THE RETAIL INVESTORS BEHAVIOUR ON EQUITY SHARES IN CHENNAI CITY – A STUDY
Thesis submitted to the Bharathidasan University, Tiruchirappalli for the award of the Degree of DOCTOR OF PHILOSOPHY IN COMMERCE
By
N.SRIVIDHYA,M.Com., M.Phil., MBA., Associate Professor, Dept. of Management Studies, Sri Manakula Vinayagar College of Engineering, Madagadipet, Puducherry.
Under the Guidance of
Dr.S.RAJKUMAR, M.Com., M.Phil., B.Ed., Ph.D., Principal and Research Advisor, Naina Mohamed College of Arts and Science, Rajendrapuram, Arantangi Taluk, Pudukkottai District.
May - 2012
1
Dr. S. RAJKUMAR, M.Com., M.Phil., B.Ed., e-mail: Ph.D, [email protected] Principal & Research Advisor, [email protected] Naina Mohamed College of Arts and Science, Mobile/ Phone:9443588201 Rajendrapuram, Aranthangi Taluk, Pudukkottai District.
Date:
CERTIFICATE
This is to certify that the Ph.D. thesis entitled “The Retail Investors behaviour on Equity Shares” – A Study is a bonafide record of research work done by Mrs.N.Srividhya, under my guidance and supervision and the thesis has not previously formed the basis for the award of any degree, diploma, fellowship or similar title. The thesis represents entirely an independent work of the candidate.
2
N.Srividhya, M.Com., M.Phil., M.B.A., Associate Professor, Dept. of Management Studies, Sri Manakula Vinayagar Engineering college, Madagadipet, Puducherry 605107.
Date:
DECLARATION
I, N.Srividhya, Ph.D. Scholar, Department of Management Studies, Sri
Manakula Vinayagar Engineering college, Madagadipet, Puducherry, do hereby declare that the thesis entitled “The Retail Investors behaviour on Equity Shares” –
A Study submitted to Bharathidasan University, Tiruchirappalli for the award of the degree of “DOCTOR OF PHILOSOPHY IN COMMERCE” is my original work and that the thesis has not formed the basis for the award of any degree, diploma, associate ship, fellowship or any other similar titles.
Counter Signed Research Scholar
3 ACKNOWLEDGEMENT
Dr. S. Rajkumar, my Research Advisor, Principal, Naina Mohamed College of Arts and Science, Rajendrapuram, Aranthangi Taluk, Pudukkottai District is the inspiring force behind this research work. He has been my Guide in the true sense of word. He offered me valuable guidance and suggestions to complete this work successfully. This study would not have been possible but for his immense help.
I feel immense pleasure to express my heart-felt gratitude to my Doctoral committee members Dr.S.Sekar, Principal, Urumu Dhanalakshmi College, Kattur, Tiruchirappalli – 620 019 and Dr.E.Mubarak Ali, Associate Professor, P.G. and Research Department of Commerce, Jamal Mohamed College, (Autonomous), Tiruchirappalli, for providing me the valuable suggestions to make this study.
The help of librarian of Bharathidasan University is gratefully
acknowledged for their assistance in literature collection.
My acknowledgements are due to all the publishers of both the research articles and popular articles of mine in their leading national and International Journals by giving me an opportunity to write my views and findings. I wish to extend my heartfelt thanks to all the Colleges and Universities for giving me an opportunity to present my papers on the emerging issues.
I render my thanks to the entire respondents for the co-operation and co- ordination extended by them in the collection of data needed for the research.
I wish to make a special mention about my better half Mr._G. Ravichandran, who helped in all the way from the beginning to the end of my research journey. He gave his moral support in all spheres of my research work. I am at a loss for words when I think about the sacrifices made by my dear daughter Selvi._R. Vishnu Priya, and my son Selvan. R. Maadhav, who had to suffer my absence during the period of my research work.
(N.Srividhya)
4 CONTENTS
CHAPTER TITLE PAGE NO I INTRODUCTION AND RESEARCH DESIGN 1
II REVIEW OF LITERATURE 17
III CONCEPTUAL FRAMEWORK OF INDIAN 66
CAPITAL MARKETS
IV ANALYSIS – I 102
V ANALYSIS - II 139
VI FINDINGS, CONCLUSIONS, SUGGESTIONS 236
BIBLIOGRAPHY
ANNEXURE - QUESTIONNAIRE
5 LIST OF TABLES
Table Page Title No. No. 3.1 International Equity Markets 71
3.2 Resources Mobilised from the Primary Market 72
3.3 Secondary Markets – Selected Indicators 73
3.4 SEBI Registered Market Intermediaries 75
3.5 Trends in Resource Mobilisation by Mutual Funds 77
3.6 Derivatives Segment at BSE and NSE 79
3.7 Foreign Investment Inflows 80
3.8 Trends in FII Investment 81
3.9 Settlement Statistics for Cash Segment of BSE and NSE 84
3.10 Receipt and Redressal of Investor Grievances 93 4.1 Age of the Investors 103 4.2 Gender of the Investors 104
4.3 Marital Status of the Investors 106
4.4 Education of the Investors 107
4.5 Occupation of the Investors 108
4.6 Income of the Investors 109
4.7 Nature of Family of the Investors 111
4.8 Number of Dependents of the Investors 112
4.9 House Ownership of the Investors 113
4.10 Type of Investors 114
4.11 Category of Investors 115 4.12 Number of years of Dealing with securities Markets 116 4.13 Number of Companies Invested 117
4.14 Size of Investment 117 4.15 Source of Investment 118
6 Table Page Title No. No. 4.16 Percentage of Savings invested in Securities Markets 119 4.17 Sources of Information 120 4.18 Criteria for Investments 121 4.19 Member of Investors’ Forum 121 4.20 Awareness of Malpractice of Intermediaries 122 4.21 Mode of Trading 122 4.22 Awareness of Financial Sector Reforms in India 123 4.23 Frequency Distribution of Index 124 Chi-square value for sources of Information with regard to News 4.24 125 papers Chi-square value for sources of Information with regard to 4.25 126 Journals and Magazines 4.26 Chi-square value for sources of Information with regard to T V 126 Chi-square value for sources of Information with regard to stock 4.27 127 Brokers Chi-square value for sources of Information with regard to 4.28 128 Investment Consultant Chi-square value for sources of Information with regard to On 4.29 128 line website 4.30 Chi-square value for sources of Information with regard to 129 Friends and Relatives Mean and Standard Deviation for preference of Investments and 4.31 130 their Ranks 4.32 Mean and Standard Deviation for Ranking of Industries 131 Mean and Standard Deviation of Reasons for Investments and 4.33 132 their Ranks 4.34 Mean and Standard Deviation of Preference of Investment Style 132 Mean and Standard Deviations for Preference in Choosing Stock 4.35 133 Exchanges 4.36 Paired Samples Statistics for the Factors of the risk and return 134 Paired Samples Correlations for the Factors of the Investment in 4.37 135 equity market 4.38 Paired samples Test Values for the Factors of the Latest Reforms 136 in Capital market
7 Table Page Title No. No. 4.39 Frequency Distribution of Percentage of expected return 137 5.1 Clusters of Investors Based on Elements of Retail Investment 140 5.2 Number of cases in Each cluster of Retail Investment 140 5.3 Paired Samples statistics for the Elements of Retail Investment 141 Paired Samples correlations for the Elements of Retail 5.4 142 Investment Paired Samples Test values for the Elements of Retail 5.5 143 Investment 5.6 Correlation Matrix for Number of year Dealing 145 Correlation co-efficient Table for percentage of savings in Share 5.7 146 Market ANOVA for the Elements of capital investments with respect to 5.8 147 investment in shares ANOVA for the Elements of Retail Investment with respect to 5.9 148 Investment in Government Bonds 5.10 ANOVA for the Elements of Retail Investment with respect to 149 Investment in Fixed Deposits ANOVA for the Elements of Retail Investment with respect to 5.11 150 Investment in Gold ANOVA for the Elements of Retail Investment with respect to 5.12 151 Investment in Debentures ANOVA for the Elements of Retail Investment with respect to 5.13 152 Investment in Mutual Funds ANOVA for the Elements of Retail Investment with respect to 5.14 153 Investment in Real Estate ANOVA for the Elements of Retail Investment with respect to 5.15 155 the Reason for Investment - Return ANOVA for the Elements of Retail Investment with respect to 5.16 156 the Reason for Investment - Liquidity ANOVA for the Elements of Retail Investment with respect to 5.17 157 the Reason for Investment – Tax Benefits ANOVA for the Elements of Retail Investment with regard to the 5.18 159 Investment Decisions influenced by Abridged Prospectus ANOVA for the Elements of Retail Investment with regard to the 5.19 160 Investment Decisions influenced by T V Channels 5.20 ANOVA for the Elements of Retail Investment with regard to the 161
