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ORIGINAL PAPER
DOI: 10.26794/2587-5671-2024-28-4-18-32 JEL G4, G40, G41
(CO ]
Role of Personality Traits and Perceptive Factors in Determining Stock Market Investment Intentions
C. Gautama, R. Wadhwab, T. V. Ramanc
a Management Education and Research Institute, New Delhi, India;
b Amity Business School, AUUP, Noida, India; c Birla Institute of Management and Technology, Greater Noida, India
ABSTRACT
The present study intends to comprehend the stock market investment intention among individuals. The purpose of the study is to assess the role of perceptive factors, including subjective norms, attitudes and perceived behavioural control, in relation to individual personalities and the theory of planned behaviour. In this regard, the study adopts a quantitative approach with the help of the PLS-SEM technique to predict relationships between variables. The responses were collected through a structured questionnaire from individuals with or without trading experience in the stock market. The key findings indicate a positive impact of perceptive factors on individual investment intentions. Furthermore, it was found that personality characteristics influence individual investment intentions, while gender and age moderately influence the relationship of intuitive factors and personality traits with investment intent. Overall, the study contributes to the individuals' perception regarding Indian stock market investments. Hence, the findings are crucial for governments, investment businesses and financial intermediaries to propel stock market participation and investment. Keywords: personality traits; big-five; theory of planned behaviour; investor behaviour; stock market investment
For citation: Gautam C., Wadhwa R., Raman T.V. Role of personality traits and perceptive factors in determining stock market investment intentions. Finance: Theory and Practice. 2024;28(4):18-32. DOI: 10.26794/2587-5671-2024-28-4-18-32
ОРИГИНАЛЬНАЯ СТАТЬЯ
Роль личностных качеств и перцептивных факторов в определении инвестиционных намерений на фондовом рынке
Ч. Гаутама, Р. Вадхва", Т. В. Раманс
а b Бизнес-школа Amity, AUUP, Нойда, Индия; c Институт технологии управления Birla, Большая Нойда, Индия
АННОТАЦИЯ
Настоящее исследование направлено на изучение инвестиционных намерений индивидов на фондовом рынке. Цель исследования - оценить роль перцептивных факторов, включая субъективные нормы, установки и воспринимаемый поведенческий контроль, в отношении личностных особенностей индивидов и теории планируемого поведения. В связи с этим в исследовании использован количественный подход с применением метода PLS-SEM для прогнозирования взаимосвязей между переменными. Ответы получены с помощью структурированной анкеты от респондентов, имеющих или не имеющих опыт торговли на фондовом рынке. Основные результаты свидетельствуют о положительном влиянии факторов восприятия на индивидуальные инвестиционные намерения. Кроме того, было установлено, что личностные характеристики влияют на индивидуальные инвестиционные намерения, в то время как пол и возраст воздействуют на взаимосвязь как интуитивных факторов, так и личностные характеристики. В целом, данное исследование вносит вклад в изучение восприятия индивидами инвестиционных намерений на индийском фондовом рынке. Таким образом, полученные результаты имеют большое значение для правительств, инвестиционных компаний и финансовых посредников, чтобы стимулировать участие в фондовом рынке и инвестиции. Ключевые слова: характерные черты личности; большая пятерка; теория планируемого поведения; поведение инвесторов; инвестиции на фондовом рынке
Для цитирования: Gautam C., Wadhwa R., Raman T.V. Role of personality traits and perceptive factors in determining stock market investment intentions. Финансы: теория и практика. 2024;28(4):18-32. DOI: 10.26794/2587-5671-2024-28-4-18-32
© Gautam C., Wadhwa R., Raman T. V., 2024
BY 4.0
INTRODUCTION
The constantly changing scenario in global financial markets has changed individual investors' outlook on traditional finance. Fama [1] discussed that traditional finance operates on the efficient market hypothesis, presuming information-efficient financial markets and rational investors. However, in reality, investors follow the rule of thumb instead of optimization [2]. This contradiction created a revolutionary shift in research and practice, where conventional finance took a leap to behavioural finance. Behavioural finance focuses on individuals' irrational behaviour in the market owing to the concepts and myths of traditional finance, psychology, and neuroeconomics [3].
