Role of Gender in Predicting Determinant of Financial Risk Tolerance

Abstract

This research was conducted to determine whether the determinants of financial risk tolerance varied by gender or whether the same factors influenced the risk-taking capacities of both genders. This study utilised personality types (Type-A and Type-B), financial literacy, and six demographic parameters, including marital status, age, education, income, occupation, and the number of dependents, as independent variables, and gender as a dividing variable. In order to conduct this study, information was gathered from 671 investors. The financial risk tolerance of male investors was determined by six out of eight independent factors (personality type, financial literacy, marital status, income, occupation, and the number of dependents). However, just four factors (personality type, financial literacy, marital status, and income) have a substantial impact on the financial risk tolerance of female investors.

1. Introduction

According to the tenets of classical economics and finance, investors are assumed to be rational actors that do exhaustive research and weigh all available data before making investment decisions that maximise returns relative to risk [1]. The assumption of investor rationality has been central to the literature on finance and economics for a considerable amount of time [2]. In reality, it was thought that the only thing moving asset values was the anticipation and reaction of rational investors, which in turn affected supply and demand and, consequently, the price [3]. Selecting the investment avenues or the combination of investment avenues (portfolio) that results in the best degree of gain or utility is at the heart of the rational investment decision-making process [4]. Since it was assumed that all investors were rational, there was only one “best” answer to any problem or investment choice.

Recent years have seen widespread criticism of the traditional economic tenets of market efficiency and human reason. Evidence of trading anomalies that rational investor models cannot explain has prompted a growing body of literature to examine this question from various theoretical perspectives. One such perspective is cognitive science, which treats each person as an individual with their own set of experiences and perspectives. Thus, current studies attempt to pin down the underlying causes of investors’ varied investment styles. Now, many years after Kahneman and Tversky published “Nudge” theory in 1979 [5], the idea of “behavioural finance” has become a legitimate field of study. This is because it is understood that investors are unique people whose decisions about where to put their money depend on several personal and environmental factors.

Complex financial instruments, lack of financial expertise, higher return expectations, volatile markets, and time constraints have given rise to professional financial planning services [6]. Evaluating the client’s risk tolerance capability and planning their portfolio based on this foundation is a crucial function of investment and financial planning [7]. The superior ability of financial planners to estimate their clients’ financial risk tolerance (FRT) and also design a rewarding portfolio based on his/her risk-return spectrum is key to the success of a financial planner [8]. Hence, the factors that can precisely determine investors’ risk tolerance are always a significant concern for financial planners. However, the irony is that risk tolerance is a qualitative phenomenon that can diverge from person to person based on the individual’s genetic makeup, demographics, personality type, cultural setting, and psychological variables/constructs. The subjective nature of risk makes it more challenging to measure as well [9].

The FRT of an investor can be measured using any one of the three most used methodologies: first, by observing the actual and real-time portfolio; second, by asking his/her investment preferences and choices; third, by asking psychologically designed questions that are capable of measuring investors’ risk tolerance [7]. Certainly, real-time portfolio information is the most accurate method of evaluating the FRT of investors but obtaining real-time portfolio investment information is difficult. Hence, the majority of the research in the field has used the psychologically designed questionnaire to predict the risk tolerance of investors [7,9,10,11,12,13,14]. An investor’s FRT can be predicted accurately by a questionnaire, but the questionnaire would have to be created in accordance with psychometric theories as a precondition [13]. The current study also goes with the method primarily used in determining the FRT of investors and uses a questionnaire-based approach to evaluate investors’ risk tolerance.

Financial planners must accurately measure the level of risk tolerance a client possesses, but this level can be difficult to forecast due to the subjective nature of risk tolerance. As a result, people working in fields as diverse as economics, finance, psychology, academic research, and industrial research have started paying attention to the FRT problem. This study aimed to determine whether or not the factor that determines risk tolerance takes into account gender differences.

