A STUDY ON GENDER DIFFERENCES IN INVESTOR SAVINGS BEHAVIOUR (A STUDY WITH REFERENCE TO PUDUCHERRY AND TAMILNADU) Nandini PhD Scholar, Department of Commerce, Pondicherry University, Puducherry Malabika Deo Professor and Head, Department of Commerce, Pondicherry University, Puducherry ABSTRACT Every investor differs from others in many aspects predominantly because of demographic factors which includes socio-economic background, educational attainment level, age, race and sex. The investor always desires to make an optimum investment decision so as to get the maximum of the investment. Thus, an optimum investment decision plays a vital role in economic activities of a person and deserves a significant consideration. However, it is presumed that psychological factors influence investment decision and the behavioral finance has become an integral part of the decision making process, because it heavily influences investor s decision. There is no denial of the fact that man differ from women with regard to psychological state of mind, who is prone towards taking high risk etc., Whether these differences also are seen in investment decision making or as rational investment decision presupposes that all human beings are rational and all behave in similar manner when economic activities are considered in a question to be probed into. This paper attempts to find out the gender differences in investment behavior in terms of demographic character and the respective savings behavior. The demographic variables, such as age, martial status, education, occupation and income whether affect investor s decision making and the investor savings and investment regularity are typical of gender are the crux of this study. A detailed investigation reveals, there is a significant difference between gender demographics which affects investment decisions. Keywords: Investment decision, savings behavior, gender 22
INTRODUCTION Behavioral Finance is a new emerging science that blends psychology with strict conservative finance to explain the rational behavior of investors. It is commonly defined as the application of psychology to understand human behavior in finance or investing. It is the study of market that draws on psychology, throwing more light on why people buy or sell the stocks as well as why they decide otherwise. Based on the behavior of investors, their investment style, choice, pattern, decision making etc., differ at the time of investing. Mainly how the gender plays a major role in investment behavior is the central focus of the study. Behavioral Finance is becoming more popular in the study of investments as investor s decision making heavily influences investor s performance and is more psychological. As psychologically male and female differ in many aspects, the crux of this study is to know whether there is also difference in the investment behavior among gender. The findings of this study can give better insight as regards to how normally investments are done and how the demographics variables have effect on the decision making of respective gender. NEED OF THE STUDY The need of the research is to examine, whether there exists a gender differences in any of the socioeconomic factors of the investors and in their monthly savings and investments. Every investor differ from others in all aspects due to various factors like demographic factors which includes socio-economic background, educational attainment level, age, race and sex. The most crucial challenge faced by the investors is in the area of investment decisions. An optimum investment decision depends heavily on the factors taken into consideration by different investors. Strict financial dictum presupposes that all investors are rational and behave same and consider similar factors in their decision making which behavioral finance contradicts emphasing the psychological make up of investors influencing the investment decision which may possibly be conditional to the demographics factors. This paper has explored the association between demographics factors and gender in investment decisions and also in investor savings. The findings of the study can give better insight as regards to how normally 23
investments are done and how the demographic variables have effect on the decision making of respective gender. REVIEW OF LITERATURE The present research work has built up its analysis on the base of earlier researches done in the same area. Sunden and Surette (1998) used data from the 1992 and 1995 SCF to investigate individual investment in DC plans and found that women are less likely to have a defined contribution (DC) plan than men and both gender and marital status significantly affect the actual allocation of assets. They also found that neither age nor education seems to affect the investment decision. Olsen and Cox (2001) conducted a unique study which investigated the risk/gender differences for professionally trained investor. It was found that women investors weight risk attributes such as possibility of loss and ambiguity more heavily than their male colleagues. It also revealed that women tend to prefer lower risk assets