Financial markets are competitive, offering flexible investing options among various financial assets and obtaining liquefiable returns from the invested capital [4]. However, stock market investment has always been a challenging decision which demands a rational thought process [5, 6]. Hoffman and Post [7] found that individual investors struggle to align their anticipated returns with their risk tolerance. Nearly 30% of investors think they can make prudent decisions yet fall short of achieving their investment objectives [8]. Hence, it is essential to comprehend what influences their investment intentions in the stock market. The discussion concerning individual investment decisions has been polarized by numerous scholars [9-13]. However, limited studies have been done on Indian investors' intentions to invest in financial markets [14, 15].
It has been noted that despite the advancements in the financial markets, most Indian consumers have significantly less stock market participation [16]. According to 2021 World Bank data, India is the top 20 saver nation, with a 30% savings rate as a percentage a percentage of GDP, the majority of which is accumulated in bank deposits, physical assets, and currency [17]. In a survey sponsored by the Securities and Exchange Board of India [18] on investment and savings behaviour, it was found that 15% of the total urban Indian households only invested in securities markets, and the remaining are more inclined towards less risky assets like bank deposits, post office schemes, insurance, etc. It has also been observed that the major roadblock is a lack of awareness among investors regarding key instruments. Thus, it becomes more important to study the rationale behind this context. The present study attempts to comprehend investor intentions in the Indian financial markets, one of the largest developing economies. In addition, with the aim
of understanding the investor behaviour in stock markets, this research also studies those individuals who can be potential investors. This research is an extension to understand the relationship between perceptive factors and social traits and the individual intention to invest [14, 19, 20].
LITERATURE REVIEW
Investment Intentions and Perceptive Factors
According to I. Ajzen [21], the theory of reasoned action asserts that behavioural intentions are insightful and can predict an individual's inclination to behave in a particular manner. The theory of planned behaviour extends the theory of reasoned action, which states that intentions and perceived behavioural control can predict an individual's behaviour [22, 23]. Behavioural intentions work with three critical, independent conceptual frameworks: attitude, subjective norms, and perceived behavioural control [24]. The theory of planned behaviour (TPB) proposes that individual intention precedes behaviour and has been widely used in studies related to behavioural domains [25].
subjective Norms
The theory of planned behaviour postulates that individuals who are likely to invest in stock markets are influenced by their close peers or family [26]. Further, it creates social pressure on an individual to perform or not perform a specific behaviour in a given situation [22]. While understanding financial choices in family firms, family norms for external debt and equity positively and significantly affect behavioural intentions [27]. Social investors find a stock market investment more attractive when their peers participate [28]. While studying Indian stock markets, it was found that subjective norms show a weak positive effect on investment intention [29]. Thus, the perceptive factor, a subjective norm springing from acquaintances, influences the investment intention of an individual, proposing the following hypothesis:
H1: Subjective Norm positively impacts individual investment intentions towards the stock market.
Attitudes
Attitude is an individual's psychological and cognitive behaviour while assessing a particular aspect and evaluating the favourable or unfavourable outcomes [30]. A positive attitude will lead to a stronger behavioural inclination,
whereas a negative attitude will provide a weaker preference [15]. Sin-Hui et al. [31] identified attitude as the most substantial TPB variable to describe the intentions of accounting practitioners concerning earning management. Attitude towards risk impacts investment behaviour, creating specific behavioural aspirations for different risk-intolerant levels [32]. Further, while studying the theory of planned behaviour in the Indian stock market, investors' attitudes partially mediate the relationship between financial knowledge and investment intentions [33]. Based on the arguments, the attitude of individual investors influences their investment intentions, proposing the following hypothesis:
H2: Attitude positively affects individual investment intentions towards the stock market.
Perceived Behavioural Control
The theory of planned behaviour presumes that perceived behavioural control explains the perception of whether an individual has possession of the required resources, ability, or opportunity to perform a behaviour [34]. Various studies were done under the pretext that perceived behavioural control influences the behavioural intentions of individual investors [35, 36]. Mahastanti & Hariady [37] identified perceived behavioural control and risk preference as influencing the intent of potential female investors to purchase financial products. While understanding the factors influencing the adoption of future products, perceived behavioural control indicates a strong association with investment intentions [38]. Thus, the study proposes the following hypothesis:
H3: Perceived Behavioural Control (H1c) positively impacts individual investment intentions toward the stock market.