2. Materials and Methods

• Theoretical Background

The early finance theories, such as Utility Theory, Markowitz Efficient Frontier, Capital Asset Pricing Model, and Arbitrage Pricing Theory, are based on the basic assumption of rationality. If the assumption of rationality holds, other things being equal, every investor decides on only one investment option which maximises their output (return) for a given input level (risk) [15].

The assumption of rationality was well accepted in finance and economics until the time it was challenged by the ground-breaking work in finance by Kahneman and Tversky [16]. Kahneman and Tversky challenged the assumption of rationality in 1974 in their work on heuristics and biases and in 1979 in their prospectus theory. This theory has challenged the rationality argument and entirely changed how the investment decision-making process is viewed. These theories have given rise to entirely new areas of finance called “Behavioural Finance”.

Behavioural finance envisaged human psychology and its impact on financial decisions [17,18,19,20,21,22,23,24], where it was proved how investors behave irrationally, which is described as the quasi-rational behaviour of investors.

• Personality theories A and B

Personality traits are consistent personality dimensions along which individuals vary; they range from extremely low to extremely high. The Big Five Model, Myers–Briggs Type Predictor (MBTI), and Type A/B personality are well-known personality attribute theories. The Big Five Model categorises people into five basic personality types: openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism [25,26]. Based on Carl Jung’s idea of personality types, MBTI was created [27]. It comprises four scales: 1. Extraversion (E)—Introversion (I), 2. Sensing (S)—Intuition (N), 3. Thinking (T)—Feeling (F), and 4. Judging (J)—Perceiving (P). Using a combination of four measures, individuals are categorised into sixteen unique personality categories [28]. Type A/B personality was initially explored by [29], who divided people into A and B personality types. Both personality types are opposed to one another, with the former being aggressive, passionate, and constantly in a hurry, and the latter being laid-back and unhurried [30,31]. It was discovered that type A individuals are more risk-tolerant than type B individuals, and as a result, they tend to have greater levels of education, financial literacy, income, and occupational standing [32].

• Hypotheses development

In the early 90s, researchers started talking about investors’ risk tolerance. FRT can be defined as the amount of uncertainty or investment return volatility an investor is willing to accept when making a financial decision [9,10]. Early and remarkable research in this domain has focused on demographic and socio-economic factors to predict investors’ risk tolerance [33,34,35,36]. The risk-taking behaviour of investors is based on demographic and psychological factors such as personality [37]. Adding to that, an investor’s financial literacy also plays a role in determining FRT [38,39,40,41,42,43].

2.1. Gender and FRT

Gender is an important risk tolerance classification factor and plays a significant role in general risk aversion [9,10,31,33,36,42,44,45,46,47,48,49] in investment decisions. Studies have also pointed out that the risk-taking capacity of men is higher than that of women [50]. Men are more sure of their choices than women, so they feel that they can forecast future consequences more reliably than women [51]. The gender disparity in stock market participation is generally interpreted by the lower financial literacy (FL) of women [52,53], lower numeracy [54], lack of understanding of financial instruments [55], or lower risk tolerance [56,57]. However, some researchers have inferred an insignificant relationship between gender and risk tolerance [35].

2.2. Age and FRT

Age is one of the demographic factors that affect the degree of an investor’s risk tolerance. Financial advisors consider the age of the investor to understand the period to recover the losses of investments. As age increases, the investor has fewer years, so the investor’s risk appetite decreases. FRT is inversely related to age [42,58,59], whereas, in contrast, some studies found that risk tolerance positively increases with age [37,60,61]. On the same line, some research studies say that the relationship between age and risk tolerance is not linear [31,62,63]. There is a ‘U’ shaped relationship between the age and risk tolerance of an individual, as risk capacity increases as age declines to a certain point. Therefore, in this study, it is expected that:

H1: 

There exists a negative relationship between age and the FRT level of investors.