8 Table Page Title No. No. Investment Decisions influenced by Consultant ANOVA for the Elements of Retail Investment with regard to the 5.21 162 Investment Decisions influenced by websites Association between preference of Investment in Equity Shares 5.22 163 and Clusters of Investors 5.23 Chi-square for preference of Investments in Equity shares 164 Multivariate General Linear Model for percentage of 5.24 165 Investments 5.25 Association Criteria for Investment and Clusters of Awareness 168 5.26 Chi-square Test and criteria for Investments 169 5.27 Final Cluster Centres for Awareness of the equity Investment 170 Frequency of Clusters for Awareness of the latest Reforms in 5.28 170 Capital Market ANOVA for the Elements of Retail investment with regard to 5.29 172 preference of Investment in Banking Sector ANOVA for the Elements of Retail investment with regard to 5.30 173 preference of Investment in FMCG ANOVA for the Elements of Retail investment with regard to 5.31 174 preference of Investment in Pharma Sector ANOVA for the Elements of Retail investment with regard to 5.32 175 preference of Investment in PSE Sector ANOVA for the Elements of Retail investment with regard to 5.33 176 preference of Investment in MNC Sector ANOVA for the Elements of Retail investment with regard to 5.34 177 preference of Investment in IT Sector ANOVA for the Elements of Retail investment with regard to 5.35 178 preference of Investment in Manufacturing Sector ANOVA for the Elements of Retail investment with regard to 5.36 179 preference of Investment in Service Sector Investment in Equity Shares is Higher Risk and Clusters of 5.37 180 Awareness on Retail Investment Chi-square Test Statistics for Investment in Equity Shares is 5.38 181 Higher Risk ANOVA for the Elements of Retail Investment with regard to 5.39 182 preference of Stock exchanges - Sensex 5.40 ANOVA for the Elements of Retail Investment with regard to 183
9 Table Page Title No. No. preference of Stock exchanges - Nifty ANOVA for the Elements of Retail Investment with regard to 5.41 184 preference of Stock exchanges – CNX 100 Reason for Preference Given to Stock Exchange Dealing and 5.42 185 Cluster of Awareness on Retail Investment Chi-square Tests for Reason of preference Given to Stock 5.43 186 Exchanges Experience in Dealing shares through Electronic mode (demat) 5.44 187 and Cluster of Awareness on Elements of Retail investment Chi-square Tests statistics showing Experience in Dealing shares 5.45 with Electronic mode (demat) and Cluster of Awareness on 187 Elements of Retail investment Percentage of Different sources of Information to know About 5.46 189 Retail investment 5.47 Paired Samples statistics for the Factors of the equity investment 190 Paired Samples correlations for the Factors of the equity 5.48 191 investment Paired Samples Test values for the Factors of the equity 5.49 192 investment Multivariate Tests (b) for the Impact of the Latest Reforms in 5.50 194 Capital Market Impact of the equity investment objectives on the Element of 5.51 195 Investment decision Tests of Between – Subjects Effects 5.52 ANOVA for Group means of investment options 199 Co-efficient of correlations for Number of years Dealing in 5.53 200 Capital market 5.54 ANOVA for the Latest Reforms Based on Percentage of savings 201 Variance of Independent variable on General information’s and 5.55 203 Cluster 1(b) 5.56 ANOVA (b.c) for General information’s and Cluster 1 203 5.57 Coefficients (a.b) of General information’s and Cluster 1 204
5.58 Variance of Independent variable on General information’s 205 and Cluster2 (b) Cluster 2(b) 5.59 ANOVA (b, c) for General information’s and Cluster 2 205 5.60 Coefficients (a, b) of General information’s and Cluster 2 206
10 Table Page Title No. No. 5.61 Variance of Independent Variable for Company 207 management and Cluster 1(b) 5.62 ANOVA (b, c) for Company management and Cluster 1 207 5.63 Coefficients (a, b) of Company management and Cluster 1 208 Variance of Independent Variable for Company management and 5.64 209 Cluster 2(b) 5.65 ANOVA (b,c) for Company management and Cluster 2 209 5.66 Coefficients (a,b) for Company management and Cluster 2 210 Variance of Independent variable on Details of present values 5.67 211 Cluster 1 (b) 5.68 ANOVA (b,c) for Details of Present values and Cluster 1 211 5.69 Coefficients (a,b) of Details of present Values and Cluster 1 212
5.70 Variance of Independent Variable on Details of present values 213 and Cluster 2(b) 5.71 ANOVA (b,c) for Details of present values and Cluster 2 213 5.72 Coefficients (a, b) for Details of present values and Cluster2 214
5.73 Variance of Independent Variable on project details and their 215 changes and Cluster 1(b) 5.74 ANOVA (b,c) for project details and their changes and Cluster 1 215
5.75 Coefficients (a,b) for project details and their changes and 216 Cluster 1 5.76 Variance of Independent Variable on Project details and their 217 Changes and Cluster 2(b) 5.77 ANOVA (b, c) for project details and their changes and Cluster 2 217 5.78 Coefficients (a,b) for project details and their changes Cluster 2 218
5.79 Variance of Independent Variable on Financial parameters and 219 Cluster 1 (b) 5.80 ANOVA (b,c) for Financial parameters for Cluster 1 219 5.81 Coefficients (a, b) for Financial Parameters and Cluster 1 220
5.82 Variance of Independent Variable on Financial parameters and 221 Cluster 2 (b) 5.83 ANOVA (b, c) for Financial parameters for Cluster 2 221 5.84 Coefficients (a.b) for Financial parameters and Cluster 2 222
11 Table Page Title No. No. 5.85 Impact of Retail investment preference of returns Amount 223 Received and Tests of Between – Subjects Effects 5.86 Impact of Demographic Variables on the investment objectives, 228 decision and satisfaction – Tests of Between –Subjects Effects
LIST OF FIGURES
Figure Page Title No. No.
4.1 Age of the Investors 104
4.2 Gender of the Investors 105
4.3 Marital status of the Investors 106
4.4 Education of the Investors 107
4.5 Occupation of the Investors 109
4.6 Income of the Investors 110
4.7 Nature of the Family of Investors 111
4.8 Number of Dependents of the Investors 112
4.9 House ownership of the Investors 113
5.1 Investment pattern in stock market 235 - 236
12 LIST OF ABBREVIATIONS
ADRs - American Depository Receipts
AMFI - Association of Mutual Funds in India
AUM - Assets Under Management
BSE - Bombay Stock Exchange
C&D - Corporatisation and Demutualisation
CAGR - Compounded Annual Growth Rate
CC - Clearing Corporation
CDSL - Central Depositary Services (India) Limited
CH - Clearing House
MSX - Madras Stock Exchange
ECS - Electronic Clearing Scheme
EDIFAR - Electronic Data Information Filing and Retrieval
EPS - Earnings Per Share
FAQs - Frequently Asked Questions
FIIs - Foreign Institutional Investors
FMCG - Fast Moving Consumer Goods
GDP - Gross Domestic Product
GDRs - Global Depository Receipts
GDS - Gross Domestic savings
GETFs - Gold Exchange Traded Funds
GIC - General Insurance Corporation
13 HKEx - Hong Kong Exchange and Clearing Ltd
ICICI - Industrial Credit and Investment Corporation of India
IDBI - Industrial Development Bank of India
IFCI - Industrial Financial Corporation of India
IMSS - Integrated Market Surveillance System
IPF - Investor Protection Fund
IPO - Initial Public Offering
IT - Information Technology
LIC - Life Insurance Corporation
MDA - Multiple Discriminate Analysis
MF - Mutual Fund
MIDC - Maharashtra Industrial Development Corporation
MNC - Multi National Company
NCAER - National Council for Applied Economic Research
NISM - National Institute of Securities Markets
NSCCL - National Securities Clearing Corporation Limited
NSDL - National Securities Depository Limited
NSC - National Savings Certificate
NSE - The National Stock Exchange
OIAE - Office of Investor Assistance and Education
OTCEI - Over the Counter Exchange of India Limited
PAN - Permanent Account Number
14 PE ratio - Price Earnings ratio
PPF - Public Provident Fund
PSE - Public Sector Enterprises
QIBs - Qualified Institutional Buyers
RBI - Reserve Bank of India
RSEs - Regional Stock Exchanges
SEBI - Security Exchange Board of India
SGF - Settlement Guarantee Fund
SMAC - Securities Market Awareness Campaign
STP - Straight Trough Processing
UTI - Unit Trust of India
VSAT - Very Small Aperture Terminal
15 CHAPTER - I
INTRODUCTION
Introduction Chapter deals with a brief note about importance of capital market, Statement of the problem, Objectives of the study, Hypothesis, scope of the study, Geographical coverage, Field work and collection of data, Limitations of the study, Research methodology, Main study, Sample size, Tools used in the study, Operational definitions and Chapter arrangement.