than men. Barber and Odean (2001) found evidence of overconfidence, among men, in comparison to women. They found that men invest more in equities and trade more actively than women. In addition, married investors hold more investment in equities than their single counterparts. Further, investors who earn higher salaries tend to be more aggressive in their allocations and tend to trade more often. They also reported that age induces investors to allocate less to equities and to rebalance more frequently. Felton, Gibson and Sanbonmatsu (2003) examined the role of gender and optimism in determining the preference for risk in investment choice of students. The analysis suggested that males make more risky investments choices than females, and this difference was mainly due to riskier choices made by optimistic males. Watson and McNaughton (2007) find that after controlling for age, income and education; women choose more conservative options than men. Croson and Gneezy (2009) reviewed the literature on gender differences and identified differences in risk preferences, social preferences and competitive preferences. Mittal, Manish and Vyas R K (2011) investigated whether women are more risk-averse than men and the reasons suggested by psychologists for the same. Psychologists suggest that women lack confidence and are more methodical in their information processing and accumulation style. The study indicated that men 24
engage in more risk-taking and are more overconfident than women. Kathuria, Lalit Mohan and Singhania, Kanika (2012) found out that male and female respondents were using magazines, internet and TV channels as the three most important sources of awareness regarding various investment alternatives. Also, advice of parents and spouse were rated as the most important factor that influences the investment decision of female respondents. Bhushan, Puneet and Medury, Yajulu (2013) studied the gender differences in Investment Behaviour among employees and revealed that the respondents invested money in almost all investment avenues available to them. Significant gender differences were noticed in investment preferences for health insurance, fixed deposits and market investment. R.BanuReka (2014): analysed the difference between gender investors with respect to investment products and also the effect of age on investment choice. The conclusion of the study was that there exist significant difference between the choice of investment products and equity products between gender investors DATA AND METHODOLOGY 1. Objective of the Study The present paper is developed on the basis of a set of objectives such as, To investigate the existence of gender differences in demographic variables and investor savings. To study the association between the demographics variables and gender in investment decisions. To study the association between the investor savings and gender. Based on the objective of the study, the following hypotheses were formulated: 1. There exist no significant difference between gender wise and demographics variables. 2. There is no significant difference between genders with respect to their savings. 2. Data Analysis The data were collected through a structured questionnaire survey of 380 investor from the union territory of Pudhucherry and Tamilnadu State, of which only 320 responses were 25
finally considered for the study. The respondents were selected using snowball random sampling method. Percentage and Chi-Square test were applied for data analysis. The analysis of the data was carried out using Statistical Package for the Social Sciences (SPSS) 17.0 windows. ANALYSIS I. Socio Economic Details: Looking at the socio economic profile of the respondents figures in table1, it was observed that out of five age groups, majority (66%) of the male respondents were more than 26 years, whereas approximately 34% of female respondents were more than 26 years of age. The maximum respondents belong to age more than 26 but less than 35 years. While we find the respondents in the age group of 26 to 35 years generally are more spirited investors, female respondents are more in percentage in this group when compared to other age groups. While majority of the respondents are unmarried, in male category it is 70% and among female it is 25%. Unmarried male make investment more than female and in married group female make investments more in comparison to male. Regarding the education, options are given as Master Degree, Bachelor degree, Vocational or technical, higher secondary or equivalent and middle school. Most of the respondents in male (89%) have completed bachelor degree while 44% of the respondents in female have completed their Masters degree. In an overall observation of investor s education profile both male and female are equally educated. In occupation there are five category viz., Professional, Business, Employee, Retired and Others. Majority of the respondents are in others category which include traders, agriculture, etc.,(36.25%). The female respondents in other category and employee are investing more when compared to rest of the categories of occupation. In income, majority are males (60%) when compared to females who are investing their income, and majority belong to the income group 10001 to 20000. The remaining income groups are females invest more. The overall data is depicted in TABLE 1. 26