2.3. Income and FRT

Income and wealth also play a significant role in explaining the FRT of an individual. Income is the immediate resource for investments. Individuals allocate some percentage of their income for investment to increase their wealth, which is positively associated with FRT. With the income/wealth increases, the FRT moves upward [35,39,42,49,62,64,65,66,67,68]. A higher income and wealth level helps to hold adverse investment return shocks. So people with higher earnings appear to be less risk-averse [69]. Therefore, it can be said:

H2: 

There is a positive relationship between FRT and the income of the investor.

2.4. Marital Status and FRT

The role of marital status is another aspect that influences risk behaviour. Investment managers consider marital status to be an important factor in determining investor risk exposure levels and support the idea that single people are greater risk takers than married people [35,49,70,71,72,73]. Married investors have low levels of FRT as they have more responsibilities than single investors [58,60,61]. In this study, it is expected that;

H3: 

Married investors are less risk-tolerant than unmarried investors.

2.5. Occupation and FRT

Investors’ occupations and professions apply to the primary task that anyone undertakes to fulfil the requirement for their livelihood. They may play a role in measuring the tolerance of financial risks. Self-employed individuals and entrepreneurs are often likely to accept more risk than others [74]; they are more risk-tolerant than salaried individuals [64,75]. This leads us to the following hypothesis:

H4: 

Self-employed investors tend to have a higher level of risk tolerance than salaried investors.

2.6. Education and FRT

Many studies on education and risk tolerance have also been carried out. It is commonly accepted that individuals with a higher education level have a greater capacity to measure risk and return on investment than others [35,42,71,76,77,78]. Individuals with a higher level of education were considered more risk-tolerant than those with a lower level of education, although some studies have inferred that the risk attitude of the individual is not determined by education [10,66,79]. Therefore, it can be hypothesised that;

H5: 

Investors with a higher education level tend to have a higher risk tolerance.

2.7. Number of Dependents and FRT

It has been suggested that having a dependent is also a factor that affects the level of willingness to take financial risk. Individuals with children are less likely than those without children to take financial risks [80]. Individuals desire security and become more risk-averse with an increasing number of dependents. Therefore, family size and the number of people who depend on investors have a negative relationship with FRT. FRT decreases proportionally to the increase in dependents [10,49]. Contrary to popular belief, many studies have found that the number of dependents does not affect FRT [67,72]. Therefore, it is expected that;

H6: 

The level of risk tolerance decreases as the number of dependent increases.

2.8. Personality and FRT

In the study of psychology, an individual’s risk attitude, ranging from risk-averse to risk-taking, is a personality characteristic [81], and it plays a crucial role in determining investor behaviour and investment avenue selection [82,83,84,85]. However, relatively little research [30,73,86,87,88] has considered personality type as one of the influential elements alongside demographic variables.

Financial risk taking is influenced by a range of personality qualities that contribute to risk aversion and risk seeking, and there is a link between personality traits and financial performance [13]. Investors’ personalities not only affect them when deciding how to invest their money but also strongly influence the investment strategy they choose [30,75,85,89]. Personalities of type A are more likely to be aggressive and competitive, whereas those of type B are more likely to take calculated risks. Type A also has a larger readiness to take chances, whereas type B does not and is even reluctant to take risks. It is also assumed that those with type A personalities are more comfortable taking financial risks than those with type B personalities [90]. As a result, it stands to reason that;

H7: 

Personality type/trait has a significant positive impact on FRT.

2.9. FL and FRT

FL can be described as a person’s ability to understand and make use of financial concepts [91]. There is a scarcity of research ascertaining the direct relationship between FL and FRT, and there could be a new area of research in this line [39,40]. Financial experts prefer more risky investments than laypeople due to the distinction in their risk perception and interpretation [38]. Portfolio diversification and wealth accumulation are positively correlated to FL [92,93,94]. FL mediates the relationship between the demographic characteristics of investors and their proclivity to take risks [95]. Hence, FL is a significant determinant of FRT [42]. Therefore, it is proposed that;

H8: 

FL has a significant positive impact on FRT.

