Thus, we
reject the null hypothesis ‘‘There is no significant
effect of herd factors on the financial performance
of investors in Nigeria capital market’’ and
conclude that there is a significant positive effect of
herd factors on the investor’s financial performance.
This is in line with the findings of the research
carried out by, [35], which looked into the
relationship between the herd and investment
performance and concluded that the herding effect
has a substantial impact on investment success.
Other studies that share the same conclusion that
Herd is positively correlated and significantly
related to investment performance include, [20],
[36], [37]. This finding also supports the study of,
[32], which reveals that herd behavior influences
investment performance.
H04: There is no significant effect of market factors
on the investors’ decision in the Nigeria capital
market. From the model summary table above, the
market factor returns a model coefficient of 0.9815
which implies a positive effect on the investor's
financial performance. Furthermore, this shows that
with a unit increase in the market factor, the
investors’ financial performance will see about a
0.9815-unit increase. The coefficient also returns a
coefficient p-value of 0.000 which is less than the
0.05 (5%) level of significance, and hence seen to
be significant. Thus, on the basis of this, we reject
the null hypothesis ‘‘There is no significant effect of
market factors on the financial performance of
investors in Nigeria's capital market’’ and conclude
that there is a significant positive effect of the
market factor on the investor’s financial
performance.
This finding also supports the study of, [38], which
reveals that market factor has an influence on
investment performance.”
Modeling behavioural factors together with the
investors’ age as a mediating variable on the
investment performance. The investor’s age returns
a coefficient of 0.1283 with a p-value of 0.008
which is positive and significant, while the
behavioural factor returns a coefficient of 0.8189
which is positive and significant. Therefore, the null
hypothesis ‘‘There is no significant effect of the
investors’ age and the behavioural factors on the
investment performance in Nigerian capital market’’
is rejected and we accept the alternative which states
‘‘There is a significant effect of the investors’ age
and the behavioural factors on the investment
performance in Nigerian capital market’’. Thus, we
can conclusively say that the age of the investor is
significantly mediating the effect of the behavioural
factor on the investor’s financial performance. This
finding corroborates the works of, [39], which
reveal that the age of investors influences
investment performance. Furthermore, this can be
said to mean that the investors’ age is critical to
measure the effectiveness of the behavioural factor
on investment performance.Type of investment as a
mediating variable: Similarly, we fitted the
behavioural factor together with the type of
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.27
Bekweri Mark Edeh, Umar Abbas Ibrahim,
Faiza Maitala, Cross Ogohi Daniel
E-ISSN: 2224-2899
291
Volume 20, 2023
investment as a mediating variable on the
investment performance. The type of investment
returns a coefficient of 0.1005 with a p-value of
0.054 which is positive but not significant, while the
behavioural factor returns a coefficient of 0.8189
which is positive and significant. Therefore, the null
hypothesis ‘‘There is no significant effect of the
investment type and the behavioural factors on the
investment performance in Nigerian capital market’’
is not rejected thus suggesting that there is no
significant mediating role of the type of investment
and the behavioural factors on the investment
performance in Nigerian capital market’’. Thus, we
can conclusively say that the type of investment is
not significantly mediating the effect of the
behavioural factor on the investor's financial
performance. Furthermore, this can be said to mean
that the type of investment is not critical to the
effect of the behavioural factor on investment
performance.” This finding also supports the study
of, [40], which reveals that the type of investor has a
negative effect on investment performance.
5 Conclusion
The study concludes that behavioural factors have a
significant effect on investment performance in
Nigeria's Capital Market. This confirms the study
by, [41], which concluded that the herding effect,
risk aversion, prospecting, and anchoring influence
investment decision-making in the stock market.
This study also confirms the study by, [42], who
studies the impact of behavioural factors on
individual investors’ decision-making and
investment performance in the Pakistani Stock
Market and found that a specific dimension of
behavioural factors would enhance the knowledge
of behavioural factors in finance.
5.1 Recommendations
Investors should carefully evaluate and do research
before making investment decisions, according to
the study, and should not be swayed by their
previous losses while making future investment
decisions. This can limit attractive investment
opportunities and have a detrimental impact on
investor mentality, resulting in poor investment
performance. Second, potential cognitive mistakes
including representativeness, hindsight, the illusion
of control, availability biases, and emotional biases
like regret aversion and over-optimism should be
highlighted. To manage and balance the impact of
behavioural influences on investors' decision-
making and investment performance, prospective
individual investors should be offered training
programs that increase their awareness of how to
spot and avoid cognitive errors and emotional biases
that lead to poor investment decisions. Finally, it is
thought that establishing a body to monitor market
performance and offer the best investment advice to
both potential and current market participants is a
good idea for the future.
5.2 Contribution to Knowledge
The study contributes to the literature on the effect
of Behavioural factors on the investors’ decision-
making in the following ways:
i. It covers all active investors listed in the
stock brokerage firms, not just one or a few as other
studies on the subject matter have done. It,
therefore, has a larger scope than previous studies
and gives a better-rounded view of the effect across
the entire economy;
ii. It covers the subject from the Nigerian,
and emerging market, perspective, extending the
body of knowledge on the effect of Behavioural
Factors on Investors' decision-making across
markets and jurisdictions where studies on the
subject had been relatively less extensive.
Acknowledgments:
We wish to acknowledge the Nile University of
Nigeria, Abuja for providing an enabling
environment for this study.
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
-Bekweri Mark Edeh carried out the
conceptualization and the manuscript
preparation.
-Umar Abbas Ibrahim supervised the entire study.
-Faiza Muritala was responsible for the Statistics.
-Cross Ogohi Daniel supervised the study and was
responsible for all corrections on the research
Conflict of Interests
The Authors have no conflict of interests to declare.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
This research received no specific grant from any
funding agency in the public, commercial, or non-
for-profit sectors.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
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WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.27
Bekweri Mark Edeh, Umar Abbas Ibrahim,
Faiza Maitala, Cross Ogohi Daniel
E-ISSN: 2224-2899
294
Volume 20, 2023