Subjective Norms and Attitude
Various studies have found a direct influence of subjective norms on the attitude of individual investors [39, 40]. Shanmugham and Ramya [41] identified a significant effect of various social factors, including media, the Internet and social interactions, on the attitudes towards trading. This research evaluates the individual investment intentions in the Indian stock market, where most individual investors are easily affected by others' opinions and the media. In India, the stock market is widely discussed across various media channels, which descriptively provide knowledge and analysis of the stock market. The opinions of peers and financial
professionals will influence whether investing or not in stocks is a wise decision for an individual. Thus, the study proposes the following hypothesis:
H4: Subjective Norm positively influence an individual's attitude toward stock market investment intentions.
Investment Intentions and Personality Traits
Personality is a distinct representation of how individuals feel, think, and behave [42]. Multiple researchers, including Raymond Cattell, Donald Fiske, Norman, Smith, Goldberg, McCrae & Costa, have conducted various empirical studies to contract personality attributes [43]. The Big Five Traits taxonomy can be identified by addressing five personality dimensions: extroversion, openness to experience, conscientiousness, emotional stability and agreeableness [44]. Numerous studies have suggested that personality traits can anticipate the purview of human behaviour, preference and effects [20, 45, 46]. Pak and Mahmood [47] found that these attributes affect individual investors' risk tolerance behaviour, ultimately impacting their investment decisions in the financial market.
While studying the perceptions of individual investors and their decisions regarding various investment opportunities, it has been found that anxious people are sensitive to high risk and tend to save more and avoid investment. In contrast, independent and extroverted individuals lean more toward making investments [48]. Researchers have examined various psychological antecedents related to investment intentions and proposed that extroverted individuals have more intentions to invest in the short-term. In contrast, individuals with higher neuroticism and risk aversion avoid investing in short-term investment opportunities [19]. Conscientious, open to experience, and agreeable individual investors carry long-term investment intentions, whereas risk-averse individuals avoid them [49]. This study will extend the literature on how different personality characteristics influence individual intentions to invest. Subsequently, the following hypothesis is proposed:
H5: Extroversion (H5a), Agreeableness (H5b), Conscientiousness (H5c), Emotional Stability (H5d) and Openness to Experience (H5e) significantly influence individuals' stock market intentions.
Moderating roles of Demographic Factors (Age & Gender)
Several researchers have examined various demographic factors affecting the investment
Fig. 1. Conceptual Framework for studying stock Market Investment Intentions
Source: Compiled by the authors.
decisions of individuals. It has been found that males are more overconfident than females and often underperform while indulging in excessive trading [50]. While designing a practical application for behavioural finance, women are more risk-averse than men [51]. Various personality traits and emotional intelligence significantly affect the risk tolerance level of males and females [52]. A diverse relationship has been found between different age groups when making an investment decision [53]. It has also been found that risk aversion falls with age, increases until five years before retirement, and then rises again with age [54]. Therefore, the research proposes the following hypothesis to study the moderating role of gender and age:
H6: Gender (H6a) and Age (H6b) moderate the relationships between the personality of an individual investor, intuitive factors, and stock market investment intention.
Figure 1 represents the Conceptual Framework for the study. This framework will help to understand factors influencing Stock Market Investment Intentions.
research data and methodology
sample and Data Collection
The target population for the present study is individual investors who are 20 years of age and older and eligible to do stock market trading in India with or without prior trading experience. A solicited questionnaire is better for a dispersed population to understand their personal opinions; thus, a well-structured questionnaire was designed. Individual participants from the National Capital Region (NCR), India were approached randomly, and questionnaires were distributed via phone and e-mail using purposive and convenience sampling techniques. In order to prevent sampling errors and ensure the predictability and validity of the research, G* Power Software is a statistical power analysis program used to estimate the sample size and conduct power analyses [55]. With the help of G* Power Software V 3.1.9.7, the minimum sample size was estimated at 160 respondents at 0.80 power at a 0.05 confidence level [56]. For this study, nearly 483 participants were approached with the questionnaire, out of which 422 responses were received, with twelve incomplete responses. At
Table 1
Demographic Information
Characteristics Frequency Percentage
Gender Male 217 52.8%
Female 194 47.2%
Age 20-30 years 324 78.8%
30-40 years 57 13.9%
40-50 years 14 3.4%
50-60 years 16 3.9%
Educational Qualification Diploma 18 4.4%
Graduate 115 28.0%
Post-graduate 278 67.6%
Marital Status Married 127 30.9%
Unmarried 284 69.1%
Trading Experience Yes 168 40.9%
No 243 59.1%
Source: Compiled by the authors.
last, 411 responses were found valid [57], with an effective response rate of 85.09%.