Table 1: Socio Economic Details VARIABLE MALE FEMALE TOTAL N % N % N % Gender 229 72 91 28 320 100 Age Upto 25 years 6 16.2 31 83.8 37 11.56 26 to 35 years 105 66 54 34 159 49.68 36 to 45 years 70 92.1 6 7.9 76 23.75 46 to 55 years 19 100 0 0 19 5.93 55 & Above 29 100 0 0 29 9.08 Marital Status Married 35 64.8 19 35.2 54 16.87 Unmarried 194 72.9 72 27.1 266 83.13 Education Master Degree 61 56 48 44 109 34.06 Bachelor Degree 79 89.8 9 10.2 88 27.5 Vocational/Technical 23 69.7 10 30.3 33 10.31 High School/Equivalent 34 77.3 10 22.7 44 13.75 Middle School 32 69.6 14 30.4 46 14.36 Occupation Professional 23 69.7 10 30.3 33 10.31 Business 66 100 0 0 66 20.62 Employee 55 58.5 39 41.5 94 29.38 Retired 11 100 0 0 11 3.44 Others 74 63.8 42 36.2 116 36.25 Income Below 10000 28 59.6 19 40.4 47 14.68 10001-20000 141 72.7 53 27.3 194 60.62 20001-50000 39 67.2 19 32.8 58 18.13 Above 50000 21 100 0 0 21 6.57 (Source: Primary data) 27
Age: Age is considered as the first demographic factor in investment. Different age groups people think differently and take decision based on risk, knowledge and their experience. The age factor may influence differently both the young and grown up to invest their money in shares in different proportion. The younger person like to earn money quickly within a short period so they invest in business. The elder person may invest to maintain capital appreciation and steady income. From table 2 it is clear that the age group from 26 to 35 years are making high investment wherein among female respondents this age group is prominent when compared to other age groups. The most active investors among male are in 26 to 45 and among female the suitable age is upto 35 years. When we see the total investor group we find investment in shares is more prominent among people under the age of 45. Based on these age groups gender-wise tabulation is presented below in Table 2. Table 2: Gender Wise Distribution Based On Age Age Male Female Total N % N % N % Upto 25 years 6 2.620 31 34.07 37 11.56 26 to 35 years 105 45.85 54 59.34 159 49.69 36 to 45 years 70 30.57 6 6.59 76 23.76 46 to 55 years 19 8.30 0 0 19 5.94 55 & Above 29 12.66 0 0 29 9.06 Total 229 100 91 100 320 100 (Source: Primary data) Table 2.1: Chi- Square Results - Association Between Gender And Age Value Df Asymp. Sig. (2-sided) Pearson Chi-Square 92.912 a 4.000 Likelihood Ratio 103.554 4.000 Linear-by-Linear 68.695 1.000 Association N of Valid Cases 320.0 cells (.0%) have expected count less than 5. The minimum expected count is 5.40. 28
Chi-Square test was undertaken to check the significant differences between genders with regard to age. The null hypothesis was that there is no significant difference between gender and age. The results revealed that the asymp.sig is less than 0.05 (.000). Hence, null hypothesis is rejected. Therefore, there is a significant difference between gender and age as far as investment is considered. Marital Status: Whether the investment habit among gender changes with marital status? To find answers to this question the data was analysed in terms of marital status. The marital status included two options viz., Married and Unmarried. Gender wise and marital status wise respondent involves investment more were tabulated in table 3. It revealed that majority of the respondents 266(83.12%) were unmarried, out of 320 overall were unmarried. In this group the proportion of male respondents was as high as 194 (84.72%) out of 229 slightly higher compared to female 72(79.12%) respondents out of 91 in total. However among married, female respondents were slightly higher 19(20.88%) than married male 35 (15.28%) respondents. In general, unmarried male make investment more than female and in married female make investments more. Table 3: Gender Wise Distribution Based On Marital Status Marital Status Male Female Total N % N % N % Married 35 15.28 19 20.88 54 16.88 Unmarried 194 84.72 72 79.12 266 83.12 Total 299 100 91 100 320 100 (Source: Primary data) 29
Table 3.1: Chi- Square Results - Association Between Gender And Marital Status Value Df Asymp. Sig. (2-sided) Pearson Chi-Square 1.453 a 1.228 Continuity 1.082 1. 228 Correction b Likelihood Ratio 1.406 1. 