The capital market is used as a main vehicle to mobilize funds for the economic growth of the country. It performs crucial functions like the conversion of savings of the households and institutions into investment, creation of financial assets and development of asset-related products. A well functioning securities market is conducive to the sustained economic growth of any country in the world1. There exists a direct relationship between the development in the securities market and economic growth of a country. The securities market provides a bridge between ultimate savers and ultimate investors and creates the opportunity to put the savings of the cautious at the disposal of the enterprising, thus promising to raise the total level of investment and growth. It allocates scarce savings to the enterprises and forces them to focus on their performance, which is continuously evaluated through share prices in the market. It thus converts a given stock of investible resources to a large flow of goods and services.
The development of the securities market changes the quantum and composition of savings and investment of the households. The availability of yield- bearing securities induces people to consume less and invest more in high yielding, divisible, liquid securities. A strong domestic stock market performance forms the basis for the well performing domestic corporate to raise capital in the international markets. The securities market facilitates the internationalization of the economy by linking it with the rest of the world. This linkage happens through the inflow of capital in the form of portfolio investment.
16 Financial markets across the globe are undergoing profound, unprecedented and fast–paced changes2. Technology has revolutionized the processes and the information explosion has sparked off remarkable changes in the way the world market has been operating. Change has become an inevitable phenomenon.
Indian Capital market is one of the fastest growing markets in the world. It has grown impressively during the recent years in tune with the global financial markets. The Indian Capital Market comprises of two segments, namely, the Primary and the Secondary market. The fresh issue of securities takes place in primary market and trading among investors takes place in secondary market. The primary market is the major channel through which the savings of the households are mobilized by the companies directly for investment purposes. It is the centre stage of the capital market that really boosts industrial and financial activities by providing long term funds to the corporate and the government. It infuses new securities, adding volume and wider base of securities in the secondary market. The secondary market affords liquidity to the investment in securities and reflects the general health of the economy.
Indian corporates mainly raise funds through capital market. Two types of capital are essentially raised viz., Equity and Debt. Equity forms part of the net worth and the Debt forms part of the outside liability of the firm. The capital raised through equity is superior to that of debt capital for both the firm and the investor. Equity enhances the borrowing power of the firm from banks and financial institutions. If a firm is able to mobilize sizable amount of equity capital through primary market, it can approach banks to fund long-term investment. From the investor’s point of view, it could be noticed that over the long term, the equity investments have out-performed debt and other asset classes across the globe. In India, looking at the 8 years Compounded Annual Growth Rate (CAGR), equity returns have out-performed debt to the tune of 15.8 percent3.
The Indian Capital Market has witnessed unprecedented euphoria from the early nineties and it has won critical appreciation from various quarters4. At present there are 19 Stock Exchanges in India. The National Stock Exchange (NSE) and
17 Bombay Stock Exchange (BSE) together account for more than 99 percent of the total turnover having a combined market capitalization of $ 125.5 billion. Around 9600 companies are listed in NSE and BSE.
Success of equity issues totally depends on the confidence of the investors. If the investors perceive high profitability prospects, they will invest in equity. There are two types of investors, namely, institutional investors and retail investors (households). Institutional investors are huge investors who operate through Portfolio Managers. Portfolio Managers only shuffle around the holdings in the existing scrips in their basket, based on their subjective evaluation of various scrips but they do not inject the much needed risk capital to upcoming enterprises to undertake new industrial activities. Even Foreign Institutional Investors (FII’s) generally bring capital into the country only to acquire shares in the existing highly profitable companies but do not provide risk capital to the corporate world. It is the Retail Investor i.e. the household sector, who is the only source of providing risk capital5. The Retail Investor provides this risk capital, either directly by investing in equity market or through collective schemes popularly called as Mutual Funds. There are 39 Mutual Funds offering about 600 schemes to the households, managing assets to the tune of Rs. 3,10,171 crores (US $ 68 billion) at the end of October 20066. Indian retail investors have been directly participating in equity markets and taking price fluctuations for decades. The household sector generates more than $ 30 billion of savings every year, which is available to the Indian financial system. It is the only source of providing risk capital within the country.
It is globally recognized that the growth of the economy depends to a large extent on the growth of the securities market, as it provides the vehicle for raising resources and managing risks. The growth of the securities market is the result of high confidence of the investors, that too the retail equity investors, the only risk capital providers of yesterday, today and tomorrow.
1.2 STATEMENT OF THE PROBLEM
The stock market is one of the most vital and dynamic sectors in the financial system making an important contribution to the economic development of a country.
18 Investors are the backbone of the capital market and they are not alike. Institutional investors are capable of understanding the intricacies involved in the stock market activities but the retail investors lack adequate awareness about it. As the bulk of the savings of the country generally emanate from the households, and the retail investor is still the major source of risk capital to upcoming enterprises, to undertake new industrial activities, the capital market cannot grow without their participation, directly or indirectly.
With the liberalization of the Indian capital markets, securities market has grown into one of the most dynamic, modern and efficient markets. The infrastructure and operating efficiency of the Indian stock markets are well appreciated by its global counterparts. In India, to encourage, enhance and safeguard retail investor participation and to make the markets more efficient, a number of reforms have been initiated by the Security Exchange Board of India (SEBI). In the case of fixed price public issues and book built issues, 50 percent and 35 percent shares respectively are being allotted to the retail investors7. As small investors find it difficult to participate directly in the capital market to a significant extent, SEBI encourages mutual fund industry to offer innovative products to suit the risk appetite of the retail investors.
In spite of all the efforts taken by SEBI to attract and enhance retail participation, the household (retail) savings and investment scenario is highly disappointing. According to the SEBI – NCAER survey, only 7.4 per cent of the Indian households directly participated in the securities market in 2000 as against about 50 percent in the USA. As the economy grew at 8.5% in 2003-04, GDS (Gross Domestic Savings) rate reached 28.1 percent of GDP, (Gross Domestic Product) and the household financial savings increased to 11.4 percent of GDP, but the capital market instruments contributed barely 1.4 percent of the financial savings and investment. In 2004 – 2005, though India’s GDS in proportion to GDP was 29.1 percent, the investment by households in shares and debentures stood at a meager 0.8 percent of GDP8.
19 Despite the developments happening in the capital market in India and even after a decade of existence of a vibrant capital market, the equity instruments are not considered as an attractive household investment.
The ill effect of such a phenomenon is that, if such a situation persists, the performance of the capital markets will be determined and dominated by a few large and wealthy players. High dependence on FII funds will lead to a volatile and high risk market which will make the retail investor the only risk capital provider-extinct. This will hamper the whole growth of the securities market and in turn the economic growth of the nation. So bringing the retail investors back into the equity market would be a very healthy structural development for the nation itself.
The recent economic recession had a great impact on stock market. The developing countries also taste the economic downtrend. The Indian economy is also not left out. Before the recession, Indian economy was moving at a faster rate because of the growth in information technology and other sectors. But after the recession the economic level comes down and there will be some velocity in the Indian stock market conditions. As the regulatory system is so strong in India, the stock market is able to withstand many odds. Since the stock market is all the time unpredictable and unstable, the investors are all the time at very high risk. They have to consider many factors like Economic environment, Political stability, Industrial growth etc., before they invest. Though there are many studies on the stock market related areas, the information provided to the investor and industry is not sufficient. As a result the investor and the stock market players will be searching for required information. There are some research gaps in the existing literature relating to the stock market.
Hence the current study is undertaken to fill the gaps in the existing research in the field of stock market and also to provide required information to the investors as well as industry.
20 1.3 OBJECTIVES OF THE STUDY
1. To study the investment pattern of retail equity investors in Chennai.
2. To analyse the information search and investment option of retail investors.
3. To identify the various investment preferences and investors perception on risk and return.
4. To examine factors influencing investment evaluation and decision of investors.
5. To evaluate investors level of satisfaction and their futuristic perceptions towards retail equity investment.
6. To find the relationship between demographic variables of investors and their investment objectives, decision and satisfaction.
1.4 RESEARCH HYPOTHESES
1. There is no significant difference between level of risk and returns of investors.
2. There is no association between investment objectives and satisfaction.
3. There is no association between investment decision and satisfaction.
4. There is no significant influence of demographic variables of investors and investment objectives, decision and satisfaction.
5. The factors of level of investor’s satisfaction do not differ significantly with respect to share investments.
1.5 SCOPE OF THE STUDY
The present study covers the investment pattern with regard to retail investment in equity shares. This study opens fascinating vistas over investor’s
21 preference, perceptional differences and their predominant objectives. This also paves the way to study the pre and post investment satisfaction in an intensified manner. It also focuses exact problems associated with equity investment of retail equity investors in Chennai city.
1.6 GEOGRAPHICAL COVERAGE
The area of coverage of the study is Chennai the capital of Tamilnadu in India. Chennai is opted for study because of its role in industrial and economic development of the country.