Measurement of the variables
The first section of the research survey explained the aim of the study and provided directions for completing the survey. The second section was designed for respondents to submit demographic data. The third section included a research tool with items studied through a seven-point Likert scale, with one being "Strongly Disagree" and seven being "Strongly Agree". Various exogenous and endogenous variables, along with their latent variables, were adapted from previous studies. Some items were modified in the Indian context for better research analysis. The research is analyzed through the Partial Least Squares — Structural Equation Model (PLS-SEM) with the help of SmartPLS software.
The proposed model for this study includes five variables. The big five-factor model is the most commonly used personality model for research [58]. Romeros et al. [59] suggested that a compact version of the big five personality scale might save research costs, boost participation, and simplify survey administration. In this study, personality traits are measured through a Ten-Item Personality Inventory (TIPI) measure, which is adapted from
the study of Gosling, Rentfrow, & Swann [60]. This research examined the cognitive constructs of TPB adopted from the previous work of Taylor and Todd [61] & Elliot and Ainsworth [24] and modified the items to align with the study [3, 4]. For the dependent variable, i.e., the investment intention of individual investors, four items were used for measurement, adapted from the work of Lim, Soutar, & Lee [62].
results
Demographic Profile
Table 1 summarizes the demographic profile of the survey respondents. Of 411 respondents, 52.8% were male, and 47.2% were female. A total of 78.8% lie in the age group of 20-30 years, 13.9% were in 30-40 years, 3.4% in 40-50 years and 3.9% respondents were from the 50-60 years age group. Most of the respondents were post-graduates (67.6%), followed by graduates (28%) and the rest were diploma qualified (4.4%). Respondents who had trading experience in the stock market stood at 40.9% while 59.1% did not have any trading experience.
DATA ANALYsIs VIA PLs-sEM
Measurement Model
The measurement model is assessed by examining the reliability of the item, internal consistency,
Table 2
Standard Loadings of the Measurements
Constructs Items Outer Loadings AVE Composite Reliability Cronbach's Alpha
Extroversion (EX) I find myself extraverted and enthusiastic 0.977 0.717 0.831 0.786
I am reserved and quiet® 0.692
Agreeableness (AG) I am critical and quarrelsome® 0.971 0.784 0.878 0.766
I am sympathetic and warm to others 0.791
Conscientiousness (CT) I am dependable and self-disciplined 0.913 0.743 0.852 0.764
I am disorganized and careless® 0.807
Emotional Stability (ES) I am anxious and quickly get upset® 0.799 0.742 0.851 0.765
I am calm and emotionally stable 0.919
Openness to Experience (OE) I am open to new experiences 0.981 0.674 0.798 0.727
I am conventional and uncreative® 0.621
Subjective Norm (SN) I will participate in stock markets if: • My colleagues do 0.775 0.608 0.886 0.845
• The media promote 0.842
• The senior management agrees 0.742
• My family approves 0.777
• The Government and experts encourage 0.760
Attitude (AT) Investment in the stock market increases the financial knowledge of an individual 0.754 0.644 0.900 0.861
Stock market investment is a smart choice 0.827
I perceive stock market investment as substantial 0.882
Stock market investment is a fresh concept 0.688
I enjoy trading in the stock market 0.848
Perceived Behavioural Control (PBC) I generally have the information required to invest in the stock market 0.910 0.758 0.924 0.886
I invest in the stock market for a significant amount of time 0.956
I invest in the stock market and put forth more effort 0.948
I have enough money to make stock market investments 0.624
Investment Intentions (IN) I aim to invest in the stock market 0.922 0.831 0.951 0.932
I endorse investing in the stock market and will advise others to do the same 0.870
I will keep on investing in the stock market 0.960
I can cope with the disruptions brought on 0.892 the stock market trading 0.892
Source: Compiled by the authors.
Table 3
Discriminant Validity of the Measurements
EX AG CT es OE sn AT PBC iN
EX 0.720
AG 0.593 0.756
CT 0.524 0.729 0.765
ES 0.523 0.601 0.517 0.773
OE 0.650 0.662 0.668 0.588 0.807
SN 0.193 0.012 -0.006 0.004 0.023 0.78
AT 0.162 -0.020 0.089 0.045 0.073 0.53 0.803
PBC 0.180 -0.025 0.080 0.020 0.067 0.363 0.645 0.87
IN 0.174 -0.019 0.102 0.078 0.098 0.471 0.778 0.659 0.911
Source: Compiled by the authors.
