A Study of Factors Affecting Investment Decision of Women Investors

Men traditionally provided financially for their families while women were expected to stay at home & care for their children. Formerly reserved for the home, women are now just as likely to compete with males in the workplace. This is because of the increased access to education and employment prospects for women as a result of social and economic changes such as urbanization, industrialization, liberalization, globalization, etc. Women's access to education, employment, and other opportunities has helped them become financially self-sufficient, and they have become actively engaged in the economy, government, & society at large. Many individuals find investing to be exciting since they can participate in the decision making process & witness the outcomes of their choices. An investor's portfolio won't always see a positive return due to poor investment choices over time, but a well-balanced portfolio should still generate a profit. Investment is not a hobby but rather a serious business that can have a profound effect on one's financial security in the long run. Virtually everyone makes investments. Individuals who don't choose stocks or other equities can nevertheless invest in the financial markets by joining a 401(k) or other workplace savings plan, saving for a down payment on a home, or putting money away in a savings account at a bank or post office. Presently the sector of investment is significantly more dynamic than it was only a decade ago. Rapid changes in the global economy can have a dramatic impact on the value of a variety of assets, and investors have never had access to so much data on which to base their decisions. Saving more money over a longer period of time and investing it wisely is the key to a secure financial future. The turnover rate in investments should exceed the inflation rate & pay taxes and also allow you to earn an amount that compensates the risks taken. No considerable future rate accumulation can be expected from savings accounts, money at low interest rates, or money market accounts. However, investments in tangible assets like real estate typically yield the largest returns. Although, these investments are not fully immune from hazards, therefore one should strive to understand what kind of risks are associated to them before taking action. The lack of understanding about how stocks work makes the myopic point of view of investing in the stock market (purchasing when the propensity to climb or selling when it tends to decline) perpetuate. To grasp the features of each one of the numerous types of investing you must have significant financial understanding.

Dr. Anju Singh et al. (2021) It is commonly believed that only cold, calculated logic can be relied upon when making financial judgments. The theories & research of behavioural finance contradict this conventional understanding of finance. According to the tenets of behavioral finance, investors' choices are influenced by irrational tendencies like heuristics & cognitive biases. In the modern day period as the role of the woman in the home has evolved tremendously. Women are increasingly able to make research is to analyze how gender prejudice influences women's financial decisions. The data has been obtained from 345 working women. The study examines the effects of mental accounting, loss aversion, pack mentality and over confidence biases on female investors projected rate of return and duration of investment. The results have been evaluated utilizing multiple regression. Research shows that some types of bias can significantly affect financial decisions. Hyo-Eun Seong et al. (2021) The purpose of this research is to examine the variables that influence VC funding for new businesses, identify the most important ones, and propose a decision-making model that can serve as a benchmark for future funding decisions. The analytic hierarchy process was employed for this purpose in this study (AHP). This research utilized 19 evaluation elements focused on the entrepreneur, product & service, Target market, and finances to build a decisionmaking concept model for venture capital investment decisions. It surveyed 15 VCs and 15 startup support experts (consultants, employees of startup support organizations, etc.) with a questionnaire. The survey found that the entrepreneur is more important than the product or service, the market, or the availability of capital. More crucial than an entrepreneur's personality or technical expertise was their reliability and business fit. Thus, it was verified that the dependability & business fit of entrepreneurs became significant decision variables in venture capital investment judgments on cutting-edge firms. ISMAIL et al. (2021) Information drives the primary forces of the stock market, which are supply & demand. The most important thing to remember is that investors' opinions change depending on the data they have access to at any given time. Investors' actions in the stock market can have a significant impact on the market's performance, but it can be challenging to deduce what they'll make of any given piece of information. Thus, the purpose of this research is to conduct a type diagnosis of behavioral investors among FMPs in the Oman financial market. To determine the impact of demographic variables like age & gender on investor bias, this study analyzed the different personality types of stock market investors. It divides investor prejudices into distinct categories based on factors like age and gender. This study uses first-hand information gleaned from a survey sent out to a random sample of male and female participants in the Muscat Securities Market. A variety of statistical tests, including the sample t-test, one-way ANOVA, CATPCA, and ALSCAL, were employed to experience between the groups of respondents. According to the results of the current investigation, investors of all sexes are susceptible to cognitive biases. Dr. Rizwan Ullah Khan, Dr. (2021) Women now are widely acknowledged as powerful economic drivers thanks to their drive, skills, and ability as business owners. Women's contributions to economic growth are so substantial that we plan to study what influences women entrepreneurs in Pakistan. Information was gathered from 181 licensed SMEs in Pakistan using standardized questionnaires. The process involves the creation of a conceptual model and the use of SPSS & AMOS for statistical analysis. The findings show that women- owned businesses benefit from a combination of internal and external elements that contribute to their success. These factors include the desire for accomplishments, willingness to take risks, and confidence in one's own abilities. Based on the findings of this study, it is recommended that the Small and Medium Enterprises Development Authority (SMEDA), policymakers, and practitioners implement a number of incentives & supports tailored to women business owners so as to inspire them to sustain their operations over the long term. Although several studies have tested the impact of various factors on women's entrepreneurial success, ours explored some psychological, cultural, & religious elements that have received comparatively little attention, especially in Pakistan. The new research adds to the body of knowledge by providing pieces of empirical evidence that have previously been missing.