228 Fisher's Exact Test.248.149 Linear-by-Linear 1.449 1 229 Association N of Valid Cases 320 a.0 cells (.0%) have expected count less than 5. The minimum expected count is 15.36 ; b. Computed only for a 2*2 table To test the significant differences between gender and marital status chi-square analysis was undertaken, for the null hypothesis there is no significant difference between gender and marital status. The result arrived in Table 3.1 revealed that the asymp.sig is more than 0.05 (.228). Therefore, there is no significant difference between gender and marital status with regard to investment decisions. Education: The third element in socio-economic characteristics is education. The level of education is an important one which may influence the investment decisions of the investors. Education makes a person more confident and strong, which results in making investment more rational decision like low risk more return. To stay in stock market one should have the knowledge about it, otherwise it will be difficult to survive in the stock market. Investor Beware should be the golden rule here, in order to invest in it. Those who know the rule of game in stock market can play effectively. As there are many factors like demographic condition, political condition etc., education level may help investor to make good judgment and play the game effectively. Based on this, education is divided into five category viz., Master degree, Bachelor Degree, Vocational Technical, High School or Equivalent and lastly Middle School. The data collected is tabulated in table 4. 30
Table 4: Gender Wise Distribution Based On Education Education Male Female Total N % N % N % Master Degree 61 26.64 48 52.75 109 34.06 Bachelor Degree 79 34.50 9 9.89 88 27.5 Vocational/Technical 23 10.04 10 10.99 33 10.31 High 34 14.85 10 10.99 44 13.75 School/Equivalent Middle School 32 13.97 14 15.38 46 14.38 Total 229 100 91 100 320 100 (Source: Primary data) From the above table 4 it is evident that the female are high 48(52.72%) in Master Degree, followed by 14(15.38%) in Middle school and10 (10.99%) in Vocational or technical where as male have high responses in Bachelor degree 79(34.50%) followed by higher secondary education 34 (14.85%). In both gender group investors were found more, in higher education groups. Table 4.1: Chi- Square Results - Association Between Gender And Education Value Df Asymp. Sig. (2- sided) Pearson Chi-Square 28.224 a 4.000 Likelihood Ratio 30.280 4.000 Linear-by-Linear 2.577 1.000 Association N of Valid Cases 320 a.0 cells (.0%) have expected count less than 5. The minimum expected count is 9.48 To test the significant differences between gender and education, chi-square analysis was undertaken. The null hypothesis was that there is no significant differences between gender and education. The result as depicted in Table 4.1 revealed that the asymp.sig is less than 0.05 (.000). Hence, null hypothesis is rejected. Therefore, there is a significant difference between gender of investors and education level. 31
Occupation: Occupation is the next element in socio economic characteristics. Even though education is necessary but income and investments depend more on occupation. It is the key factor as regards to the investment and the extent of risk the investor can take. There are certain occupations, which force the people to go in for extra earnings, and there are certain occupation, which expose the investors to the stock market activity, and hence the occupational influence on the investment decisions needs an analyses. Presently, occupation is classified into five groups viz., Professional, Business, Employee, Retired and Others. presented in Table 5. Table 5: Gender Wise Distribution Based On Occupation Respondents occupational profile Occupation Male Female Total N % N % N % Professional 23 10.04 10 10.99 33 10.31 Business 66 28.82 0 0 66 20.63 Employee 55 24.01 39 42.86 94 29.38 Retired 11 4.82 0 0 11 3.44 Others 74 32.31 42 46.15 116 36.25 Total 229 100 91 100 320 100 (Source: Primary data) It is evident from the above table 5, that out of total 320, 116 (36.25%) belong to others (include unemployed housewives, traders, students, research scholars etc.,) invest more, in which female respondents are high 42(46.15%) out of 91 when compared to male respondents 74 (32.31%) out of total 229. Then employees like engineers, teachers, medical practioners etc., are 94(29.38%) in which female investor respondents are more 39(42.86%) than male 55 (24.01%) respondents. The next occupation of investor is business where only male were found to be existant, i.e 66(28.82%). In fourth place comes professionals who are working based on their knowledge and skills their number was 33(10.31%) of which male were 23 (10.04%) which was higher than number of female respondents 10(10.99%) but percentage wise both genders were same. The last category in occupation is retired where their earnings are not there, they have to depend on their 32
pension who did show least interest investment in shares as seen only 11(3.44%) male respondents are investing 11(4.82%) and no female is there in this category. Overall the female respondents are more in others category and more female employee are investing compared to male and male are more only in the professional, business, retired group. Table 5.1: Chi- Square Results - Association Between Gender And Occupation Value df Asymp. Sig. (2- sided) Pearson Chi-Square 41.964 a 4.000 Likelihood Ratio 62.177 4.000 Linear-by-Linear 8.122 1.004 Association N of Valid Cases 320 a.1 cells (10.0%) have expected count less than 5. The minimum expected count is 3.13. To test the significant differences between gender and occupation, chi-square analysis was undertaken. The null hypothesis was that there is no significant difference between gender and occupation. The result is