2.10. Rationale for the Study

While several studies have focused on the connection between investor demographics and FRT, few have investigated how investor personality, financial literacy, and risk tolerance are intertwined. Few studies have looked into whether the factors influencing FRT vary depending on the investor’s gender. In terms of economics and social mores, the roles of men and women in India radically differ from those in Western countries.

Therefore, even though the woman contributes financially, she does not shoulder the primary burden of meeting the family’s economic demands. It is fascinating to see if males and females have similar risk tolerances or if the differences are due to the distinct roles men and women play in Indian society. The following model (Figure 1), derived from existing works in the field, accounts for differences between the sexes [96].

2.11. Research Methodology

• Procedures and Participants

A single cross-sectional research design was used for this investigation. Using a structured online and offline questionnaire as a point of contact with respondents from the Gujarat region, the relevant data were gathered using a convenience sample technique. The sample size was determined utilising a statistical technique. With equal probabilities of success and failure (p,q = 0.5), the confidence interval was set at 99%, and the error was assumed to be 5%. Using Gujarat’s total population, the formula yielded a sample size of 666. With the assistance of a few stockbrokers in the Gujarat region, we reached out to around 5600 investors. The responses of 765 investors were gathered using both techniques. A total of 94 replies out of 765 were lacking in one or more respects and were therefore rejected. Finally, the study used data from 671 investors to satisfy its objective.

A structured questionnaire containing basic demographic information, a personality scale, FL scale, and FRT scale was utilised for data collection. All of the demographic data were collected as nominal categories. Personality type A/B was measured using the scale created by [12] and validated by [97]. It has six statements on a four-point scale, so the total score runs from six to twenty-four.

FL was assessed using the 2018 FL tool set from the OECD. The OECD Financial Literacy (FL) toolkit examines FL on three dimensions: financial knowledge, financial conduct, and financial attitude. The range of possible total FL scores is from 1 to 21. A scale made by [74] was used to measure FRT. It has five statements, each of which has a four-point scale, for a total scale range of 5 to 20.

The scale data were checked for reliability using Cronbach’s alpha. The reliability of all three scales is above the threshold limit of 0.6 [98], confirming the scale’s reliability. Using the average variance extracted (AVE)and Fornell–Larcker criteria, we assessed convergent and discriminant validity. All three constructs had an AVE better than 0.5, which indicates sufficient convergent validity for the scales [99]. The discriminant validity of the scale is confirmed by the fact that the square root of the AVE for each construct is higher than the correlation with the other constructs [99] (see

Table 1. Reliability and Validity.

Construct	Cronbach’s Alpha	AVE	Fornell–Larcker (Discriminant Validity)
			FL	FRT	Personality Type
FL	0.675	0.517	0.759
FRT	0.750	0.617	0.580	0.786
Personality type	0.852	0.663	0.705	0.702	0.814

(Source: Author’s calculation using SPSS).

).

According to

Table 2. Demographic information of the respondents and descriptive analysis.

Variables	Classification	Male (N = 381, Avg. FRT = 13.86)			Female (N = 290, Avg. FRT = 10.81)
		Frequency	Percent	Avg. FRT	Frequency	Percent	Avg. FRT
Marital Status	Married	177	46.5	12.6	181	62.4	10.5
	Single	204	53.5	15.5	109	37.6	11.4
Age	40 years and Above	169	44.4	13.5	122	42.1	10.8
	Below 40 years	212	55.6	14.2	168	57.9	10.9
Education	Below graduation	152	39.9	14.1	107	36.9	10.7
	Graduation and above	229	60.1	13.8	183	63.1	10.9
Income	Below 800 k	215	56.4	13.3	202	69.7	10.6
	800 k and above	166	43.6	14.6	88	30.3	11.2
Occupation	Non-entrepreneur	184	48.3	13.2	191	65.9	10.8
	Entrepreneur	197	51.7	14.5	99	34.1	10.7
Number of Dependents	4 or fewer dependents	213	55.9	15.0	171	59.0	10.8
	More than 4 dependents	168	44.1	12.4	119	41.0	10.9
Variables	Classification	Mean		SD	Mean		SD
Personality Type	----	14.79		4.23	12.18		4.59
FL	-----	16.22		3.58	15.19		3.68

(Source: Author’s calculation using SPSS).

