Financial behaviour of individual investors: a segmentation approach.

Arora, Sangeeta ; Marwaha, Kanika

Introduction

Investing is not a game but a serious subject that can have major implications on an investor's future well being. Virtually everyone needs investments. Even if an individual does not select a specific investment, the participation is still made through pension plans, life insurance, saving schemes of post office and banks etc. Each of these investments has common characteristics such as potential return and the risk you must bear (Kabra et.al.2010). Today, the financial services and the economic sector are more highly diversified than ever. This diversification means that the individual investors have a wider range of investments and a greater choice of how to invest their money (Warren, et. al, 1990).

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"Only two things are infinite, the universe and human stupidity, and I am not sure about the former" Albert Einstein.

Investors trade not only for higher returns but for emotional reasons as well. An individual investor can't be assumed to be making rational decisions always and not being influenced by the psychological factors. So, this area of study that deals with investor's psychology is called behavioural finance. It tries to explain that how people forget the technical analysis and fundamentals and make investment decisions on the basis of their attitudes, emotions and opinions. Funfgeld and Wang (2009) suggested that research is needed to understand the underlying psychological factors and behavioural tendencies of different individuals and to investigate relationship between actual behaviour and change in attitudes and behaviour over an individual's life cycle.

Literature Review

Though a comprehensive literature review about behavioural finance involving study of segmenting investor's on basis of their attitudes and understanding investor behaviour in general is beyond the limitation of this paper, some well known empirical studies have been highlighted regarding investor's attitude towards investment decision.

Lease, Lewellen and Schlarbaum (1 974) focused on finding out who the individual investor is, how he makes his decisions, his dealings with his broker, and analysis of his asset portfolio among the U.S. investors. The responses portrayed that the investors followed a fundamental approach preferring a balanced and well-diversified portfolio of income, preferred long term capital appreciation securities with dividend income , instead of short-term gains. The factors such as age, income level and sex (in descending order) were found as dominant elements in effecting individual investor's behaviour regarding taking investment decisions and forming strategies. Warren et. al (1 990) studied the demographic characteristics as well as attitudes and opinions, which represent lifestyle characteristics of investor decisions and segmented the investors on such basis. The study helped the authors to differentiate between investor behaviour types i.e. active and passive investors and in addition, they were also able to differentiate between light and heavy investors in particular stock investments i.e. stocks and bonds. Wood and Zaichkowsky (2004) identified and characterized four main segments of investors i.e. risk intolerant traders, confident traders, loss-averse young traders, and conservative long-term traders based on their shared investing attitudes and behaviour and concluded that each segment purchased different types of stocks, used different information sources and had different levels of trading behaviour.

Murphy and Soutar (2005) used a conjoint analysis approach to identify the various share attributes that are valued by the Australian individual investors while making decisions regarding share purchases. The company management was found as the most important attribute followed by market status, price trend, source of recommendation, place of operation, dividend and others. In addition to this, the authors identified four segments of investors i.e. the explorers, the risk-averse investors, the traders and the contrarian investors that valued different share attributes and had different attitudes and preferences to investment alternatives with the help of cluster analysis and discriminant analysis.

Al-Tamimi and Kalli (2009) focused on identifying the relationship between the financial literacy and the investment decisions of the UAE individual investors. It was concluded that there was no significant difference in financial literacy on the basis of their age, employment and monthly income but there was a significant difference between financial literacy on the basis of gender, work activity and education level.

Reddy and Krishnudu (2009) examined the investment behaviour of the rural investors of the state of Andhra Pradesh. The authors studied the socio- economic profile of the investors to assess its impact on their investment habits, analyzed the awareness, preferences and experiences of investors in respect of various investment avenues. It was found that the majority of investors was quite unaware of corporate investment avenues like equity and preference shares, mutual funds, corporate debt securities and was highly aware of traditional investment avenues like real estate, bullion, bank deposits, life insurance schemes and small saving schemes.

Funfgeld and Wang (2009) examined the self-stated attitudes and behaviour of a variety of demographic groups regarding their everyday financial affairs. Principal factor analysis was used to determine the factors such as anxiety, interest in financial issues, intuitive decisions, precautionary saving and free spending revealing behavioural tendencies of different individuals. A two-step cluster analysis identified groups of investor's i.e. rational consumers, myopic consumers, anxious savers, intuitive investors and anxious spenders who shared common characteristics in attitudes and financial behaviour.

