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Investors' perception towards capital market operations--an empirical study.
Abstract:
The economic development of a country depends upon the size and extent of the economic activity in the country, which need capital to carry out the activities. So investment culture is to be developed among the public to motivate them to select corporate securities as their investment avenue. The creation of investment culture can be effectively done by understanding the factors influencing the capital market operations. So, this study focuses its attention to identify the major factors that help the creation of investment culture and related activities by the policy makers and capital issuers.

Authors:
Devi, S. Renuga
Bharathi, N.
Pub Date:
07/01/2008
Publication:
Name: Asia-Pacific Business Review Publisher: Asia-Pacific Institute of Management Audience: Academic Format: Magazine/Journal Subject: Business; Business, international Copyright: COPYRIGHT 2008 Asia-Pacific Institute of Management ISSN: 0973-2470
Issue:
Date: July-Sept, 2008 Source Volume: 4 Source Issue: 3
Accession Number:
198667810
Full Text:
Introduction

The Indian capital market witnessed radical changes as a result of liberalization initiative, characterized by institutional build up, technological advancements, modernization and transparent trading practices. The change in the capital market is also reflected in the number of shareholders which has exploded everywhere for the whole country to 125 lakhs with an increase of 3-4 times between 1983 and 1992. After that it rose to 20 million shareholders. This is too small when compared to the population of India. In advanced countries, a sizable percentage of the population invests in capital market and mutual funds. Such investments culture is to be developed in India also. Inspite of the developments in the capital market, many investors continue to keep away from the market due the prevalence of unethical acts of promoters, shares brokers, high volatility in the market, poor investment knowledge of the ordinary investors and high element of uncertainty and risk added to these problems. This calls for the attention of the government and policy makers to understand the factors influencing the capital market operations which enable them to take initiatives to decide the measures to pull them into the ambit of investors in corporate securities. This ensures individual development as well as alround development of the country's economy. So, the present study focused its attention to bring to limelight the factors influencing the capital market operations with the following objectives:

* To study the factors influencing the behaviour of investors in their capital market operations.

* To know the perception of investors towards the factors influencing capital market operations.

* To analyze the behaviour of the investors under different economic conditions.

Methodology

The study covers 150 active investors using the convenient sampling method. All investors were involved in the purchase and sale of securities in order to take advantage of the favourable position in the capital market. The respondents for the study included government employees, private sector employees, Finance professionals and business people in the Coimbatore city. Primary data has been collected with the help of a questionnaire consisting of personal profile and the factors influencing the capital market operations. The socio- economic status of the respondents have been presented in Table 1.

Limitations

(i) The sample size is limited to 150 respondents in Coimbatore city. The sample size may not adequately represent the national market.

(ii) The study used convenient sampling method and it may not reflect the universe.

(iii) As the study is conducted over a short period of two months, it may be difficult to analyze the complete behaviour of the investors in span of short period.

Framework of Analysis

The data collected was statistically analyzed using simple percentages, scaling technique and factor analysis. The different factors (variables) are presented in Table 2. The important attributes were listed using a structured questionnaire and the respondents were asked to rate them according to the importance in their activity of purchase / sale of securities in the capital market on 5 point scale basis. Factor analysis was used to determine the parameters that determine the capital market operations in terms of awareness, buying decision, pattern of investment, general economic conditions and prevailing legal environment in the capital market. The data collected has been summarized in Table 2.