1. To evaluate women investors‘ perception & interpretation pertaining different investment options. 2. To determine the influences working women's investing decisions.

This study surveyed women in six large Indian cities to learn how they plan to invest in the future. Taking into account the goals of the study and other factors, a purposive sampling method was used to choose the sample, which includes only women who are employed, above the age of 21, and have investment experience of more than three years. These polls will shed light on the opinions & preferences of working women. The study has used both primary & secondary resources to compile its data. The combined information has improved the quality of our assessment of the decision-making process's affecting elements. Women in the beginning the item-generation process, a thorough literature research was conducted to frame constructs and determine their domain. The content validity of these items was tested and sent in. The surveying was split neatly into two halves. The data collection process had two stages: the pilot study in the beginning, and the final phase of data collection. There were three distinct data collection phases in both of these stages. In the first section, participants were briefed on the study's objectives and responsibilities. In the second part, participants were asked questions about the numerous elements that go into making investment choices. Literature review was used to determine the variables that informed all of the queries. The researcher used a five-point Likert scale to record responses since it worked well with the data analysis method (Hair et al., 2006). The last section gathered in-depth information about the population. Diverse national periodicals on investments serve as secondary resources for the study. A total of 2680 people participated in the survey. SPSS software version 24 was used to analyze the data. The questions in the poll were primarily concerned with exploring respondents' perspectives on the many considerations that go into making financial investments. By taking a practical approach, we were able to obtain information with high credibility and validity. Exploratory factor analysis is the method of statistics used in this investigation. Variability in a set of measured quantities can be explained by a smaller set of unmeasured characteristics using this statistical technique.