Kabra et. al (2010) the behaviour of various types of investors working in the government or private sectors in India and also on the basis of their annual income and annual amount invested by them. The major variables considered for the study were investing background, opinion, leadership, duration of investment, awareness of investments and security. The authors concluded that risk averse people opted for insurance policies, fixed deposits with banks, post office, PPF and NSC and the investor's age and gender affected their risk taking capacity.

Investor Segmentation

Segmenting of investor groups involves identifying homogeneous groups who behave differently to different financial instruments. The investment behaviour of individual investors is methodical and logical function of personal circumstances and hence attitudes. Investment attitudes result in selecting particular instruments in portfolio. When the target market is very large, companies usually resort to market segmentation based on variables like demographics, psychographics etc. However, due to intense competition, the basis for market segmentation is becoming increasingly complex. Hence, financial companies are turning to statistical methods for clustering individuals in a market which enables them to consider many varied and complex characteristics than would be possible without these methods (Kiran, et. al, 2004).

Need and Objective of the Study

The need for the study arises, as in Punjab, the research focusing on segmenting the investors on the basis of their investing attitudes has not been studied so far. So, the present study aims to fulfill the gap with following objective:

* To examine the extent to which individual investors in Punjab can be segmented based on their attitudes, together with their behavioural pattern and can be classified into clusters in order to identify group specific needs in financial affairs.

Research Methodology

The present study is mainly based on primary data collected from 1 20 respondents from Punjab which includes three districts i.e. Amritsar, Jallandhar and Ludhiana. These investors were interviewed through a pre-tested, well structured questionnaire which was administered personally. Convenience sampling technique was used keeping in view the socio-economic characteristics. Out of 1 20 questionnaires distributed, 1 00 completed questionnaires were received back. The cluster analysis has been applied to identify the group of individual investors in order to have insight into the enforcing of specific behaviour. Participants were first asked to give their self-assessment by answering 27 statements on their financial behavioural practice or attitude towards financial affairs. The response format is a five-point-Likert-type scale with "strongly agree" to "strongly disagree". Subsequently, the questionnaire contains questions concerning socio-demographic variables such as age, gender, educational qualification and income. Due to time constraints the sample of respondents was just 1 20, further study can be conducted by taking larger sample.

Cluster Analysis

Cluster analysis is a multivariate technique whose primary purpose is to group objects characteristics they possess. (Malhotra, 2002).Here, Cluster analysis is used as a means of representing the potential structure of data to identify groups of people who share certain common characteristics in attitudes and financial behaviour. The aim is to obtain clusters whose members are as similar in the cluster and at the same time, as distinct to the other clusters as possible (Funfgeld and Wang, 2009).

Null Hypothesis 1: All the respondents have similar attitudes towards making investment decisions.

Determination of Optimum Number of Clusters and Initialization Process

In the first step, a hierarchical cluster procedure with ward's linkage and squared Euclidean distances as the dissimilarity measure was used to identify the number of clusters and define group centroids. Such agglomerative procedure uses an algorithm that initially adds all the same combinations to the cluster. The agglomeration schedule is used to identify the number of clusters in the data. It. shows all possible solutions from 1 cluster to (n-1) cluster, where n is the number of respondents. Going up from the bottom of the agglomeration schedule, we looked at the column called coefficient to decide on the number of clusters. In this column, starting at the bottom, calculated the difference in the value of coefficient in neighbouring rows. In the study, the maximum value of the difference occurs between the third and the fourth row (from the bottom) coefficients indicating that there might be three clusters.

Once the number of clusters has been identified, a K-means clustering option is run on the data. The number of clusters identified above i.e. 3 is specified and the output is obtained. The final cluster centres for each variable are part of this output and are used to interpret the average values of each variable for a cluster and thereby describe the clusters.