depicted in Table 5.1. Based on the result, which shows asymp. sig. is less than 0.05 (.004) rejecting the null hypothesis was rejected. Therefore, the inference drawn is that there is significant difference between gender and occupation. Income: The income is the main source of investment. Depending on the earning capacity, the investment differs. Whatever is their income, a small portion of money gets invested by all category of people. After analyzing the investment behavior of the investors on the basis of the occupation, the influence of the income may also be considered as a determining factor i.e., only the people who have high disposable income can save more and it is only the people who have more marginal propensity to save can invest more, Therefore the influence of the income of the investors was analysed. To get the information in this regard four options were given to 33
respondents i.e., below 10000, 10001 to 20000, 20001 to 50000 and above 50001. The profile data is presented in table 6. Table 6: Gender Wise Distribution Based On Income Income Male Female Total N % N % N % Below 10000 28 12.23 19 20.88 47 14.69 10001-20000 141 61.57 53 58.24 194 60.62 20001-50000 39 17.03 19 20.88 58 18.13 Above 50001 21 9.17 0 0 21 6.56 Total 229 100 91 100 320 100 (Source: Primary data) Table 6 reveals that income group between, 10001 to 20000 are investing more i.e., 194 (60.62%) out of 320. Among total, male respondents are more 141(61.57%) out of total 229, compared to female respondents 53 out 91 (28.24%). Then the income group between 20001 to 50000 amounted 18.13% and the female were investing more than the proportion of male i.e., female 20.88% and male respondents 17.03%. The third place in income group was below 10000 which have 47 (14.9%) respondents where percentage of female were 20.88% higher than male respondents 12.23%. The last income group above 50001 is the least 21(6.56%), where only male respondents 21(9.17%) were there and there were no female in this category. Overall both male and female were found equally investing in all the categories of income except above 50,000. Table 6.1: Chi- Square Results - Association Between Gender And Income Value Df Asymp. Sig. (2-sided) Pearson Chi-Square 12.315 a 3.006 Likelihood Ratio 17.790 3.000 Linear-by-Linear 6.174 1.013 Association N of Valid Cases 320 a.0 cells (.0%) have expected count less than 5. The minimum expected count is 5.97. 34
To test the significant differences between male and females respondents with their income, chisquare analysis was undertaken. The results in table 6.1 revealed that there is significant difference between gender and income with.013 asymptotic significance. II. Investors Savings And Investment Behavior In this section Investors Savings and their behavior regarding investment has been analysed. Normally a part of a earnings is saved by individuals for future needs. The savings made is not kept idle, instead in order to get return from it in future, it gets invested. Savings are made for many reason accordingly, the saved amount should be appropriately invested. They are many investment avenues where one can park one s saving. But regularity in savings and investment is always better for every individual. The information depicted in table 7 reveal the savings and investment behavior of the respondents. Table 7: Investors Savings And Investment Behavior VARIABLE MALE FEMALE TOTAL N % N % N % Gender 229 72 91 28 320 100 Monthly Savings Below 5000 143 88.3 19 11.7 162 50.63 5001-10000 39 42.4 53 57.6 92 28.75 10001-15000 21 100 0 0 21 6.56 15001-20000 9 100 0 0 9 2.81 Above 20001 17 47.2 19 52.8 36 11.25 Monthly Investment Below 5000 151 67.7 72 32.3 223 69.69 5001-10000 39 100 0 0 39 12.19 10001-15000 12 100 0 0 12 3.75 15001-20000 17 47.2 19 52.8 36 11.25 Above 20001 10 100 0 0 10 3.12 Investment Regularity Regularly 115 55.8 91 44.2 206 64.38 Wait for an Opportunity 62 100 0 0 62 19.37 Only when I have surplus money 52 100 0 0 52 16.25 35
Investment Motivation Family 73 100 0 0 73 22.81 Friends 40 35.7 72 64.3 112 35 Consultant 14 100 0 0 14 4.38 Self 98 83.8 19 16.2 117 36.56 Others 4 100 0 0 4 1.25 (Source: Primary data) From the above table 7, the results revealed that in monthly savings, the male respondents are saving more money monthly than female. The majority of savings of monthly 5000 or less is done by male 143 (62.45%) and in female 19(20.85%). The monthly investment are regularly made by male respondents more when compared to female and majority of the respondents are making monthly investment below 5000, i.e., 223(69.69%) out of 320 are making monthly investments below 5,000. In this category, the male respondents are 151(65.93%) out of 229 total male and 72(79.12%) out of 91 are female. In regularity of investments 115( 50.22%) out of 229 are male respondents. Interestingly, female respondents 91(100%) are making regular investments. More than 50% of the male respondents are making investment only when they find opportunity and only when they have surplus money. Majority of the respondents, investing mostly out of their own interest, belong to male category, whereas females are motivated by self and friends only. Monthly Savings: Today savings is a way to begin an investment program in order to increase the standard of living and get more income in future. The amount an investor invests depends on his income, as well as his attitude towards saving and thrift. A part of the earnings should be kept as savings. Savings should become a habit as it will be useful for the future emergencies. To analyse the effect of monthly savings of the respondents, the savings pattern of the respondents was studied. The monthly savings were categorized as follows. Upto Rs.5000, 5001-10000, 10001 to 15000, 15001 to 20000 and above 20001. As the study is based on gender, the data is tabulated based on gender and shown in table 8. 36