Table 4
HTMT Ratio
EX AG CT es OE sn AT PBC iN
EX
AG 0.409
CT 0.486 0.193
ES 0.447 0.181 0.635
OE 0.400 0.442 0.534 0.525
SN 0.289 0.116 0.143 0.121 0.062
AT 0.219 0.142 0.117 0.101 0.130 0.570
PBC 0.251 0.082 0.160 0.069 0.095 0.373 0.704
IN 0.207 0.074 0.149 0.140 0.129 0.472 0.605 0.714
Source: Compiled by the authors.
and discriminant validity [63]. Table 2 shows the 28-indicators with their factor loadings in the measurement model. Cronbach's alpha is applied to determine internal consistency for a detailed reliability check. The value of Cronbach's alpha is within the acceptable limit of 0.7 and above [64]. Furthermore, the internal consistency and composite reliability (CR) of the latent variables are analysed to ascertain the convergent reliability
of the constructs, which is between 0.79 and 0.95, exceeding the threshold value of 0.7 [65]. Thus, CR is assured. Additionally, to determine convergent validity, the average variance extracted (AVE) is calculated and is higher than 0.5, which is considered adequate [65, 66].
Discriminant validity is determined to evaluate the degree to which the constructs are different from others [67]. According to Fornell and Larcker
Fig. 2. PLS-SEM Full Model with Path Coefficient and t-Statistics (p < 0.05*, p < 0.10**)
Source: Compiled by the authors.
[65], to determine discriminant validity, the AVE square root of an identified construct should be greater than the inter-construct correlation in a measurement model, as shown in Table 3. The value of the square root of AVE (in italics) is greater than the inter-construct correlation. Table 4 illustrates the Heterotrait-Monotrait ratio (HTMT ratio) to ascertain the discriminant validity of the constructs, which are under the required threshold of 0.85 [68]. Therefore, the results of the discriminant validity analysis are accepted.
Structural Model Assessment
The structural model assessment is based on four parameters, including examination of multicollinearity, structural model relevance, and determination of coefficient (R 2) [69]. Collinearity is evaluated by assessing the Variation Inflation Factor (VIF) with the help of latent constructs. According to Hair et al. [67], the value of VIF should not exceed 5 for the data to follow collinearity. In the present study, no issue of multicollinearity is found, as the VIF values obtained are EX (1.484), AG (1.302), CT (1.435), ES
(1.185), OE (1.700), SN (1.428), AT (2.168) and PBC (1.729).
After a successful collinearity check, the significance of the constructs is determined using bootstrapping techniques [67]. Table 5represents the results of path coefficients and t-statistics through bootstrapping 5000 random cases. Figure 2 shows the structural model results using Partial Least Squares (PLS) analysis with standardized path coefficients and summarizes the PLS analysis of the structural model with t-test statistics. Post-hypothesis testing, the coefficient of determination (R 2) is calculated, and the results are satisfactory [70], as shown in Table 6.
DISCUSSIONS AND IMPLICATIONS
Discussions
Hypotheses Testing
Table 5 represents the path coefficient value and results of the hypothesis. The results support the hypotheses H1, H2 and H3, showing a positive and significant impact of SN, AT and PBC on IN (H1: t = 2.085, p < 0.05; H2: t = 12.883, p < 0.05; H3: t = 6.198, p < 0.05). SN has also shown a significant
Table 5
Results of Hypothesis Testing. ** and * Represents a Significant Level at 5% and 10% (Two-Tailed Test)
Hypothesis Path Coefficients t-Value
H1 SN->IN 0.072 2.085"
H2 AT->IN 0.559 12.883"
H3 PBC->IN 0.267 6.198"
H4 SN->AT 0.530 17.963"
H5a EX->IN 0.024 0.350
H5b AG->IN -0.126 1.974"
H5c CT->IN 0.040 0.539
H5d ES->IN 0.094 1.701""
H5e OE->IN 0.017 1.786""
Source: Compiled by the authors.
Table 6
Coefficient of Determination (R2)
Variables Coefficient of Determination (R2)
AT 0.288
IN 0.657
Source: Compiled by the authors.