Results and Discussion

The output is derived by first doing a hierarchical cluster analysis to find the number of clusters that exist in the data. The agglomeration schedule is used to identify the large differences in the coefficient. The agglomeration schedule from top to bottom indicated the sequence in which cases get combined with others until all 1 00 cases are combined together in one cluster at the last stage. Therefore, stage 99 represents a one- cluster solution, stage 98 represents a 2-cluster solution and stage 97 represents a three- cluster solution and so on going up from the last row the first row. The difference between rows in a measure called coefficient in column 4 is used to identify the number of clusters in the data. It is observed that there is a difference of (84.424-78.378 = 6.046) in the coefficients between the one -cluster (stage99) and the 2- cluster solution (stage98). The next difference is of (78.378-76.1 55 = 2.223) between stage 98 and stage 97. The next one after this is again a larger difference between stage 97 and stage 96 of 6.312(76.1 55-69.843). Thereafter, the differences are smaller between the subsequent rows of coefficients. Ignoring the first difference of 6.046 which would indicate only 1-cluster in the data, we look at the next largest difference between stage 97 and stage 96 indicating a 3-cluster solution

Results of K-means clustering

K-means clustering also known as quick clustering generally provides more stable clusters. This method needs a pre-specified number of starting points, to get an initial position, so that it is used in combination with stage 1. From the k-means partioning, the algorithm is run until convergence. The final cluster centres (table 1) describe the mean value of each variable. The final cluster centroids, cluster size with descriptive details and cluster name are shown in Table 1.

Through above discussion it is found that the null hypothesis 1 is rejected as there are three distinguished clusters formed instead of one cluster which reveals that respondents do not have similar attitudes towards making investment decisions. In lieu of literature review, Wood and Zaichkowsky (2004) identified and characterized four main segments of investors i.e. risk intolerant traders, confident traders, loss-averse young traders, and conservative long-term traders based on their shared investing attitudes and behavior. Murphy and Soutar (2005) identified four segments of investors i.e. the explorers, the risk-averse investors, the traders and the contrarian investors that valued different share attributes and had different attitudes and preferences to investment alternatives with the help of cluster analysis and discriminant analysis. Funfgeld and Wang (2009) used twostep cluster analysis and identified four groups of investors' i.e. rational consumers, myopic consumers, anxious savers, intuitive investors and anxious spenders who shared common characteristics in attitudes and financial behavior. Hence, using the final cluster centers', in the present study, three clusters are formed and interpreted in the terms of 27 original variables.

Cluster 1: Rational/Confident Investors

Investors belonging to this group are rational investors who agree to statements "I read business section of newspaper attentively", "I like to join conversations about financial matters", "I am anxious about financial and money affairs", "After making a decision, I am anxious whether I was right or wrong", "I compare and calculate risks". Such investors have deep concern for their future as they strongly agree to I statements "to care for future is essential for me" and disagree I to statement "I find it hard to save money for bad days". I These are risk takers as they agree to statement "I prefer I to take substantial risks in order to achieve substantial financial I gains from my investments" and disagree to "I consider myself I to be less inclined to take risks than the average investor". Such investors have high knowledge of investments as they strongly agree to statements "I understand the basic principles and I track my investments from time to time", "I have thorough knowledge of financial markets and economy and I closely track my investments and financial news" and agree to "I know a good deal about the various investment categories and accompanying risk levels", "I feel that I am substantially better informed than an average investor". So, such attitude shows that these investors are informative, risk takers, rational decision makers who make decisions after having thorough knowledge of their area of interest of investment. Such investors are less intuitive and more confirmative in their decision making as they are neutral towards statement "I get unsure by the lingo of financial experts", "At the end of the day, I decide intuitively in financial affairs". Besides this ,such investors like investing as they agree to statements "Special offers entice me into investing ", "I enjoy reading about results of product testing", "it is fun to compare I enjoy investing and look forward to such activity in future". Such investors are aggressive as they agree to "I feel annoyed when things don't go my way" and protest against wrong acts as they disagree to "I don't complain often, even if I have a reason to".