Monthly Savings Table 8: Gender Wise Distribution Based On Monthly Savings Male Female Total N % N % N % Below 5000 143 62.45 19 20.85 162 50.63 5001-10000 39 17.03 53 58.24 92 28.75 10001-15000 21 9.17 0 0 21 6.56 15001-20000 9 3.93 0 0 9 2.81 Above 20001 17 7.42 19 20.88 36 11.25 Total 229 100 91 100 320 100 (Source: Primary data) It is evident from table 8 that the highest monthly savings are below 5000, i.e., out of overall total 320, 162 (50.63%) respondents are saving monthly. The majority of savings below 5000/- is done by male 143 (62.45%) and among female 19(20.85%). The second highest monthly savings is between 5001 to 10000 and the number of respondent are 92(28.75%). In this group female numbers are more i.e., 53(58.24%) when compared to male which is 39(17.03%). The third place in monthly savings is above 20001, the total respondents are 36(11.25%), of which female are 19 (20.88%) significantly more than male 17 (7.42%). The fourth place in monthly savings is between 10001 to 15000, having 21 (6.56%) respondents and the last category in monthly saving is between 15001 to 20000, in which the total respondent are 9(2.81%). The former and the latter category of monthly savings have only male respondents. The overall conclusion is that male are saving more money monthly than female. Table 8.1: Chi- Square Results - Association Between Gender And Monthly Savings Value Df Asymp. Sig. (2-sided) Pearson Chi- 83.097 a 4.000 Square Likelihood Ratio 89.790 4.000 Linear-by-Linear 16.136 1.000 Association N of Valid Cases 320 a.1 cells (10.0%) have expected count less than 5. The minimum expected count is 2.56. 37
To test the significant differences between gender and monthly savings, chi-square test was employed. The result (table 8.1) revealed that the asymp. sig is less than 0.05(.000), indicating there is a significant difference between gender in the aspect of monthly savings. Monthly Investment: The income earned, is saved for future needs. The saving amount instead of being kept idle need to be invested properly for a good return. So proper planning is necessary for a safe investment. The study has analyzed the amount of investment made monthly in the stock market under different categories such as below 5000, 5001 to 10000, 10001 to 15000, 15001 to 20000 and above 20001. The same is tabulated in table 9. Table 9: Gender Wise Distribution Based On Monthly Investment Monthly Investment Male Female Total N % N % N % Below 5000 151 65.93 72 79.12 223 69.69 5001-10000 39 17.03 0 0 39 12.19 10001-15000 12 53.24 0 0 12 3.75 15001-20000 17 7.42 19 20.88 36 11.25 Above 20001 10 4.38 0 0 10 3.12 Total 229 100 91 100 320 100 (Source: Primary data) The above table (table 9) reveals that the monthly investment under below 5000 category, female respondents are more numbering 72(79.12%) than male 151(65.93%). In the remaining monthly investment ranging from 5001-10000, 10001-15000 and above 20001 have only male respondents. Overall, the male are making monthly investments regularly. 38
Table 9.1: Chi- Square Results - Association Between Gender And Monthly Investment Value Df Asymp. Sig. (2- sided) Pearson Chi-Square 35.878 a 4.000 Likelihood Ratio 51.098 4.000 Linear-by-Linear.049 1.825 Association N of Valid Cases 320 a.2 cells (20.0%) have expected count less than 5. The minimum expected count is 2.57. Chi Square result (table 9.1) to test the significant differences between gender and monthly investment, reveal that the asymp. sig is more than 0.05(.825). Therefore, there is no significant difference between gender and monthly investment pattern. Investment Regularity: To analyze the intensity of the involvement of the investors to the investment in stock market, the regularity or otherwise of the investment of the sample respondents was attempted. Regularly investing every month or at set periods throughout the year can pay off. It takes the emotion out of investing as one don t have to worry about when to enter the market, and just have to be confident that bad months will be outweighed by good ones over the long-term. The options given to the respondents were, Do you make investment regularly? or Wait for an Opportunity or Only when I have surplus money. The data has been tabulated in table 10 gender wise. Table 10: Gender Wise Distribution Based On Investment Regularity Investment Male Female Total Regularity N % N % N % Regularly 115 50.22 91 100 206 64.38 Wait for an 62 27.07 0 0 62 19.37 Opportunity Only when I have 52 22.70 0 0 52 16.25 surplus money Total 229 100 91 100 320 100 (Source: Primary data) 39