Respondents in the pilot study came from six different states in India. Each state was separated into four regions for the research. Each zone stands in for a different stratum: zone 1 represents the South Stratum, zone 2 represents the North Stratum, zone 3 indicates the West Stratum, and zone 4 represents the East Stratum. Both the pilot and final scale samples strongly supported an item-to-response ratio of at least 1:10, which was considered adequate. Pilot data included 700 participants and 25 items; final scale data included 2680 participants and 19 items. To exclude data that is thought to be logically incompatible, a preliminary content validity test is conducted (Hinkin, 1998). Content validity is ensured so long as there is consensus amongst experts that the samples are valid representations of the whole concept (Netemeyer et al., 2003). Three academics and two professional investment managers evaluated the items for content validity & suggested cutting a couple that they found unnecessary, redundant, or ambiguous. They also proposed varying the order of questions, how the answers were presented, and even how they looked. This process results in the removal of four items and the retention of 25 items for subsequent statistical examination. collected during the study period, these estimates are frequently used as benchmarks. The demographic make-up of a study's population is particularly crucial, especially when applying factor analysis. A thorough demographic analysis was performed to prevent any surprises during the data analysis phase. Respondents' ages, marital statuses, annual incomes, and professions are only a few of the variables broken down in Table 1. This figure shows that out of a total of 2680 respondents, 70% fall between the ages of 21 and 32, while only 5% fall in the older age bracket of 52 and up. Indicating that working women between the ages of 21 and 32 are more engaged in making investing decisions because they are more likely to be unmarried, have fewer responsibilities, and be willing to take more risks in pursuit of higher returns. The majority of respondents (52%) are now single, whereas over half of all female respondents (48%) are married. Sixty-six percent of those who responded were salaried professionals. And only 10% of people polled were engaged in anything but salaried work or self-employment. This demonstrates that salaried women, as opposed to self-employed or otherwise occupied women, are more likely to have confidence in making investment decisions. Salaried workers make larger investments overall because they are required to do so in order to qualify for tax breaks. The highest percentage of respondents (40%) came from households with an annual income of $3,600,000 to $7,000,000. And only 9% of people polled reported making more than $11,000,000.

Errors & inconsistencies might arise from data corruption or from incorrect data entry, so it's important to perform data cleaning to get rid of these problems. The study's data has been cleaned and screened, with inactive responses (1.6% of the total) removed. Data was not kurtotic or skewed, as indicated by the kurtosis and skewness measures. The VIF score used to test for multicollinearity was less than 3, indicating that the data are free of multicollinearity issues. The data passed the screening and could be used for further study. between many variables. This method is employed to reduce a large amount of data to a manageable number of summary variables and to probe the theoretical framework of a phenomenon. Since the researcher had no preconceived notions regarding the nature of the contributing components or the observable patterns, this method was employed.

As can be seen in Table 2, the KMO value is 0.798, meaning that there is a sizable enough sample to conduct the factor analysis. An insignificant chi-squared statistic of 980.390 indicates that the values are not dependent on one another and that multi-collinearity exists in the data. It's preferable if people live in more densely populated communities. All measured levels of togetherness are higher than 0.5. A variable with a low communality (between 0.0 & 0.4) finds it difficult to load considerably on any component. There is a substantial factor loading for each of the study's variables.

Total Variance Explained The Varimax rotation method was employed to extract the components. Since the variance is being redistributed, the factor loadings & percentage of variance across factors will change. The number of factors is determined by using eigenvalues. Table 3 shows that six of the factors (out of a total of 19) have Eigen values greater than 1. The main component has a value greater than 1 and can be used to derive the answer. The 62.477 percentage of total variation explained by these six factors is satisfactory, since it is greater than the minimum acceptable value of 50%.

Rotated Component Matrix The rotated component matrix, or factor loading table, can be seen in Table 4. It is essentially the end result of PCA. It includes predictions of the associations between the variables & calculated components. fourth factors each have five, three, and four such variables, respectively. Two variables each have a factor loading of greater than 0.5 on the fifth & sixth factors. On the basis of their inter-item correlation, a total of 19 independent variables have been combined into 6 components. Listed in Table 6 below are all of the established components & underlying variables that make them up. Similarly, the fact that all the variables are the same within the factor demonstrates that all the factors are different.