1.7 FIELD WORK AND COLLECTION OF DATA
Personal interview by the researcher is the major tool used for data collection. Structured interview schedule is used during personal interviews. Interviews are conducted at various stock broking houses and at the residence of the equity investors at their convenience. Before the interview, proper rapport is established. The data collected are recorded by the researcher in the interview schedule. The schedules thus filled up are thoroughly checked to ensure accuracy, consistency and completeness. On an average, each interview took about an hour. The data thus collected were categorized and posted in the master table for further processing.
1.8 LIMITATIONS OF THE STUDY
The major limitations of the study are:-
The study is confined to Chennai District alone. Hence the findings may not be generalised for the other parts of the country.
The study is confined to the retail equity investors alone. Institutional investors remain uncovered.
The limitations associated with the statistical tools are applicable for the tools employed in this study also.
22 RESEARCH METHODOLOGY
1.9 PILOT STUDY AND PRE-TESTING
A preliminary investigation is undertaken by contacting 75 investors of equity shares to identify the important variables regarding characteristic features of equity shares, instrument and the changes, return of investments, investment decisions and satisfaction. The purpose of the pilot study is to test the quality of the items in the questionnaire and to confirm the feasibility of the study. This preliminary investigation is conducted in different parts of Chennai. The random sampling method, Cronbach alpha method and Hotellings t-square test are applied. It is found that the Cronbach alpha value is 0.912 and hotelling t-square value is 422.31 which are statistically significant at 5 per cent level.
It is ascertained that the items in Likert’s five point scale of the questionnaire are highly reliable and the samples satisfy the normal distribution rationally. So, the items in the questionnaire can be used further in the study.
1.10 MAIN STUDY
The data is collected for the study by means of a two section questionnaire (refer Appendix). Section 1 for the questionnaire is framed to obtain the general information about investment preferences, percentage of investment in equity shares and different portfolio and sources of information of the equity investment. Section II deals with the characteristic features of equity shares, their changes, and return on investments. The section –I of the questionnaire is designed in optional type, where as the section II is designed in Likerts 5-point scale, ranging from 5-strongly agree, 4-agree, 3-neutral, 2-disagree, 1-strongly disagree. The questionnaire with covering letter is handed over personally to each and every respondent and they are requested to return the filled in questionnaire after 15 days, when the researchers visit them. The respondents took the period of 15 days to 2 months to return the completed questionnaire.
23 1.11 SAMPLE SIZE
Initially 623 questionnaires are circulated to investors in all the areas of Chennai city, by following simple random sampling method. Out of the 623 questionnaires only 514 respondents returned the filled in questionnaires. But only 507 of them are found usable. Hence, the exact sample of the study is 507.
1.12 DATA ANALYSIS
The sources of data are primary as well as secondary. The data collected from the investors’ survey constitutes primary and information gathered through books, journals, magazines, reports, dairies are considered as the secondary source. The data collected from both the sources is scrutinized, edited and tabulated. The data is analyzed using statistical package for social sciences (SPSS) and other computer packages. The following statistical tools are used in the study.
1. Measures of central tendency and measures of dispersion.
2. Parametric t-test.
3. One-way analysis of variance.
4. Factor analysis.
5. K-means cluster analysis.
6. Multiple discriminant analysis
7. Multiple regression analysis.
8. Non-parametric chi-square analysis
1.13 OPERATIONAL DEFINITIONS a. Investment
The use of capital is to create money, either through income producing vehicles or through more risky ventures designed to create capital gains.
24 b. Investment Practices
Usual and repeated way of doing investment (i.e.) usual investment pattern, preferences, perceptions, investment objectives, factors generally influencing investments, investment satisfaction, investor’s confidence and problems faced by investors regularly. c. Retail Equity Investor
Individual share investor or households investing in shares or small investor. d. Institutional Investor
Corporates investing huge money in securities. e. Primary Market
A market where corporates directly issue securities i.e., where initial public offering is made. f. Secondary Market
A market where the already issued securities are traded. g. Mutual Funds Small investor, collective investment scheme. h. Derivatives
Financial contracts, whose values are derived from the value of an underlying primary financial instrument (i.e.) stock futures and options. i. Dividend
The part of company’s profit distributed to shareholders. j. Capital Gain
25 Gain arising due to sale of stock. k. Liquidity
Availability of stock coupled with buyers and sellers for it in the market. l. Volatility
Sharp rise or fall of share prices over a short period of time. m. Rights, Bonus and Stock Splits
Rights : A Method of raising additional capital from the existing share holders.
Bonus : Shares are issued to the existing shareholders at free of cost in some decided ratio.
Stock splits : Splitting the face value of existing shares and distributing additional shares on pro-rata to shareholders. n. Floor Based, Forward Trading
Trading on the stock exchange floor, where contracts traded today are settled at some future date at the price decided today. o. Anonymous Screen Based Electronic Trading
Buying and selling of securities using computers and electronic matching of orders on price / time priority without knowing who the trader is. p. Clearing and T+2 Rolling Settlement
Clearing is the process by which all the transactions between members are settled. T+2 Rolling Settlement is the system where trades executed during the day are settled based on the net obligations for the day. The maximum time that may be taken for settlement is T+2 (i.e.) Trading day + 2 working days.
26 q. Straight Through Processing (STP)
STP is a system, which allows electronic capturing and processing of transactions in one pass from the point of order origination to the final settlement. r. Dematerialisation
The process by which shares in the paper form are converted into electronic form popularly called as demat. s. Market Capitalisation
The market value of a company found by multiplying the number of ordinary shares outstanding with its current market price. t. Fundamental Analysis
Method of predicting the behaviour of company stock by looking at fundamental information about the company such as financial health, sales, earnings and dividends. u. Technical Analysis
Techniques of predicting share price behaviour by studying the price movements and trading volumes using charts. v. Corporatisation and Demutualisation
The system where ownership, management and trading membership would be segregated from one another. w. Settlement Guarantee Fund
Fund maintained by the stock exchange to take care of investor claims, which may arise out of non-settlement of obligations by the trading member as he has been declared a defaulter or expelled.
27 x. Circuit Breakers
It is an investor protection measure by SEBI to curb excessive price volatility. It brings about a nation – wide coordinated halt in trading on all equities. y. Mark-to-Market Margin
It is a risk containment measure computed based on mark-to-market loss of a trading / clearing member. z. VaR Based Margins
It is a risk containment measure intended to cover the largest loss that can be encountered on 99% (value at risk) of the days.
1.14 CHAPTER ARRANGEMENT
Chapter - I Introduction - deals with a brief account on history of equity shares, elements of equity shares, need and importance of the study and research methodology.
Chapter - II Review of literature - relevant to the present study, studies on information search, awareness of factors of characteristics of equity shares and capital market and investment preferences are included in this chapter.
Chapter - III A conceptual frame work of Indian Equity shares - An Overview - explains the growth of the market, trends in various years and certain important overviews.
Chapter - IV Analysis of investment preference and decision deals with an analysis of primary data with the help of statistical tool.
Chapter - V Analysis of investment satisfaction and portfolio choice –encounters with multivariate statistical analysis of the primary data
28 Chapter - VI Summary of Findings, Suggestions and Conclusions - summarizes the findings along with the suggestions to the investors for framing the investment strategies.
1.15 SUMMARY
In this chapter, the research design is adopted as per the norms and followed by review of literature in the next chapter.
REFERENCES
1 Levine and Ross, “Stock market Development and Economic Growth”, The world Bank Economic Review, Vol. 1012), 2008, pp: 323 – 339.
2 Bajpai G.N, “Indian Securities Markets – New Bench Marks”, SEBI Bulletin, Vol.1, No.8, August 2009, pp: 5-14.
3 “Retail Investments into Equity”, IIM Working paper series, E27119, p:4.
4 Tarapore wala, Russi Jai, “The Union Budget 2005 -06 and the Capital Market”, BMA Review, Vol. III, No.26, March 14-278, 2006.
5 Ramesh Gupta, “Retail Investor – A lost Species”, IIM Working paper series, E 15378, p:1.
6 Chopra V.K, “Capital Market Reforms in India: Recent Initiatives”, SEBI Bulletin, Vol.4, No. 11, Nov 2008, pp: 7-11.
7 Chopra V. K, “Investor Protection: An Indian Perspective”, SEBI Bulletin, Vol.4, No.11, Nov 2010, pp: 11-15.
8 Ibid., Pp.24-26
29
CHAPTER - II
REVIEW OF PREVIOUS STUDIES
INTRODUCTION
Chapter two portrays review of literature, which briefly discusses about six objectives which is stated in the objectives of the study.