, 381 of the total 671 responders were male, while the remainder were female. Males had an average FRT of 13.86, while females had an average FRT of 10.81. Males and females had average overall personality scores of 14.79 and 12.18, respectively. While the average FL total sum score for males was 16.22, for females, it was 15.19. Single Males displayed the greatest FRT (15.5), followed by males with four or fewer dependents (15.0), those with incomes over USD 8 million (14.6), and male entrepreneurs (14.5). Males with over four dependents had the lowest FRT score, 12.4. Regarding female investors, unmarried women have the highest FRT at 11, followed by those with an income of INR 800 K or more. Females earning less than INR 800 K had the lowest FRT score (see Table 2).

3. Results

Multiple regression analysis was conducted using SPSS 23’s split file feature to identify the variables that are important in determining the FRT of males and females. Below is the data code utilised for the analysis (see

Table 3. Name, definition, code, and variable type used in the analysis.

Variables	Classification	Variable Type	Code
Marital Status	Married	Independent	0
	Single		1
Age	40 years and above	Independent	0
	Below 40 years		1
Education	Below graduation	Independent	0
	Graduation and above		1
Income	Below 800 k	Independent	0
	800 k and above		1
Occupation	Non-entrepreneur	Independent	0
	Entrepreneur		1
Number of Dependents	4 or fewer dependents	Independent	0
	More than 4 dependents		1
Personality Type	----	Independent	Actual score
FL	-----	Independent	Actual score
FRT		Dependent	Actual score

(Source: Author’s calculation using SPSS).

).

When the split file function is used for regression analysis by gender, it gives a separate regression model for men and women. Personality type, income, occupation, marital status, number of dependents, and FL variables were significant in determining the FRT of male investors. In contrast, the age and education variables were found to be insignificant. The value of the ANOVA test is below the threshold level of 0.05, so it can be said that the model is statistically significant. The adjusted R square of the model is 0.544, implying that six independent variables, namely, personality type, income, occupation, marital status, number of dependents, and FL, explain 54.4 per cent of the variation in FRT level (see

Table 4. Regression Model for Male Gender.

	Unstandardised Coefficients		Standardised Coefficients	t	Sig.
	B	Std. Error	Beta
(Constant)	7.153	0.626		11.429	0.000
Type A or B personality	0.276	0.025	0.430	11.092	0.000 *
Age	0.227	0.200	0.042	1.135	0.257
Income	1.214	0.195	0.222	6.235	0.000 *
Education	−0.102	0.196	−0.018	−0.519	0.604
Occupation	0.881	0.194	0.162	4.546	0.000 *
Marital Status	1.083	0.214	0.199	5.064	0.000 *
Number of Dependents	−1.129	0.216	−0.206	−5.224	0.000 *
FL	0.092	0.027	0.122	3.433	0.001 *
R	0.744		Adjusted R Square	0.544
R Square	0.553		Std. Error of the Estimate	1.83604
ANOVA	0.00

* = significant @ 5% level of significance (Source: Author’s calculation using SPSS).

).

Personality type, income, marital status, and FL were significant in determining female investors’ FRT. While age, education, occupation, and number of dependents variables were not found to be significant in the determination of female investors’ FRT, the value of the ANOVA test is less than the threshold level of 0.05, indicating that the model is significant. Based on the adjusted R square value, personality type, income, marital status, and FL can explain 43.7 per cent of the variation in FRT (see

Table 5. Regression Model for Female Gender.