Table 7
Result of PLS-MGA. * and ** Represent a Significant Level at 5% and 10% (Two-Tailed Test)
Variables Path Coefficients Gender Differences Path Coefficients Age Differences
Male Female Below 40 years Above 41 years
SN->IN 0.124 0.091 0.657 0.071 -0.234 0.057""
AT->IN 0.76 0.255 0.000" 0.536 0.549 0.939
PBC->IN 0.076 0.535 0.000" 0.258 0.249 0.963
SN->AT 0.473 0.667 0.000" 0.498 -0.805 0.000"
EX->IN -0.091 0.03 0.328 -0.017 -0.09 0.774
AG->IN -0.014 -0.237 0.191 0.045 -0.139 0.552
CT->IN -0.076 0.204 0.064"" -0.007 0.213 0.49
ES->IN 0.009 0.076 0.603 0.067 0.009 0.777
OE->IN 0.182 0.012 0.32 -0.02 -0.079 0.866
Source: Compiled by the authors.
and positive effect on AT (H4: t = 17.963, p < 0.05). Thus, the results support hypotheses H4. While talking about the effect of personality traits on investment intentions, ES and OE have a significant and positive impact on IN (H5d: t = 1.701, p < 0.10; H5e: t = 1.786, p < 0.10), while AG has a significant and negative impact on IN (H5b: t = 1.974, p < 0.05). For testing further hypotheses (H6a and H6b), partial least squares — multi-group analysis (PLS-MGA) is done.
This research confirms the role of personality traits and perceptive factors in determining individual stock market investment intentions. It expands the knowledge of individual investment behaviour rather than sticking to fundamental or traditional theories. This study provides empirical evidence demonstrating individual investors' intentions in the stock market by revalidating TPB. The findings suggest that perceptive factors, including subjective norms, attitudes, and perceived behavioural control, positively and significantly influence the stock market investment intentions and align with the work of Ibrahim and Arshard's [71]. Investment firms can introduce mobile applications and financial analysis software to promote new and innovative portfolio management techniques. Investment organizations or security firms can also influence an individual's perception of participating in stock market trading by providing accurate information and efficient infrastructure and technology. More media reporting will help promote the stock market, which will escalate an individual's investment intention. The empirical results of this study also indicate that subjective norms positively affect an individual's attitude towards stock market investment. It implies that individual opinions will also turn positive towards stock markets if their family or peers participate in trading.
The result also suggests a positive and significant association between personality traits like emotional stability and openness to experience and the investment intentions of individual investors in the stock market. However, agreeableness negatively impacts investment intentions. These results extend the work of Aren & Nayman [72]. As every individual carries different characteristics, the social trait of being emotionally stable and open to new experiences positively boosts the intention to invest. Investment organizations may seek happy individuals who are excited about new opportunities and can invest more time and energy participating in stock markets. Besides expecting investors to develop efficient portfolios, a financial adviser might ask
for preferences and build a behavioural portfolio based on their personality attributes.
Multi-group Analysis using PLS
PLS-MGA has been suggested as a practical approach to study group comparison research [70]. The current research examines the moderating effect of Gender and age through PLS-MGA using SmartPLS. The Gender is divided into male and female, while the construct age is categorized into below 40 and above 41 to compensate for the unequal age distribution of the sample. The findings of PLS-MGA are summarized in Table 7. The group difference of path coefficients of the male and female groups is significant and, thus, moderates the relationship between AT and IN, PBC and IN, and SN and AT at p < 0.05. The findings also suggest that Gender moderates the association of CT and IN at p < 0.10. Thus, H6a is partly supported. The path coefficient difference of age category significantly moderates two relationships, including SN and IN at p < 0.10 and SN and AT at p < 0.05. Consequently, H6b is partly supported. This study tries to understand the moderating effect of demographic factors, i.e., Gender and age, on the relationship between perceptive variables and traits with individual investment intentions. The empirical results extend the research work of Mayfield et al. [20] and Barber & Odean [12]. The research findings suggest that males form an attitude toward their investments; in contrast, females have a perceived difficulty while investing and develop attitudes towards their investments based on social pressure.
A substantial influence of Gender is also seen between conscientiousness and investment intentions, suggesting that females are more anxious and conscientious regarding their investments when compared with males. Furthermore, the results suggest a difference in the impact of an investor's age on their intent to invest. It was found that young investors have a positive intent to invest in the Indian stock markets. However, they are swayed away by social pressure and develop an attitude of their own. In contrast, older investors are experienced and are not influenced by social anxiety. The policymakers can deliver a clear-cut fair-trading process with transparent corporate details to enhance individuals' stock market trading experience. As a result, the government and financial intermediaries should work more to rebuild investor confidence, develop better attitudes toward investing, consequently booming the stock market.