Cluster 2: Intuitive Investors

Investors belonging to this category are intuitive investors as such investors are quite inconsistent and unsure in their responses. Such investors either agree or are neutral towards the statements. They don't strongly agree, disagree or strongly disagree to any of the statements. They agree to statements "At the end of the day, I decide intuitively in financial affairs", "I am anxious about financial and money affairs.", "After making a decision, I am anxious whether I was right or wrong", "I read business section of newspaper attentively", " I like to join conversations about financial matters", "I compare and calculate risks", "To care for future is essential for me" , "Special offers entice me into investing", "I enjoy reading about results of product testing, it is fun to compare", "I feel annoyed when things don't go my way" " I enjoy investing and look forward to such activity in future", "I prefer to take substantial risks in order to achieve substantial financial gains from my investments", "I understand the basic principles and I track my investments from time to time", "I know a good deal about the various investment categories and accompanying risk levels". They are neutral toward statements "I get unsure by the lingo of financial experts", " I tend to postpone financial decisions", " I enjoy spending more than saving it", " I spend money when I am unhappy or frustrated", " I find it hard to save money for bad days", " Even on large purchases, I tend to spend spontaneously", " I don't complain often, even if I have a reason to", " I feel that I am substantially better informed than an average investor", " I consider myself to be less inclined to take risks than the average investor", " I feel that most individual investors are net losers", " I know very little about investments", " I know the basic principles but I don't know how to apply them to my personal situation", " I have thorough knowledge of financial markets and economy and I closely track my investments and financial news". The above responses reveal that investors falling in this segment reveal a moderate level of knowledge and seem to follow herd behaviour and their instinct in making investment decisions rather than following a rational procedure.

Cluster3: Conservative investors

Investors belonging to this category are conservative in their decision making. They are neutral to the statements "I read business section of newspaper attentively", "I get unsure by the lingo of financial experts", "I tend to postpone financial decisions", "At the end of the day, I decide intuitively in financial affairs", " I compare and calculate risks", " I spend money when I am unhappy or frustrated", " I find it hard to save money for bad days", "Special offers entice me into investing", " Even on large purchases, I tend to spend spontaneously", "I enjoy reading about results of product testing, it is fun to compare", "I don't complain often, even if I have a reason to", " I enjoy investing and look forward to such activity in future", " I feel that I am substantially better informed than an average investor", "I prefer to take substantial risks in order to achieve substantial financial gains from my investments", " I feel that most individual investors are net loser". Such statements show their leisurely nature of taking decisions. Such investors are risk averse as they agree to statement "I consider myself to be less inclined to take risks than the average investor" and disagree to "I prefer to take substantial risks in order to achieve substantial financial gains from my investments", "I compare and calculate risks". Such investors are conservative in nature as they do not take rational decisions and are not inclined towards gaining high knowledge of financial matters as they agree to statements "I know very little about investments", "I know the basic principles but I don't know how to apply them to my personal situation" and disagree to statements "I understand the basic principles and I track my investments from time to time", "I know a good deal about the various investment categories and accompanying risk levels", "I have thorough knowledge of financial markets and economy and I closely track my investments and financial news".

Results of ANOVA

The Anova table (Table-II) shows which of the 27 variables are significantly different across the three clusters. Null Hypothesis 2: There is no significant difference between three clusters across the 27 variables.

The last column in ANOVA table indicates that variables 1,2,3,4,5,7,8,9,10,12,15,18,19,20,21,22,23,24, 25,26,27 are significant at 0.05 level and null hypothesis is rejected i.e. there is significant difference between three clusters across these variables. The other variables i.e. 6,11,13,14,16,17 are not significant at 0.05 level i.e. there is no significant difference between three clusters across these variables. Similarly, the interpretation of clusters and differences across clusters were made on the basis of these variables, which were significantly different across clusters at 0.10 levels. The last column in ANOVA table indicates that variables 1,2,3,4,5,7,8,9,10,12, 15,18,19,20,21,22,23,24,25,26,27 are significant at 0.10 level (equivalent to 90 percent confidence level) as they have probability values less than 0.10. The other variables i.e. 6,11,13,14,16,17 having probability values more than 0.10 are not significant. However, the F-ratio report also summarizes the result of performing a one way ANOVA on each variable. The results help to investigate the importance of each variable in the clustering process. The most significant variables contribute most of the cluster solutions. The variables with largest F-value provide the greatest separation between the clusters. The variables as found significant i.e. 1,2,3,4,5,7,8,9,1 0,1 2,15,18,19,20,21,22,23,24,25,26,27 have high F-ratios and are considered to be the greatest separation variables between the clusters. And the variables found insignificant i.e. 6,11,13,14,16,17 have low F-ratios and are considered to be least separation variables between the clusters.