	Unstandardised Coefficients		Standardised Coefficients	t	Sig.
	B	Std. Error	Beta
(Constant)	3.766	0.619		6.086	0.000
Type A or B personality	0.325	0.027	0.565	12.263	0.000 *
Age	0.315	0.239	0.059	1.316	0.189
Income	0.741	0.260	0.129	2.848	0.005 *
Education	0.086	0.246	0.016	0.350	0.726
Occupation	−0.164	0.248	−0.029	−0.661	0.509
Marital Status	0.582	0.245	0.107	2.374	0.018 *
Number of Dependents	0.020	0.242	0.004	0.081	0.936
FL	0.161	0.033	0.224	4.875	0.000 *
R	0.637		Adjusted R Square	0.437
R Square	0.453		Std. Error of the Estimate	1.98550
ANOVA	0.00

* = significant @ 5% level of significance (Source: Author’s calculation using SPSS).

).

Six of the eight independent variables, namely, personality type, income, occupation, marital status, number of dependents, and FL, were important in determining male investors’ FRT. In comparison, only four of the eight sample variables, namely, personality type, income, marital status, and FL, were significant in determining the FRT of female investors. Investors’ age and education level were insignificant in both males and females. In contrast, occupation and number of dependents are found significant only in determining male investors’ FRT but not in females.

4. Discussion

The personality type of the investor is found to be significant in the determination of FRT for both genders; further personality analysis reveals that type A shares a positive relationship with FRT. Hence, it can be said that male and female individuals of personality type A are greater risk takers compared to type B personality investors, and the results are in line with other studies [32,92,93]. The income variable is also found to have a significant positive impact on FRT for both genders. The findings are supported from the similar findings by [35,39,42,49,62,64,65,66,67,100]. Entrepreneurs are inherent risk takers; hence, their FRT is also high [66]. This study again proves that a single individual takes a higher risk than a married one. These findings substantiate the previous similar findings by [13,31,35,49,57,66,76,101,102,103]. FRT is found to be negatively correlated with number of dependents, and the results reconfirm the findings of [72,80]. Investors with fewer than four dependents are found to be more risk-tolerant than those with more than four. However, this holds for only male investors; the risk tolerance of female investors is unaffected by the number of dependents.

Looking at the standardised beta value (see Table 4 and Table 5), the factors which are most influential for each gender can also be found. Regarding male investors, personality type is the most influencing factor on FRT, followed by income, number of dependents, marital status, occupation, and FL. In female investors, too, personality type is the most influencing factor in determining FRT (see

Table 6. Demographic variables, Personality type, and Financial Literacy and its impact on the FRT of Male Investors.

Study Variable	Finding for Male Investors	Level of Importance *	Inference
Personality type	Significant	1	Investors with type A personality are greater risk takers than type B personality.
Age	Insignificant	-	--
Income	Significant	2	As income increases, risk tolerance level also increases (Positive relationship).
Education	Insignificant	-	--
Occupation	Significant	5	Entrepreneurs are inherent risk takers, and take more financial risk than non-entrepreneur investors.
Marital Status	Significant	4	Unmarried or single male investors’ risk tolerance level is higher than married investors.
Number of dependent	Significant	3	Number of dependents is negatively correlated with FRT. FRT decreases with the increase in number of dependents.
Financial Literacy	Significant	6	Male Investors with higher financial literacy take the higher financial risk (positive relationship).

(* = Where 1 shows the most important and 6 shows the least important).

). For the female gender, number of dependents and occupations were insignificant. Additionally, FL is the least influencing factor in determining the FRT of male investors; whereas, for the female investor, it is the second most influencing variable (see

Table 7. Demographic variables, Personality type, and Financial Literacy and its impact on the FRT of Female Investors.