Behavioural Finance is the study of how humans interpret and act on information to make informed investment decisions. It is one of the most interesting and fascinating fields of research throwing light on the motives, preferences, perceptions and expectations of the investors. The emergence of behavioural finance has presented a new realm for analyzing the ways in which investors make decisions that includes psychological factors, as well as providing new grounds of modeling investor behaviour. The study of investor behaviour has attracted researchers with a variety of backgrounds. In this chapter the various literatures over a period of 10 years has been reviewed and presented.
2.2 The investment profile and pattern of retail equity investors.
1. Mart Grinblatt and Matti Keloharju, (2011), in their study entitled, “The Investment Behaviour and Performance of Various Investor Types: Study of Finland’s Unique Data set”, analysed the extent to which past returns determine the propensity to buy and sell. The study revealed that foreign investors tend to be momentum investors, buying past winning stocks and selling past losers. Domestic investors, particularly households contradicted the same. This difference in Investor behaviour was consistent in regular intervals. The portfolios of foreign investors outperformed the portfolios of households, even after controlling the behaviour difference.
2. Maruthu Pandian. P, Benjamin Christopher , (2010), conducted a study entitled, “A Study on Equity Investor Awareness” in order to study the stock
30 market literacy of the investors about the company, stock exchanges as well as capital market regulatory bodies. The primary data using multiple regression, path analysis and chi-square test along with ANOVA clearly revives difference in the awareness among the investors. The research work found that the awareness index is high among young male investor, post- graduates and meticulous business men.
3. Society for Capital Market Research and Development, (2009), conducted a survey entitled, “Indian Household Investors Survey-2004”, the study was based on direct interviewing of a very large sample of 5908 household heads over 90 cities and across 24 states. The study states that price volatility, price manipulation and corporate mismanagement / fraud have persistently been the household investors’ top three worries in India. A large percentage of investors had a negative opinion on company managements. A majority of retail investors in India do not regard mutual fund equity schemes as a superior investment alternative to direct holding of equity shares. Retail investors overwhelmingly prefer bank deposits rather than liquid / money market funds. Shareholding in 3-10 companies is the dominant practice among retail shareholders in all income and age classes. Middleclass investors are long term and conservative. Equity shares have achieved a much higher degree of penetration among middleclass households compared to other capital market instruments.
4. HorstRaff and Michael J.Ryan, (2008), in their paper, “Firm-Specific Characteristics and the Timing of Foreign Direct Investment Projects”, this paper uses a proportional hazard model to study foreign direct investment by Japanese manufacturers in Europe between 1970 and 1994. We divide each firm’s investment total into a sequence of individual investment decisions and analyze how firm-specific characteristics affect each decision. We find that total factor productivity is a significant determinant of a firm’s initial and subsequent investments. Parent-firm size does not have a significant influence on the initial decision to invest. Large firms simply have more investments than smaller firms. Other firm-specific characteristics, such as
31 the R&D intensity, export share and keiretsu membership, also play a role in the investment process.
5. Sudershan kuntluru and D. Mohd Akbar Alikhan , (2009) , in their article, “Financing pattern of foreign and domestic owned pharmaceutical companies in India”, foreign Direct investment has often seen as major source of long term capital which provides bundle of other benefits to the host county company. In this paper, we made an attempt to examine the financing pattern of foreign and domestic owned pharmaceutical companies in India. It has been hypothesized that there is no significant difference between the financing pattern of domestic and foreign owned companies. The financing pattern has been analyzed based on traditional methodology such as common size statement, trend analysis and ratio analysis. The results and analysis indicate mat domestic companies are highly levered than foreign owned companies in pharmaceutical industry.
6. William A. Birdthistle and M. Todd Henderson, (2009), in their article, “one Hat Too many? Investment Desegregation in private Equity”, the nature of private-equity investing has changed significantly as two dynamics have evolved in recent years: portfolio companies have begun to experience serious financial distress, and general partners have started to diversify and desegregate their investment strategies. Both developments have led private- equity shops—once exclusively interested in acquiring equity positions through leveraged buyouts—to invest in other trenches of the investment spectrum, most particularly public debt. By investing now in both private equity and public debt of the same issuer, general partners are generating a host of new conflicts of interest between themselves and their limited partners, between multiple general partners in the same consortia, and between private investors and public shareholders.
7. Diptendu simlai, (2009), in his paper, “An inquiry into the origin and growth of the capital market in India”, India’s modern capital market did not emerge in a day. This market, since its inception in the 18th century with the
32 establishment of the Bank of Hindustan (1770) in Calcutta, laid the foundation of the modern capital market in India according to A. K. Sur, a noted stock market economist of his time (Sur, Evolution of Capital Market in India, Economic Affairs, Nov-Dec/1960). The objective of this paper is to trace the evolution of this market right from the late 18th century up to our times. For purposes of our study the entire time span has been divided into four periods. The first covers the 18th and 19th centuries. The second extends from the early 20th century up to 1947, the year of Independence. For the enormous impact of the economic reforms upon the capital market, the post-Independence era has been divided into two periods: one ending with 1990 and the other starting with 1991.
8. Yadagiri. M and P.Rajender, (2009), in their article, “Analysis of investment portfolio of scheduled commercial banks”, the reforms have unleased tremendous changes in the banking sector. The government of India issued guidelines to the banks by permitting and encouraging them to diversify their activities and contributing to the equity of companies by offering financial services.
2.3 The information search and investment option of retail investors.
9. Bloomfield, Libby and Nelson, (2011), in their study entitled, “Confidence and the Welfare of Less Informed Investors”, have indicated that less informed investors are over confident in investments. Providing more information to professional investors only could harm the welfare of less informed investors if less informed investors are not aware of the extent of their informational disadvantage.
10. Statman, (2010), in his research entitled, “A Century of Investors”, compared the investors a century ago with investors today. He concluded that today’s investors are more rapidly informed than their predecessors, but they are neither better informed nor better behaved.
33 11. Stout, (2010), in his study entitled, “The Investor Game”, has indicated that investors have adaptive and not rational expectations. Adaptive expectations result in both trust and mistrust in securities market based on past actions.
12. Shivkumar Deene, Madari D.M and Gangashetty, (2009), in their paper, “Capital market Reforms: some issues”, capital market is vital for the development and strength of economy. A strong and vibrant capital market assists corporate world initiatives, finance and exploration of new processes and instruments facilitates management of financial risk. Retail investor is the backbone of the capital market. But with the expansion of the capital market, scams and anomalies, also multiplies. It ultimately leads to the dilution of the faith of the small investor, mutual funds, pension funds, Foreign Institutional Investor and insurance companies in the capital. Realising that the government made different as capital market reforms. This includes educating capital market participants regarding their rights and duties for proper functioning of capital market.
13. Alok Kumar, (2009), in his paper, “Who Gambles In the Stock Market? “this paper examines whether socio-economic and psychological factors, which are known to influence lottery purchases, lead to excess investment in lottery-type stocks. The results indicate that, unlike institutional investors, individual investors prefer stocks with lottery-type features. The demand for lottery-type stocks increases during bad economic times and demand shifts influence the returns and idiosyncratic volatility of those stocks. The evidence of the study indicates that people’s attitudes towards gambling are reflected in their stock investment choices and stock returns.
14. Nagarajan. R, (2006), in his article, “Green shoe option in IPO”, for stabilizing post-listing share price, a company making an Initial Public Offer (IPO) through the Book Building mechanism can hold the Green Shoe Option. This is an option that allows underwriter of an Initial Public Offering to sell additional shares to the public. The challenge for the regulator would be to keep fraudulent issues away from the market. In order to avoid
34 fraudulent issues investors too should do their homework before investing in IPO, because it is investor's hard earned money and he should invest it carefully.
15. Subha. M.V, (2008), in her article entitled, “Indian Capital Markets–A Road Ahead”, addressed the current issues in the Indian capital market, lack of individual participation and the ways of restoring investor confidence. The article concluded that the responsibility of creating an environment of trust and confidence lies with the regulators, stock exchanges and companies. Each of them should act in a responsible way and provide a healthy atmosphere for the functioning of an efficient capital market.
16. Kavitha Ranganathan (2008), in their paper, “A study of fund selection behavior of individual investors towards mutual funds: With reference to Mumbai city”, consumer behavior from the marketing world and financial economics has brought together to the surface an exciting area for study and research: Behavioral finance. As this is a serious subject analysts seem to treat financial markets as an aggregate of statistical observations, technical and fundamental analysis. A rich view of research waits this sophisticated understanding of how financial markets are also affected by the “financial behavior” of investors. Hence, this study is an attempt to examine the related aspects of the fund selection behavior of individual investors towards mutual funds, in the city of Mumbai and it showed the way for further research in this field.