Cluster Differences by Socio-demographic Characteristics

Socio-demographic characteristics including age, gender, educational qualification and income show significant differences among the three clusters (Table-III). In each cluster, the distribution of male and female differ significantly. Among Rational/Confident investors, nearly 29 percent males are there whereas only 14 percent are female. On the other hand; women are over represented in each of the remaining two clusters which shows that women are less rational and more conservative and intuitive towards investment decisions. In terms of age , education level and income, rational investors are found among the age group of 26-45 years with high percentage of individuals being post graduate (nearly 24 percent) and earning above 40000 p.m. (nearly 33 percent) and 21000-30000 p.m. (nearly 29 percent). Investors belonging to the cluster Intuitive investors are among age group of 46 years and above (nearly 80 percent) having an educational qualification of post graduate (nearly 61 percent) and graduate (nearly 60 percent) and earning less than 20000 (nearly 72 percent) or 67 percent of them earning more than 40000. The third cluster "conservative investors" include individuals within the age group of less than 25(nearly 27 percent) who hold qualification other than being graduate and postgraduate (40 percent) and earning between 21 000- 30000 p.m. (nearly 25 percent).

Managerial Implications

The study segmented individual investors on the basis of their investment attitudes. The findings of the study would enable financial advisors to provide more effective advice to the investors according to their specific needs and provide different services to each sub-group. The "rational Investors" exhibit a prudent and considerate financial behaviour. The investors falling under this cluster manage the financial matters in a rational manner. They prefer adequate savings have high interest in financial issues, are risk takers, more confident, have high knowledge of investments. This cluster constitutes middle age group (26-45 years), well educated and earning good income investors and this factor leads to conclusion that male are more rational than woman as only in this factor male investors are more than females. So, the financial advisors should help them invest in high risk - high return investments after having a proper technical analysis. The cluster "intuitive investors" constitute the major share of respondents in the study (n = 60). It reveals that most of the respondents in Punjab make intuitive decisions. Such investors neither agree nor disagree to having high knowledge or interest in financial issues i.e. they reveal a moderate level of knowledge. Such investors make decisions following herd behaviour and follow their instinct. Financial advisors can help such investors to be more confident in making decisions by helping them invest in investments that can give them good returns by helping them follow a technical analysis before investing. The members of these segment are among age group of both above 40, post graduates, earning Rs. 40000 and above per month. The third segment i.e. "Conservative investors" includes young investors of age > 25 years, having qualification other than being graduates and earning less than 25000 per month. Such investors were found to be risk averse, have no interest and knowledge in financial issues. Such investors prefer investments with lowest risk with less return. High financial consultancy can provide such investors with broad spectrum to manage their financial affairs. The financial advisors should take into account these differences when communicating with different investor segments.

Conclusion

The study segmented the individual investors on the basis of their attitudes and behaviour towards making investment decisions in their day to day financial affairs. Cluster analysis segmented investors into three clusters with their specific characteristics in their day to day financial behaviour and related socio-demographic variables. Socio demographic variables show patterns of distribution in the clusters e.g. men are found more in the rational cluster, less in the irrational ones. In contrast women are found to fall more into other two clusters. From the clusters, it has been observed that there is a need for action to improve the handling of financial matters by the investors. Thus, this paper has implications for financial advisors who can take into account the differences among different segments to help them improve their financial decisions.

References

Funfgeld, Brigitte., & Wang, Mei. (2009). Attitudes and behaviour in everyday finance: Evidence from Switzerland. International Journal of Bank Marketing, 27 (2), 108-128.

Kabra, Gaurav., Mishra, Prashant, K., Dash, Manoj, K. (2010). Factors influencing investment decision of generations in India: An econometric study. Asian Journal of Management Research, 1 (1), 308-328.

Kiran, D., & Rao, U.S. (2004). Identifying investor group segments based on demographic and psychographic characteristics, Retrieved on October 8, 201 0 at http://ssrn.com/abstract=870749.