Factor Analysis

The factor analysis determines the correlations among the variables. It is analyzed by computing the correlations between the variables when the effects of other variables are taken into account. Then the KMO and Bartlett test of Sphericity is carried out to ensure whether the correlation matrix has significant correlation among at least some of the variables. It also quantifies the degree of inter correlation among the variables and the appropriateness of factor analysis to test the adequacy of the sample. The result is presented in Table 3. From the Table 3 showing the result of Kaiser Meyer Olkin Measure, it is found that the test value is 0.641 which is well above the screening limit of 0.5. Hence, the sample is validated for factor analysis

Communalities

Table 4 shows the communalities designed for each parameter on the extracted factors. Ideally, the communalities should be at the minimum acceptance value of 0.5. It is observed that almost all the parameters are well accommodated by the extracted factors

Principal Component Extraction

Table 5 is one of the most important representations of factor analysis, as it defines the percent of variance defined by each component. Since only four components whose Eigen Value is greater than one considered, the first five components are taken as factors. These 5 factors with 57.690 of the variance of the parameters is regarded as reasonably good, because variables are reduced to the economy size from 12 to 5 underlying factors by loosing 42.31% of the information content.

Rotated Component Matrix

Table 6 shows the parameters which fall under each factor. It can be seen that the factor loading for each parameters against each parameters is significant enough to set under any of the factor. So based on the above the factors and the parameters under each factor is defined in Table 6.

Varimax rotation was applied for the selected attributes. The factor loading of their variables was observed and was clubbed into 5 factors. The rotation factor matrix has been shown in

From the above Table, we notice that variables V3, V7, and V10 have loading on factor 1, this suggests that factor 1 is a combination of these variables. At this point, it is necessary to find a suitable phrase, which capture the essence of the original variables that continue to form the underlying concept "factor". In this case, factor 1 could be named as "investor awareness and investment decision". In case of factor 2, the variables V2 and V4 have high loading of .741 and .723. This indicates that factor 2 is a combination of these two variables. Combined variables of factor 2 could be named as "impact of risk factor". Incase of factor 3, the variables V1, V6 and V12 have high loading of 0.597, 0.794 and 0.321 respectively. Therefore, factor 3 consists of these 3 variables. This factor 3 could be named as "Investor Education". In the case of factor 4, the variables V5, V9 and V11 have loading of 0.429, 0.616 and 0.747 respectively. Thus, factor 4 consists of these 3 variables and it could be named as "Life style under different economic conditions." Factor 5 consist of one variable i.e., it is having high loading .828 and therefore it consists of this one variable and it could be named as "Investment Information".

The Table 8 presents variables identified for factor scores, along with the phrases designated for such factor scores. The factor scores have been obtained by identifying the high values of the respective variable for each particular factor.

Conclusion

By understanding the need for increasing the number of investors and ensuring continuous supply of capital by creating a permanent set of investors in the capital market, the policy makers have to concentrate on the illustrated 5 factors and take initiatives to cover the investors. This could help to increase the economic activities and enabling the country to grow. Capital market has witnessed wide fluctuations in the recent times. It is felt necessary that the capital market should facilitate the function of supply of capital to the corporate in the present scenario. The study thus helps by defining the area towards which attention can be focused to increase the number of investors and ensuring continuous supply of capital to the needy corporates. The study, as per the factor analysis, revealed that the five factors among twelve factors as focus areas for the policy makers. They are:

Investment information: It may be made mandatory that the provision of full information about investment details by the capital issuers shall be ensured.

Investor awareness: The policy maker may take initiative to create awareness among the investors about the nature of advertisement, stock broker service and the level of sensex prevailing in a detailed way to enable the investors to take correct decision.

Investor education and investment decision: The investors must possess the knowledge of the availability of the grievances measures available and the economic size of the investment that may be taken care of.

Impact of risk factor: As the risk factor plays an important role in taking decision on the type of script to be selected and on the pattern of investment to be made, adequate attention may be paid to bring to limelight the risk factors involved in the particular script in a way understandable to the investors.

Lastly, the life style under different economic conditions may be considered by the capital issuers at the time of issue to enable the prospective investors to select this investment avenue.

References

Chandrasekara Rao, K. and Geetha T. (1996), Indian Capital Market, A.P.H. Publishing Corporation, New Delhi.

Cirvante, V.R. (1956), The Indian Capital Market. Oxford University Press, Bombay.