The above table reveals that majority of the respondents make regular investments 206(64.38%) out of 320. 115( 50.22%) out of 229 are male respondents who make regular investment. However, all female respondents 91(100%) are making only regular investments. Around 50% of the male respondents are making investment by waiting for an opportunity and only when they have surplus money. Table 10.1: Chi- Square Results - Association Between Gender And Investment Regularity Value Df Asymp. Sig. (2- sided) Pearson Chi-Square 70.371 a 2.000 Likelihood Ratio 99.330 2.000 Linear-by-Linear 59.362 1.000 Association N of Valid Cases 320 a.0 cells (.0%) have expected count less than 5. The minimum expected count is 14.79. To test the significant differences between gender and investment regularity, chi-square test is undertaken. From the table 10.1, the result revealed that the asymp. sig is more than 0.05(.000), indicating that, there is a significant difference between gender and investment regularity of respondents. Investment Motivation: Investment is an art. There are so many factors which influence the investors to invest their money in stock market. The extent of knowledge of the investors in investment decisions can be analyzed from the factors that influence the investment decisions. There may be a motivator behind every individual who are instrumental in guiding the investor to invest. In this study a question was asked who motivated you to invest in stock market and the options were family, friends, consultant, self and others. The results are tabulated in table 11. 40
Table 11: Gender Wise Distribution Based On Investment Motivation Investment Motivation Male Female Total N % N % N % Family 73 31.88 0 0 73 22.81 Friends 40 17.47 72 79.12 112 35 Consultant 14 6.11 0 0 14 4.38 Self 98 42.79 19 20.88 117 36.56 Others 4 1.75 0 0 4 1.25 Total 229 100 91 100 320 100 (Source: Primary data) It is crystal clear from the table 11that majority of the respondents are self motivated 117(36.56%) out of 320 in which male who have responded that they are self motivated are 98(42.79%) and female 19(20.88%). The number those are motivated by their friends are 112(35%) out of 320 in which female highly motivated by their friends numbered 72(79.12%), where as male 40(17.47%). Family, consultant and others motivated male only, no women responded being motivated under then said category. Overall, self motivation was the highest among both male and female. Female are motivated by self and friends only. Table 11.1: Chi- Square Results - Association Between Gender And Investment Motivated Value Df Asymp. Sig. (2- sided) Pearson Chi-Square 12.315 a 3.006 Likelihood Ratio 17.790 3.000 Linear-by-Linear 6.174 1.013 Association N of Valid Cases 320 a.3 cells (30.0%) have expected count less than 5. The minimum expected count is 1.14. Chi Square test result presented in table 10.1 indicates, there is a significant difference between gender and investment motivation of respondents. 41
CONCLUSION The conclusion drawn from the gender wise analysis made in the study indicates that among all socioeconomic characteristics considered age, marital status, education, occupation and income, have different effect on male and female as far as their savings and investment behavior is concerned. Age, marital status, and income, play a significant role for female differentiating them from men. In education and occupation male and female are equally distributed. It was observed that there is a significant difference between gender and all demographic variables, like age, education, occupation, income except marital status. The results find support of the earlier researchers Mittal, Manish and Vyas R K (2011) observed that there is no association between demographic variables like gender, age, marital status, occupation and household income and investment choice, whereas there is a significance association between qualifications and investment choice of occupants in financial services industry. Regarding the savings and investment behavior, majority of the male respondents are saving more money monthly and regularly than female and they are motivated by self whereas female are motivated by self and friends. Kathuria, Lalit Mohan and Singhania, Kanika (2012) found that advice of parents and spouse were rated as the most important factor that influences the investment decision of female respondents. The result of the chi-square test reveals that there is significant differences between gender and investor savings such monthly savings, monthly investment, investment regularity and investment motivation. REFERENCES 1. Sunden, Annika E., and Brian J. Surette. 1998. "Gender Differences in the Allocation of Assets in Retirement Savings Plans." American Economic Review 88: 207-11. 2. Barber, Brad, and Terrance Odean. 2001. Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics 116 (1):261-292. 42
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