Lease, Ronald, C, Lewellen, Wilbur G., & Schlarbaum, Gary, G. (1974). The individual investor: Attributes and Attitudes, The Journal of Finance, 29 (2), Papers and Proceedings of the thirty-second annual meeting of the American finance association, New York, 413-433.

Malhotra, N.K. (2002). Marketing research: An applied orientation. New Delhi, India: Pearson education.

Murphy, Marilyn C, & Soutar, Geoffrey. (2005). Individual investor preferences: A segmentation analysis. Journal of Behavioral Finance, 6 (1), 6-14.

Warren, W. E., Stevens, R. R., & McConkey, W. C. (1990). Using demographic and lifestyle analysis to segment Individual Investors. Financial Analyst Journal, 46 (2), 74-77.

Table - I

Final Cluster Centers

                               Cluster

                               Rational    Intuitive   Conservative
                               Investors   Investors    Investors
Investor attitudes               N=21        N=60         N= 19

I read business section            5           4            3
of newspaper attentively

I like to join conversations       4           4            4
about financial matters.

I get unsure by the lingo of       3           3            3
financial experts

I am anxious about financial       5           4            4
and money affairs.

I tend to postpone financial       2           3            3
decisions.

After making a decision,           4           4            4
I am anxious whether I was
right or wrong

At the end of the day, I           3           4            3
decide intuitively in
financial affairs

I compare and calculate            4           4            3
risks.

I enjoy spending more than         2           3            4
saving it.

To care for future is              5           4            4
essential for me

I spend money when I am            3           3            3
unhappy or frustrated

I find it hard to save money       2           3            3
for bad days.

Special offers entice me           4           4            3
into investing

Even on large purchases, I         3           3            3
tend to spend spontaneously.

I enjoy reading about              4           4            3
results of product testing,
it is fun to compare.

I don't complain often, even       2           3            3
if I have a reason to.

I feel annoyed when things         4           4            4
don't go my way.

I enjoy investing and look         4           4            3
forward to such activity in
future

I feel that I am                   4           3            3
substantially better
informed than an average
investor.

I prefer to take substantial       4           4            2
risks in order to achieve
substantial financial gains
from my investments

I consider myself to be less       2           3            4
inclined to take risks than
the average investor.

I feel that most individual        4           3            3
investors are net losers.

I know very little about           2           3            4
investments.

I know the basic principles        2           3            4
but I don't know how to
apply them to my personal
situation

I understand the basic             5           4            2
principles and I track my
investments from time
to time.

I know a good deal about the       4           4            2
various investment
categories and accompanying
risk levels.

I have thorough knowledge of       5           3            2
financial markets and
economy and I closely track
my investments and financial
news.

Table - II

Results of ANOVA--Cluster Differences by Investor Attitudes

                                            Cluster        Error

                                          Mean          Mean
                                         Square   df   Square   df

I read business section of               9.059    2     .784    97
newspaper attentively

I like to join conversations about       2.944    2     .526    97
financial matters.

I get unsure by the lingo of             5.138    2     .953    97
financial experts

I am anxious about financial and         4.893    2     .606    97
money affairs.

I tend to postpone financial             8.901    2    1.084    97
decisions.

After making a decision, I am            1.794    2    1.041    97
anxious whether I was right or
wrong

At the end of the day, I decide          10.444   2    0.861    97
intuitively in financial affairs

I compare and calculate risks.           14.537   2     .649    97

I enjoy spending more than saving it.    15.066   2    1.367    97

To care for future is essential for me   1.546    2     .472    97

I spend money when I am unhappy          1.332    2    1.344    97
or frustrated

I find it hard to save money             9.346    2    1.055    97
for bad days.

special offers entice me into            1.598    2     .732    97
investing

Even on large purchases, I tend to       1.086    2     .845    97
spend spontaneously.

I enjoy reading about results of         2.336    2    0.671    97
product testing, it is fun to compare.

I don't complain often, even if I have   2.998    2    1.284    97
a reason to.

I feel annoyed when things don't         0.109    2    1.072    97
go my way.

I enjoy investing and look forward to    15.654   2    0.481    97
such activity in future

I feel that I am substantially better    16.623   2     .637    97
informed than an average investor.