17. Jones Nilsson , (2007), in his article, “Investment with a Conscience: Examining the Impact of Pro-Social Attitudes and Perceived Financial Performance on Socially Responsible Investment Behavior”, this article addresses the growing industry of retail socially responsible investment (SRI) profiled mutual funds. The study examined the impact of a number of pro-social, financial performance, and socio-demographic variables on SRI behavior in order to explain why investors choose to invest different proportions of their investment portfolio in SRI profiled funds. Some 528
35 private investors including women were investigated the results showed that women and better-educated investors were more likely to invest a greater proportion of their investment portfolio in SRI. Overall, the findings indicate that both financial perceptions and pro-social attitudes are connected to consumer investment in SRI.
18. Mahabaleswara Bhatta. H.S., (2009), in his paper, “Behavioral Finance- A discussion his individual investor biases”, in this article, an attempt has been made to throw light on the investors’ biases that influence decision making process. Empirical studies have time and again proved that the irrational behaviors have caused stock market bubbles and crashes. The knowledge so developed through the studies would provide a framework of behavioral principles within which the investors react. The article suggests for a time bound program to educate and counsel the individual investors about the wisdom required in stock trading and be aware of unethical and tactical practices of brokers ,shady dealings of the companies and the insider trading.
19. Chattopadhyay. P, (2010), in his article, “Retail investors in IPO subscription”, in the liberalization regime of India, there has been a renewed emphasis on the equity cult and a growing stress of what is termed market capitalization. The number of retail investors has already become substantial and is still growing. This underlines the need for safety and security of the money invested along with the promise of augmented yield. These have required the government and the regulatory bodies to provide necessary systems and methods for safeguarding the interests of the small, retail investors The Securities and Exchange Board of India has recently mooted a proposal to the effect that in the cases of retail investors seeking to subscribe to the share offers by the public limited companies, cash transactions should take place only after the allotment has been made. The proposed intention of SEBI is to be lauded; there are other parts which are not as commendable. The proposal does not appear fool-proof on one side, and may be easily subject to abuse, on the other. Least of all, the proposal may not restore
36 parity between the institutional and retail investors, which is the major objective of the new approach. The steps taken by the regulatory authorities are not enough and the centrifugal forces triggered internally, that would lead to undesirable repercussion.
2.4 Investment preferences and investors perception on risk and return.
20. Rajarajan. V, (2011), conducted a study entitled, “Investors Life Styles and Investment Characteristics”, with the objective of analyzing the investors life styles and to analyse the investment size, pattern, preference of individual investors on the basis of their life styles. Data was collected from 405 investors in Madras using questionnaire method. The investors were classified into 3 groups’ viz., active investors, individualists and passive investors. Cluster Analysis, Correspondence Analysis and Kruskal Wallis Test were used to study the association between lifestyle groups and the various investment related characteristics. The study revealed that the level of expenses, earnings and investment were associated with the size of the household. Active investor group was dominated by officers, individual group by clerical cadre and passive investors group by professionals. The expected rate of return from investments varied between investment styles. The study clearly indicated that market performance of the share, company’s operating level, capital performance and the expectation of the investors were found to influence the risk perception of the investors.
21. Bandgar. P.K, (2011), in his study entitled, “A Study of Middleclass Investor’s Preferences for Financial Instruments in Greater Bombay”, studied the existing pattern of financial instruments in India and the performance of middle class investors, their behaviour and problems. Questionnaire was administered to collect data. Average, Skewness, Chi-square test and Fisher Irving Test were used to analyse the data. The study revealed that only 16% of the investors were facing difficulties in buying and selling securities. Middle-class investors were highly educated but they were lacking skill and knowledge to invest. Female investors preferred to invest in risky securities
37 as compared to male investors. The study also revealed that there was a moderate and continuing shift from bank deposits to shares and debentures, and a massive shift towards traditional financial instruments namely, life insurance policies and government securities.
22. Charles Lee, M.C and Balakrishna Radhakrishna, (2010), in an article entitled, “Inferring Investor Behaviours: Evidence from TORQ Data”, made an attempt to examine the several techniques commonly used to infer investor behaviour from transaction data. They adopted Lee-Ready (1991) algorithm for distinguishing trade decision. The results show that frequency, size and direction of observed trades provide a reasonable basis for evaluating the incoming flow of market orders.
23. Dechow, Hutton and Sloan, (2011), in their study entitled, “Mastering Finance”, found that analysts’ growth forecasts are routinely over optimistic around new equity offerings, but the most over optimistic are those analysts employed by the lead underwriters of the offerings.
24. Malcolm Baker and Jeffrey Wurgler, (2011), in their paper, “A catering theory of dividends”, we develop a theory in which the decision to pay dividends is driven by investor demand. Managers cater to investors by paying dividends when investors put a stock price premium on payers and not paying when investors prefer nonpayer. To test this prediction, we construct four time series measures of the investor demand for dividend payers. By each measure, nonpayer’s initiate dividends when demand for payers is high. By some measures, payers omit dividends when demand is low. Further analysis confirms that the results are better explained by the catering theory than other theories of dividends.
25. Selvam. M, et.al, (2010), in their study entitled, “Equity Culture in Indian Capital Market’, examined the need for promoting equity culture, which deserves special attention for the development of economic growth. The study discussed in detail the current trend of equity culture, its implications
38 and its revival and remedial measures. The study suggested intervention by government, SEBI and RBI and evaluation of suitable credit policy for projects in order to assure safety and assured returns to the investors, in order to restore investor confidence.
26. Alexander LJungquist and Matthew Richardson , (2010), in his study, “The Investment Behaviour of Private Equity Fund managers”, using a unique dataset of private equity funds over the last two decades, this paper analyzes the investment behavior of private equity fund managers. Based on recent theoretical advances, we link the timing of funds’ investment and exit decisions, and the subsequent returns they earn on their portfolio companies, to changes in the demand for private equity in a setting where the supply of capital is ‘sticky’ in the short run. We show that existing funds accelerate their investment flows and earn higher returns when investment opportunities improve and the demand for capital increases. Increases in supply lead to tougher competition for deal flow, and private equity fund managers respond by cutting their investment spending. These findings provide complementary evidence to recent papers documenting the determinants of fund-level performance in private equity.
27. Santi Swarup. K, (2010), in his survey entitled, “Measures for Improving Common Investor Confidence in Indian Primary Market: A Survey”, analysed the decisions taken by the investors while investing in primary markets in the first part: secondly the factors affecting primary market situation in India was analysed and finally the survey evaluates various revival measures available for improving investor confidence. The survey was conducted in 10 cities in India by mailing questionnaire. The survey results of 367 investors revealed that the investors give importance to own analysis and market price as compared to broker’s advice.
28. Stephanie Desrosiers, Jean - Francois L”Her and Jean – Francois Plante , (2010), in their article, “Style management in Equity Country Allocation”, strategies that entailed country selection based on relative strength
39 (momentum) posted significant market risk– adjusted returns over the past 30 years, but relative-value strategies based on book value of equity to market value of equity did not. Because these two fixed-style strategies are negatively correlated, using them for style diversification and for style timing (rotation) is potentially rewarding. In the study described here, style diversification enhanced return and lowered risk but style timing provided consistent risk-adjusted performance that was superior to the performance of fixed-style strategies or style diversification.
29. Jaspal Singh and subhash chandler , (2011) , in their article, “Investors’ preference for investment in mutual funds: An empirical evidence”, since interest rates on investments like PPF, NSC, bank deposits, etc., are falling, the question to be answered is: What investment alternative should a small investor adopt? One of the alternatives is to invest in capital markets through mutual funds. This helps the investor avoid the risks involved in direct investment. Considering the state of mind of the general investor, this article figures out: (i) the preference attached to different investment avenues by the investors; (ii) the preference of mutual funds schemes over others for investment; (iii) the source from which the investor gets information about mutual funds; and (iv) the experience with regard to returns from mutual funds. The results show that the investors consider gold to be the most preferred form of investment, followed by NSC and post Office schemes. Hence, the basic psyche of an Indian investor, who still prefers to keep his savings in the form of yellow metal, is indicated. Investors belonging to the salaried category, and in the age group of 20-35, years showed inclination towards close-ended growth (equity-oriented) schemes over the other scheme types. A majority of the investors based their investment decision on the advice of brokers, professionals and financial advisors. The findings also reveal the varied experiences of respondents regarding the returns received from investments made in mutual funds.
30. Gnana Desigan. C. et.al, (2011), in their study entitled, “Women Investors Perception Towards Investment–An Empirical Study”, identified the
40 investment pattern, preference, influencing factors and problems of women investors in Erode town. The findings of the study reveal that, women investors prefer to invest in bank deposits and jeweler, they are influenced by safety and liquidity and the problems faced by them are cumbersome procedures and formalities, commission and brokerage.
31. Shobana. V.K. and Jayalakshmi. J, (2010), in their study entitled, “Investor Awareness and Preferences”, studied the investors’ preferences, the level of investor awareness and the factors influencing investor awareness of 100 respondents in Salem District. The study reveals that real estate, bank deposits and jeweler were the preferred investments. Investors above 50 years of age, post graduates and professionals had high level of awareness. Age and education do not have any significant influence over investor awareness but occupational status leads to difference in the awareness level of people.