CONCLUSION
The traditional finance theories state that investors make their choices rationally and maximize their utility [1]. Whereas behavioural finance research works on the premise that investors behave irrationally and proposes various models to understand investment decisionmaking. This research examines the association between individual investors' perceptions, their personalities, and the effect on stock market investment intentions. The results show a significant effect of perceptive factors on the investment intentions of individuals. It also suggests that personality traits like agreeableness, emotional stability, and openness to experience influence an individual's investment intentions.
The study found a meaningful moderating role of socio-economic factors like age and Gender on the association of perceptive factors, personality traits and investment intentions. The research will help the media report about the stock market and escalate new government policies to promote the same in a way that will induce an individual's intention to invest. Accordingly, if investment firms and policymakers consider these implications to promote participation and investment in the stock market, they can change individual investors' perceptions about the Indian
stock market. These measures will make it easier for businesses to obtain low-cost financing, resulting in long-term growth.
LIMITATIONS AND FUTURE SCOPE OF STUDY
The findings of this survey may not be universally applicable because it was conducted in limited parts of India, with respondents aged 20 and above who earn a salary or have investment income, including those with and without stock trading expertise. Although the questionnaires are disseminated to be proportional to the demographic background, more empirical variation in other geographic locations and settings, such as Asia and Western countries, will broaden the scope of the current study's applicability. Furthermore, it is observed that the data is not proportionally distributed among different age-groups. Future studies might focus on the effects of the Big Five personalities and intuitive factors on other financial decision-making processes, such as herding, disposition effects, and ability heuristics. Finally, this research thoroughly examines people's intent to participate in stock markets, and the research model may be used as a theoretical framework for future sustainable development research.
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ABOUT THE AUTHORS / ИНФОРМАЦИЯ ОБ АВТОРАХ
Chaandni Gautam — MBA, PhD (Management), Assist. Prof., Management Education and Research Institute, New Delhi, India
Чаандни Гаутам — MBA, PhD (менеджмент), доцент, Институт образования и исследований в области менеджмента, Нью-Дели, Индия https://orcid.org/0000-0003-0157-3858 Corresponding author / Автор для корреспонденции: chaandnigautam@gmail.com
Ritu Wadhwa — MBA (Finance), PhD, Assoc. Prof., Amity Business School, Amity University, Noida, Uttar Pradesh, India
Риту Вадхва — MBA (финансы), PhD, ассоциированный профессор, Университет Эми-
ти, Нойда, Уттар-Прадеш, Индия
https://orcid.org/0000-0002-9712-5787
rwadhwa1@amity.edu
Thanikella V. Raman — MBA, PhD in Management, Assoc. Prof., Department of Accounting and Finance, Birla Institute of Management and Technology (BIMTECH), Greater Noida, India
Таникелла Венката Раман — MBA, PhD менеджмента, доцент, кафедра бухгалтерского учета и финансов, Институт менеджмента и технологий (BIMTECH), Большая Нойда, Индия
https://orcid.org/0000-0002-4335-3450 Drtvraman@gmail.com
Author's declared contribution:
C. Gautam — research problem development, justification of hypothesis, and assessment of consistency between theoretical and practical frameworks.
R. Wadhwa — review of literature and substantiation of methodology. T. V. Raman — validation of the methodology, hypotheses, and results.
Заявленный вклад авторов:
Ч. Гаутам — разработка проблемы исследования, обоснование гипотезы и оценка соответствия между теоретической и практической базами. R. Wadhwa — обзор литературы и обоснование методологии. Т. В. Раман — проверка методологии, гипотез и результатов.
Conflicts of Interest Statement: The authors have no conflicts of interest to declare. Конфликт интересов: авторы заявляют об отсутствии конфликта интересов.
The article was submitted on 06.02.2023; revised on 06.03.2023 and accepted for publication on 27.03.2023. The author read and approved the final version of the manuscript.
Статья поступила в редакцию 06.02.2023; после рецензирования 06.03.2023; принята к публикации 27.03.2023.
Авторы прочитали и одобрили окончательный вариант рукописи.