Reliability Analysis The researcher has chosen to use a self-designed survey. Therefore, it was crucial to put the questionnaire's trustworthiness to the test. For these 19 items, Cronbach's Alpha was 0.819, indicating high dependability. A Cronbach's Alpha score above 0.70 indicates that the items on the scale are reliable. Factor Analysis Outcomes Following the preceding procedures in exploratory factor analysis, six variables are found to be significant. The rotated component matrix serves as the basis for these variables. Attachment (Factor 1) had three elements with factor loadings between 0.73 and 0.76. The factor loadings for the five components making up Factor 2 (Informational Source) ranged from 0.50 to 0.72. The factor loadings of the three elements making up Factor 3 (Risk) ranged from 0.70 to 0.78. Four components with factor loadings between 0.65 and 0.75 made up Factor 4 (Additional Income). Items loading between 0.76 and 0.79 on Factor 5 (Life Satisfaction) represented the Quality of Life category. Two components, with factor loadings of 0.74 & 0.76, made up Factor 6 (Independent Decisions).

The findings will be presented in accordance with the research objectives described in the introduction, which should make the theoretical contribution of this research clearer. This research investigates the factors that influence investors' choices, focusing on the factors that influence women's trading decisions. This study demonstrates that modern-day female investors are as self-aware and knowledgeable as their male counterparts when it comes to making investing decisions. In order to ensure their financial future, 68% of respondents suggested looking into alternative investment options. The most important takeaway from this study is that modern women investors are risk takers, and that their views on less traditional investing vehicles like mutual funds have evolved favorably over time. Women investors prioritize independence and autonomy over attachment & informational sources when making financial decisions. The variance explained by factor attachment is 16.049%. Included in this category are things like one's level of expertise, degree of possessiveness over monetary choices, & emotional investment. The variance explained by the second source component is 11.889%. Friends' recommendations, broker recommendations, journal articles, magazine features, and family decisions all fall under this category. One more consideration is risk, which accounts for 9.89% of the total variance. Market conditions, a preference for government assets, and the perceived level of risk all play a role. Increased financial resources rank fourth, explaining 9.127% of the total variance. Income, returns, & consistency of any supplemental earnings fall within this category. With an R2 of 8.803%, quality of life ranks as the fifth identified factor. Considerations like affluence and quality of life fall under this category. The independent decisions component, which combines independent investment decision & independent about future, was found to account for the remaining 6.718% of the total variance. It is shown that all of these factors have some predictive power over different types of investments. The current research contributes equally to the academic and practical communities. From a scholarly perspective, it adds to the publicly available literature on the topic of investment management. Prospective researchers can now use the newly developed & validated scale to examine the factors that influence investment decisions. From a managerial perspective, the proposed study contributes in a number of ways. For example, with the help of the predictors found in this study, regulators & practitioners can access the local & global market by introducing schemes that are applicability in the real world, it is still an important piece of research. Despite these caveats, this fills an important vacuum by giving researchers a measurement tool that can be used to model intricate interrelationships between factors that influence investors' choices. The study's strengths also include its selection of states and the demographics of the samples within those states. This study will continue to expand in the future to include an examination of the influence of demographic factors like age, income, level of education, etc. on investing decisions, as these factors are crucial in influencing investors' choices. Factors revealed in this study can be evaluated across India to learn more about the investment mindset of Indian women. With only 2680 participants, this study cannot draw any firm conclusions about the factors that go into investors' choices. A larger sample size or other features that may be regarded significant in the Indian investment market are two ways to expand this study.

This studies found that income is simply one piece of the financial independence puzzle. A person's ability to put their money to good use is just as crucial. Taking financial control is especially important for working women because of the many unknowns in life & relationships. Each investor faces their own set of unique difficulties in the stock market. Understanding the various sorts of investors is crucial in light of the recent research into the investment habits of working women. The majority of women investors are taking risks, and they do so in their own unique ways. In addition, the study's conclusions were based on the characteristics that working women investors deemed important when making investment decisions. Investment choices are shown to be most affected by characteristics including attachment, information source, risk, supplemental income, quality of life, & autonomy of decision-making. Because of these considerations, they are able to make the necessary investments. That's why it's crucial for money managers to prioritize these factors if they want to attract and keep the support of women savers & investors.

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Qualified NET in Commerce in Dec 2018