32. Meir Statman, Steven Thorley and Keith Vorkink, (2010), in their paper, “Investor overconfidence and Trading volume”, the proposition that investors are overconfident about their valuation and trading skills can explain high observed trading volume. With biased self-attribution, the level of investor overconfidence and thus trading volume varies with past returns. We test the trading volume predictions of formal overconfidence models and find that share turnover is positively related to lag returns for many months. The relationship holds for both market-wide and individual security turnover, which we interpret as evidence of investor overconfidence and the disposition effect, respectively. Security volume is more responsive to market return shocks than to security return shocks, and both relationships are more pronounced in small-cap stocks and in earlier periods where individual investors hold a greater proportion of shares.
33. Viswambharan A.M, (2008), in his article entitled, “Indian Primary Market – Opportunities and Challenges”, has examined the recent trends in primary market, the current IPO system – book building process, opportunities for
41 investors, problems faced by the investors and has suggested that investors should rely on long term investment than speculation. Investor education shall be strengthened. Commercial banks may take-up investment consultancy for their clients to improve investor participation.
34. Narendra Jadhav, (2010), in his article, “Development of Securities Market – The Indian Experience”, the Indian securities markets have witnessed far- reaching reforms in the post-liberalization era in terms of market design, technological developments, settlement practices and introduction of new instruments. The markets have achieved tremendous stability and as a result, have attracted huge investments by foreign investors. There still is tremendous scope for improvement in both the equity market and the government Securities market. However, it is the corporate debt market, which needs to be given particular emphasis given its importance for providing long-term finance for development.
35. Dan palmon and Fred Sudit, (2011), in their article, “shareholders’ defensive security shares”, the purpose of this paper is to explore the possibilities and merits of offering shareholders an equity instrument (new class of common shares) designed to protect their investments from managerial opportunism. To this end, we propose a special class of shares, the Shareholders ’ Defensive Security Shares (SDSS), which would oblige Boards of Directors to declare a pre-specified extra dividend whenever executive pay exceeds a contractually pre-determined threshold. SDSS could be extended into a larger class of Defensive Security Instruments (DSI) that includes regular bonds, convertible bonds, and preferred stocks. We argue that this defensive equity, the Shareholders ’ Defensive Security, or SDSS, could be beneficial to managers as well as shareholders. What’s more, the use of SDSS is completely voluntary and requires no additional regulation.
36. Kameswari. P, (2008), in his article, “Foreign Direct investment and its role in developing Indian economy”, investment is an important factor in influencing the economic development of a country. Developing countries
42 like India have investment requirements far greater than their domestic savings can meet. Their investment deficits can be bridged by foreign capital flows in the form of Foreign Direct Investment and Portfolio Investment. But the huge flows of foreign capital may introduce some problems like inflation. In the interest of future economic growth and development a developing economy has to institute some safeguards in its national interest while welcoming the foreign investment. This article studies how India is faring in its efforts to attract foreign direct investment and in channelising the flows for the growth of economic development.
37. Som Sankar Sen and Santanu Kumar Ghosh , (2008) , in their paper, “Stock Market Liquidity of BSE and NSE: A Comparative Study (1995- 2005)”, this study compares between BSE and NSE in terms of Stock Market Liquidity during the study period of January 1995 to December 2005. The study reports that mean liquidity of NSE is higher than that of the BSE during this period. It also reveals that in most of the months BSE remains more vulnerable than NSE during this span of time in terms of liquidity. A monthly pattern of liquidity could be observed in case of NSE but no such monthly pattern is there in case of BSE. Finally, a positive correlation between these two exchanges has been reported indicating no significant movement of volume from one exchange to another.
38. Nissim Ben David, (2008), in his paper, “An indicator for internalization of analyst’s recommendations by investors”, this paper proposes an index for evaluating the internalization of an analyst’s recommendations by investors at various points of time that follow the recommendation day. The model is applied to the Israeli stock market for the years 2004 and 2005. The results indicate that investors in the Israeli stock market internalize a recommendation 14 days after its publication. Internalization continues 30 days after the publication day. The importance of this paper is that it is the first time an index for evaluating investor’s reaction to analyst’s recommendations in various stock markets has been proposed. Such information is valuable, since it can improve investment strategies that
43 follow the publication of an analyst’s recommendation. An investor would prefer buying a recommended stock when he expects a large return and would sell it when the recommendation’s effect is exhausted.
39. Mohanty. B.K , (2008), in his article, “Market capitalization: A suitable growth approach for share holders’ value creation”, before economic reforms were initiated in 1991, companies in the Indian corporate sector had to function amidst the license regime, quotas and restrictions, high taxes and host of other rules and regulations. Companies are now allowed to borrow from and invest abroad quite liberally. All this has done wonders for corporate India. Over the past 15 years of reforms, corporate profits have gone from Rs. 6440 crore in financial year 1991 to Rs.1,67,801 crore in financial year 2006.
40. Henry L. Petersen and Harrie Vreden burg, (2009), in their article, “Morals or Economics? Institutional Investor Preferences for Corporate Social Responsibility”, this article presents the results of a study that analysed whether social responsibility had any bearing on the decision making of institutional investors. Being that institutional investors prefer socially aligned organizations, this study explored to what extent the corporate actions and/or social/environmental investments influenced their decisions. Our results suggest that there are specific variables that affect the perceived value of the organization, leading to decisions to not only invest, but whether to hold or sell the shares, and therefore having a consequential impact on the capital market’s valuation.
41. Sakthivel. N, (2010), in his paper, “EVA – MVA: Shareholders’ value measure”, maximizing shareholders value is becoming the new corporate standard in India. The corporate, who gave the lowest preference to the shareholders’ inquisitiveness, are now bestowing the utmost inclination to it. Shareholders’ value is measured in terms of the returns they receive on their investment. The returns can either be in the form of dividends or in the form of capital appreciation or both. For measuring the corporate financial
44 performance, there are accounting profitability measures and shareholders’ value based measures. Accounting profitability measures include ROI, ROE, EPS, ROCE and DPS etc., Shareholders valued based measures include EVA and MVA. EVA in Indian environment and relationship between EVA (Economic Value Added) and MVA (Market Value Added).
2.5 Factors influencing investment evaluation and decision of investors.
42. Iran Peacock and Stuart Cooper, (2011), in their article, “Private equity: implications for financial efficiency and Stability”, this article (1) describes the current state of the UK private equity market. It also considers the extent to which private equity promotes efficiency by facilitating the ‘shake-up’ of businesses, and whether the success of investment houses in attracting substantially increased funds for investment poses any threats to financial stability. Private equity comprises equity investment in all types of unquoted companies, whether provided by individuals, funds or institutions.(2) The article concentrates on larger transactions (particularly management buy-outs and buy-ins of over £10 million), and excludes start-up and early-stage venture capital finance, which in effect forms a distinct market with different characteristics.
43. Security Exchange Board of India (SEBI) along with National Council of Applied Economic Research (NCAER), (2011), conducted a comprehensive survey of the Indian investor households entitled, “Survey of Indian Investors”, in order to study the impact of the growth of the securities market on the households and to analyse the quality of its growth. 25,000 investors were drawn from places all over India and the data were collected by administering questionnaire and through personal interviews. The survey was carried out with the major objective of drawing a profile of the households and investors and to describe the demographics, economic, financial and equity ownership characteristics. The study revealed that majority of the equity investors had long term motive of investment.
45 Investors revealed that they had a number of broker related problems than the issuer related problems.
44. David R. Gallagher, (2011), in his study, “Investment manager characteristics, Strategy, top management changes and fund performance”, this study examines the performance of Australian investment management organisations with direct reference to their specific characteristics and strategies employed. Using a unique information source, performance is evaluated for actively managed institutional balanced funds, Australian share funds and Australian bond funds. The study examines the performance of top management and the impact on returns when turnover arises. The research documents that a significant number of active Australian equity managers earned superior risk-adjusted returns in the period; however active managers perform in line with market indices for balanced funds and Australian bond funds.
45. Hall, (2011), has conducted research entitled, “Do Brokers Buy, Hold and Sell Recommendations of Value to Individual Investors? he found that investors, who invested in the Johannesburg Securities Exchange (JSE) based on their brokers’ advice, were able to get risk adjusted returns superior or equal to the market.
46. Santi Swarup. K, (2010), in his study entitled, “Role of Mutual Funds in Developing Investor Confidence in Indian Capital Markets”, identified safety and tax savings as the important factors affecting investment in various avenues by the investor and developed strategies for enhancing common investor confidence such as good return, transparency, investor education, guidance etc.