I prefer to take substantial risks in    9.553    2     .740    97
order to achieve substantial financial
gains from my investments

I consider myself to be less inclined    22.985   2     .804    97
to take risks than the average
investor.

I feel that most individual investors    10.419   2     .962    97
are net losers.

I know very little about investments.    20.673   2    0.916    97

I know the basic principles but          24.079   2    0.851    97
I don't know how to apply them to my
personal situation

I understand the basic principles and    28.453   2     .508    97
I track my investments from
time to time.

I know a good deal about the various     24.466   2     .530    97
investment categories and accompanying
risk levels.

I have thorough knowledge of financial   41.691   2     .503    97
markets and economy and I closely
track my investments and financial
news.

                                                            Null
                                           F      Sig.   Hypothesis

I read business section of               11.552   .000    rejected
newspaper attentively

I like to join conversations about       5.596    .005    rejected
financial matters.

I get unsure by the lingo of             5.389    .006    rejected
financial experts

I am anxious about financial and         8.076     0      rejected
money affairs.

I tend to postpone financial             8.21 1    0      rejected
decisions.

After making a decision, I am            1.724    0.18    accepted
anxious whether I was right or
wrong

At the end of the day, I decide          12.125   .000    rejected
intuitively in financial affairs

I compare and calculate risks.           22.41    .000    rejected

I enjoy spending more than saving it.    11.02    .000    rejected

To care for future is essential for me   3.274    .042    rejected

I spend money when I am unhappy          0.991    .375    accepted
or frustrated

I find it hard to save money             8.858    .000    rejected
for bad days.

special offers entice me into            2.184    0.12    accepted
investing

Even on large purchases, I tend to       1.286    0.28    accepted
spend spontaneously.

I enjoy reading about results of         3.481    .035    rejected
product testing, it is fun to compare.

I don't complain often, even if I have   2.335    0.1     accepted
a reason to.

I feel annoyed when things don't         0.102    .903    accepted
go my way.

I enjoy investing and look forward to    32.547   .000    rejected
such activity in future

I feel that I am substantially better    26.116   .000    rejected
informed than an average investor.

I prefer to take substantial risks in    12.906   .000    rejected
order to achieve substantial financial
gains from my investments

I consider myself to be less inclined    28.587   .000    rejected
to take risks than the average
investor.

I feel that most individual investors    10.836   .000    rejected
are net losers.

I know very little about investments.    22.579   .000    rejected

I know the basic principles but          28.279   .000    rejected
I don't know how to apply them to my
personal situation

I understand the basic principles and    56.001   .000    rejected
I track my investments from
time to time.

I know a good deal about the various     46.148   .000    rejected
investment categories and accompanying
risk levels.

I have thorough knowledge of financial   82.856   .000    rejected
markets and economy and I closely
track my investments and financial
news.

Table - III

Cluster Differences by Socio-demographic Characteristics

                   Clusterl     Cluster2       Cluster 3
                    (n=21)       (n=60)         (n=19)

                    Rational    Intuitive     Conservative
                   Investors    Investors     Investors
Characteristies     N (%)         N (%)         N (%)

Gender

Male              14   (28.6)   27   (55.1)   8    (16.3)
Female            7    (13.7)   33   (64.7)   11   (21.6)

Age

>25 years         4    (13.3)   18   60.0)    8    (26.7)
26-35 years       10   (24.4)   24   (38.5)   7    (17.1)
36-45 years       4    (25.0    8    (50.0)   4    (25.0)
46 & above        3    (23.1)   10   (76.9)   0     (.0)

Education level

Undergraduate     0     (.0)    1    (100)    0     (.0)
Graduate          7    (17.5)   24   (60.0)   9    (22.5)
Postgraduate      13   (24.1)   33   (61.1)   8    (14.8)
Others            1    (20.0)   2    (40.0)   2    (40.5)

Income (Per Month)

>20,000           3    (9.4)    18   (66.9)   6    (23.7)
21,000-30000      8    (28.6)   13   (46.4)   7    (25.0)
31000-40000       7    (22.6)   18   (58.1)   6    (19.4)
40000& above      3    (28.3)   11   (71.7)   0     (.0)