Study Variable	Finding for Female Investors	Level of Importance *	Inference
Personality type	Significant	1	Female investors with type A personality are more risk-tolerant than type B personality.
Age	Insignificant	--	--
Income	Significant	3	As income increases, risk tolerance level also increases (Positive relationship).
Education	Insignificant	--	--
Occupation	Insignificant	--	--
Marital Status	Significant	4	Unmarried or single females’ risk tolerance level is higher compared to married investors.
Number. of dependent	Insignificant	--	--
Financial Literacy	Significant	2	Financial literacy is positively associated with FRT. Female investors with higher financial literacy take higher financial risk.

(* = Where 1 shows the most important and 4 shows the least important).

).

Economic and societal norms in India place quite different demands on men and women. As a result, the woman does not bear the major responsibility for providing for her family’s financial needs, despite making a financial contribution. There lies our answer to why the number of dependents and occupations are not significant factors in determining the FRT of female investors.

5. Conclusions

This research paper attempted to find out if FRT is gender-sensitive or not. Six demographic variables (marital status, age, education, income, occupation, and number of dependents), along with personality type [29] and FL, were considered for testing the hypothesis. This research came out with the findings that, in the case of male investors, personality type, FL, income, occupation, marital status, and the number of dependents significantly influenced FRT. On the other hand, in the case of female investors, personality type, FL, income, and marital status were found to have significant influence. Data analysis also pointed to the conclusion that age and education have no effect on FRT on either gender.

Moreover, it was found that the personality type of investors has a more significant influence on FRT than FL or any demographic factor. It is also proved that educational qualification is not a proxy of FL. High education and poor FL may co-exist. This study proves that that formal education is not enough for a high level of FRT. What is needed for high FRT is FL or knowledge in finance.

6. Implications

Most of the time, financial advisors take the same aspects into account when establishing investment strategies for male and female clients. The study’s findings suggest that such planning should be gender-specific, as various factors impact the FRT of male and female investors in different amounts. As a result, while preparing their customers’ investment portfolios, financial planners, managers, and strategists should keep this distinction in mind. Furthermore, FRT fluctuates in response to changes in socio-economic circumstances affecting all investors. Additionally, FRT alters as socio-economic characteristics relevant to all investors vary. Thus, financial planners must keep up with these elements and adjust their clients’ portfolios to deliver the optimum return in line with their expectations and FRT.

The research’s conclusions are helpful to practitioners in the financial services industry in various ways, including counselling prospective investors, assisting their customers in choosing the right portfolio, and creating the best-suited portfolio for each client’s risk–reward profile. For example, the financial planners in the mutual fund industry, as it is a risky investment option, should focus more on males with type A personalities, those who have a smaller number of dependents, and have an income above 800 k, as this will help them to convert the prospectus investor into the investor.

The findings also benefit the academic and industry researcher involved in the finance and behavioural research field. The study is also helpful to all the current and future teachers and students to understand the concept of FRT and the factors affecting it. The study could have some implications for governments and policymakers of the financial industry. They can use the results to educate and create awareness among potential investors as per their gender and personality traits and can train them with appropriate financial awareness or literacy programs.

7. Limitation and Future Scope

This study is survey-based and has explored the behaviour of investors in the country of India only. It is limited to a few selected demographic factors, personality type, and FL. Additionally, the study has tried to prepare two different models for both genders but has not addressed the issue of the moderation effect. A future study can be carried out to check the moderation effect of gender. Future studies can look at other demographic and socio-economic factors, such as race, source of wealth (personal/received in legal heir), social affiliation, and psychological factors, such as financial satisfaction, perceived importance of money, money obsession, and financial anxiety, to find its association with FRT. The study has overlooked social and cultural-level factors that could have some impact on investors’ decisions. Despite these limitations, the study adds valuable insight into how different demographics affect the risk tolerance level of male and female investors. It also highlights how personality type and FL affect the risk tolerance level of the investor of a different gender.