Crockett Andrew, (1998), "Capital Market Innovations: Opportunities and challenges" in (Raj Kapila and Uma Kapila (Ed). pp. 19-33.

Dileep Kumar, P.M. and Raju.G, (2004), "Capital Market Investment in India", Sonali Publications, New Delhi.

Gupta, L.C. (1992), Rate of return on Equities: The Indian Experience. Oxford University Press, New Delhi.

Lease Ronald, C.et al, "The Individual Investor: Attributes and Attitude". The journal of Finance, Vol. 29 (2), pp. 413-433.

Rangarajan, C. (1998), "The Indian Capital Market, Problems, Prospects and Agenda for Reforms". In (Raj Kapila and Uma Kapila (Ed). pp. 97-103.

Saroja, S. (Ed). (1991), Emerging Trends in the capital Market in India. Global Business Press, New Delhi.

Schwert, William G. and Smith, Clifford W. (1992), Emperical Research in Capital Market. Mc Graw-Hill Inc., New York:

Singh, Pyarelal. (1994), Indian Capital Market. Kanishka Publishers, Distributors, New Delhi.

Vinayagam, (Ed). (1994), A Profile of Indian Capital Market. Kanishka Publishers, Distributors, New Delhi.

S. Renuga Devi * and N. Bharathi **

S N R Sons College, Coimbatore--641 006, Tamilnadu, India

* E-mail: renureswar@gmail.com, **E-mail: bharathi7781@yahoo.co.in
Table 1: Socio Economic Factors of the Respondents *

                                      No. of
Variable        Profile               Respondents   Percentage

Gender          Male                  111           74.0
                Female                39            26.0

Age             25-35                 44            29.3
                35-45                 62            41.3
                45-55                 31            20.7
                Above 55              13            8.7

Educational     School                35            23.3
Qualification   Graduate              51            34.0
                Post Graduate         50            33.3
                Professional          14            9.3

Occupation      Govt Employee         58            38.7
                Private Employee      36            24.0
                Professional          32            21.3
                Business              22            14.7
                Others                2             1.3

Monthly         Less than Rs.10,000   4             2.7
Income          Rs.10,000-Rs.20,000   43            28.7
                Rs.20,000-Rs.30,000   67            44.7
                Above Rs.30000        36            24.0

Table 2: Perception towards factors influencing capital market
operation

Variable   Factors                       Strongly   Disagree
                                         Disagree

V1         Advertisement           No.      14         16
           creates awareness       %       9.3        10.7

V2         Investor analysis the   No.      4          24
           Risk Factor             %       2.7        16.0

V3         Investor Grievances     No.      13         23
                                   %       8.7        15.3

V4         Investment Pattern      No.      10         15
                                   %       6.7        10.0

V5         Change the Life         No.      11         20
           Style                   %       7.3        13.3

V6         Stock broker            No.      7          13
           service                 %       4.7        8.7

V7         Investment              No.      10         22
           knowledge               %       6.7        14.7

V8         Investment              No.      14         30
           information             %       9.3        20.0

V9         Personal saving         No.      10         21
                                   %       6.7        14.0

V10        Size of Investment      No.      6          25
                                   %       4.0        16.7

V11        Economic condition      No.      21         26
                                   %       14.0       17.3

V12        Decreasing level        No.      13         41
           of Sensex               %       8.7        27.3

       Neural     Agree     Strongly    Total
                             Agree

No.      51         56         13        150
%       34.0       37.3       8.7        100

No.      57         52         13        150
%        38        34.7       8.7        100

No.      45         42         27        150
%       30.0       28.0       18.0       100

No.      44         55         26        150
%       29.3       36.7       17.3       100

No.      31         56         32        150
%       20.7       37.3       21.3       100

No.      37         59         34        150
%       24.7       39.3       22.7       100

No.      49         49         20        150
%       32.7       32.7       13.3       100

No.      37         48         21        150
%       24.7       32.0       14.0       100

No.      48         56         15        150
%       32.0       37.3       10.0       100

No.      49         61         9         150
%       32.7       40.7       6.0        100

No.      46         24         33        150
%       30.7       16.0       22.0       100

No.      40         33         23        150
%       26.7       22.0       15.3       100

Table 3: KMO & Bartlett's Test of Sphercity

 Kaiser-Meyer-Olkin                           .641
Measures of Sampling
      Adequacy

 Bartlett's Test of    Approx. Chi-Square   143.497
     Sphercity
                               Df              66

                              Sig.            .000

Table 4: Communalities

Variables   Initial   Extraction

   V1        1.000       .610
   V2        1.000       .592
   V3        1.000       .364
   V4        1.000       .531
   V5        1.000       .543
   V6        1.000       .767
   V7        1.000       .415
   V8        1.000       .734
   V9        1.000       .651
   V10       1.000       .526
   V11       1.000       .652
   V12       1.000       .536

Extraction Method: Principal Component Analysis.

Table 5: Principal Components Extraction

                   Initial Eigen Value

Component    Total        Total         % of
                                      Variance

   1         2.294        19.118       19.118
   2         1.321        11.005       30.124
   3         1.179         9.823       39.946
   4         1.101         9.174       49.120
   5         1.028         8.569       57.690
   6         0.959         7.990       65.679
   7         0.837         6.974       72.653
   8         0.805         6.705       79.359
   9         0.732         6.103       85.461
   10        0.657         5.478       90.939
   11        0.581         4.844       95.783
   12        0.506         4.217      100.000

                Extraction Sums of Squared
                        Loadings

Component    Total         % of      Cumulative
                         Variance        %

   1         2.294        19.118       19.118
   2         1.321        11.005       30.124
   3         1.179         9.823       39.946
   4         1.101         9.174       49.120
   5         1.028         8.569       57.690
   6
   7
   8
   9
   10
   11
   12

                 Rotation Sums of Squared
                         Loadings

Component    Total         % of      Cumulative
                         Variance        %

   1         1.662        13.847       13.847
   2         1.521        12.672       26.520
   3         1.376        11.465       37.985
   4         1.199         9.993       47.978
   5         1.165         9.712       57.690
   6
   7
   8
   9
   10
   11
   12

Table 6: Rotated Component Matrix

Variables   Component

                1           2           3           4          5

V1            .540       -.490     -8.38E-02      .184       .194
V2            .508       -.326        .313       -.189      -.306
V3            .572      8.67E-02   -1.92E-02     -.130      -.110
V4            .432       -.318        .382     -4.89E-02    -.308
V5            .283        .463        .444       -.133       .186
V6            .494      1.24E-02     -.273       -.168       .648
V7            .449        .356     -3.78E-02     -.281     -8.06E-02
V8            .279      5.31E-02     -.553        .528      -.261
V9            .423      -6.41E-02     .275        .620     -1.12E-02
V10           .626        .314       -.165     -1.12E-02   8.74E-02
V11         -6.94E-02     .554        .370        .452     -1.32E-03
V12          -.226       -.335        .330        .140       .494

Extraction Method: Principal Component Analysis. a 5 components
extracted.

Table 7: Rotation Factor Matrix

Factors     1       2       3       4       5

V1                        .597
V2                .741
V3        .487
V4                .723
V5                                .429
V6                        .794
V7        .632
V8                                        .828
V9                                .618
V10       .613
V11                               .747
V12                       .321

Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser

Table 8: Variables identified for factor scores

S. No.   Variables     Factor Names

1        V3, V7, V10   Investor education and
                       investment decision

2        V2, V4        Impact of risk factor

3        V1, V6, V12   Investor awareness

4        V5, V9, V11   Life style under different
                       economic conditions

5        V8            Investment information
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