47. Mohammad salahuddin and Md. Rabiul Islam, (2010), in their article, “Factors affecting investment in developing countries: A panel data study”, this paper investigates the gross investment behavior in a panel of 97 developing countries spanning a period between 1973 and 2002. Fixed Effect Model is employed to analyze data. Variance Inflation Factor (VIF) test is
46 conducted to ensure that the data are free from multicollinearity. Also, Granger Causality test is conducted to see if reverse causality exists. 2- Step 1st Difference Generalized Method of Moments (GMM) dynamic panel estimator has been employed to offset unobserved heterogeneity and endogeneity of regressors. The results suggest that investment decisions still seem to be significantly affected by traditional determinants such as growth, domestic savings, trade openness etc. The variable aid appeared to potentially affect investment which calls for developing country’s measures to ensure proper utilization of it.
48. Alexandra Dawson , (2004), in his study, “Investigating decision- making criteria of private equity investors in family firms”, this paper examines decision-making models used by private equity investors in their selection of family firms. Building on literature on investment criteria at start-up stage, a series of hypotheses is put forward, based on decision-making, strategic management and buyout theories. The theoretical model is tested through an experimental design for which data have been collected among 41 respondents based in Italy. Findings are analysed using hierarchical linear models, in order to investigate which criteria are used, assess their relative importance and test whether decision-making models are individual-specific or influenced by the firm individuals work for.
49. Xuewu wang, (2004), in his paper, “sentiment strategies”, this paper documents the profitability of the sentiment strategies. Using the aggregate closed-end fund discount as a proxy for investor sentiment, a simple sentiment strategy is constructed on the basis of the exposure of stock returns to the closed-end fund discount. The sentiment strategies buy stocks with highest exposure to closed-end fund discount and sell stocks with lowest exposure to closed-end fund discount in the past 36 months. It is shown that such a strategy can lead to an annualized profit of 11%. The source of the profitability is explored and it is found that neither market risk nor momentum anomaly can account for the profitability. However, the traditional four factor asset pricing model when augmented with an
47 additional sentiment factor can account for the profit. This finding is interpreted as supportive evidence to the fact that the pricing of the investor sentiment risk may be a potentially useful explanation for profitability.
50. Arvid O I Hoffmann and Wander jager, (2005), in their paper, “The effect of different needs, decision-making processes and network-structures on investor behavior and stock market dynamics: A simulation approach”, striking investor and stock market behavior have been recurrent items in the world press for the recent past. Crashes and hypes like the internet bubble are often hard to explain using existing finance frameworks. Therefore, the authors provide a complementing multi-theoretical framework that is built on existing finance research to describe and explain investor’s behavior and stock market dynamics. This framework is built on three main components: Needs, decision-making theory, and (social) network effects. This framework will be used to build a future simulation model of investor behavior and to generate stock market dynamics. A brief outline of the design of these simulation experiments as well as examples of the first results will be given.
51. Qiang Cheng and Terry D. Warfield, (2005), in their article, “Equity incentives and earnings management”, this paper examine the link between managers’ equity incentives. We hypothesize that managers with high equity incentives are likely to sell shares in the future and this motivates these managers to engage in earnings management to increase the value of the shares to be sold. Using stock – based compensation and stock ownership data over the 1993- 2000 time period, we document that managers with high equity incentives sell more shares in subsequent periods. As expected, we find that managers with high equity incentives are more likely to report earnings that meet or just beat analysts’ forecasts. We also find that managers with consistently high equity incentives are less likely to report large positive earnings surprises. This finding is consistent with the wealth of these managers being more sensitive to future stock performance, which leads to increased reserving of current earnings to avoid future earnings
48 disappointments. Collectively, our results indicate that equity incentives lead to incentives for earnings management.
52. Vibha Mahajan and Poonam Aggarwal, (2005), in their paper, “Foreign investment – need for a more competitive and open policy”, the forces driving globalization are changing the way in which MNCs pursue their objectives of investing abroad. Traditional factors such as existence of a pro- FDI regime, natural resources, market growth prospects and market size, labor market conditions are important and also the surveys conducted by UNCTAD during the first quarter of 2004. FDI flows are expected to pick up particularly in Asia and Pacific and CEE. China and India in Asia and Poland in CEE is considered to be especially well positioned for an upswing. This paper is an attempt to find out ways how India can attract foreign investment.
53. Marcela Meirelles Aurelio, (2008), in his article, “Going Global: The Changing pattern of U.S. Investment Abroad”, over the past decade, U.S. holdings of foreign financial assets- stocks and bonds – have grown remarkably. At the same time, foreign physical assets, such as foreign direct investment in production plants, have also become far more common. Overall, the share of U.S. investments allocated to foreign assets swelled from 40 percent of GDP in 1990 to 89 percent in 2005. This article investigates the recent behavior of U.S. foreign investment and the factors driving the change in its fastest growing category – namely, international equity investment. Home bias in U.S. equity investment has indeed during the last decade. However, the propensity to invest abroad has varied significantly across assets from different foreign economies. Specifically, U.S. investors tend to prefer investing in other industrial countries rather than in emerging markets. This pattern has likely been developed because the assets of industrial countries provide a better hedge during downturns in the U.S. business cycle.
54. Minh Quang Dao, (2009), in his paper, “The impact of investment climate indicators on gross capital formation in developing countries”, this paper
49 examines the impact of investment climate indicators on gross capital formation in developing countries. Based on data from the World Bank Investment Climate Surveys for a sample of thirty-six developing countries, we find that corruption constraint as measured by the share of senior managers that ranked “corruption” as a major or very severe constraint in the investment structure.
55. Maria May Seitanidi, (2007), in his paper, “Intangible economy: how can investors deliver change in businesses? Lessons from nonprofit-business partnerships”, the intangible economy (trust, human resources, information, and reputation) that co-exists draws attention to new expectations that request the continuous, active and within the public sphere involvement of investors in order to protect their assets by prioritising intangible resources. Design/methodology/approach – In this paper the case of non-profit-business partnerships is employed in order to demonstrate how change can be achieved. Findings – The paper finds that investors in intangible outcomes who aim to achieve change in corporations share the same limitations within the financial and non-financial field. Originality/value – The paper highlights investment in the intangible economy as a mechanism of co-determining the priority of responsibilities in the context of corporate social responsibility. The role of investors is crucial in facilitating the shift from the tangible to the intangible economy.
56. Brimberg. J , P Hansen , G Laporte , N Mladenovic and D Urosevic , (2008), in their article, “ The maximum return-on-investment plant location problem with market share”, this paper examines the plant location problem under the objective of maximizing return-on-investment. However, in place of the standard assumption that all demands must be satisfied, we impose a minimum acceptable level on market share. The model presented takes the form of a linear fractional mixed integer program. Based on properties of the model, a local search procedure is developed to solve the problem heuristically. Variable neighbourhood search and tabu search heuristics are also developed and tested. Thus, a useful extension of the simple plant
50 location problem is examined, and heuristics are developed for the first time to solve realistic instances of this problem.
57. Kenneth A. Froot and Tarun Ramadorai, (2008), in their article, “Institutional portfolio Flows and international investments”, using a new technique, and weekly data for 25 Countries from 1994 to 1998, we analyze the relationship between institutional cross-border portfolio flows, and domestic and foreign equity returns. In emerging markets, institutional flows forecast statistically indistinguishable movements in country closed-end fund NAV returns and price returns. In contrast, closed-end fund flows forecast price returns, but not NAV returns. Furthermore, institutional flows display trend-following (trend-reversing) behavior in response to symmetric (asymmetric) movements in NAV and price returns. The results suggest that institutional cross-border flows are linked to fundamentals, while closed-end fund flows are a source of price pressure in the short run.
58. Shollapur. M.R. and A B Kuchanur, (2008), in their article, “Identifying perceptions and perceptual Gaps: A study on individual investors in selected investment avenues”, investors hold different perceptions on liquidity, profitability, collateral quality, statutory protection, etc., for various investment avenues. In addition, they fix their own priorities for these perceptions. The formation of perceptions triggers the investment process in its own way, often leading to unrealistic apprehensions especially among individual investors. This study attempts to measure the degree of investors’ agreeableness with the selected perceptions as well as to trace the gaps between their perceptions and the underlying realities. Failure to deal with these gaps tends to lead the investment clientele to a wrong direction. Hence, there is a need to help investors develop a realistic perspective of the investment avenues and their attributes.
59. Eva Hofmann, Erik Hoelzl and Erich Kirchler , (2008) , in their article, “ A comparison of models Describing the impact of moral decision making on investment decision”, as moral decision making in financial markets
51 incorporates moral considerations into investment decisions, some rational decision theorists argue that moral considerations would introduce inefficiency to investment decisions. The investment decisions are influenced by both financial and moral considerations. Several models can be applied to explain moral behaviour. The study tested the suitability of (a) multiple attribute utility theory (MAUT), (b) theory of planned behavior, and (c) issue-contingent model of ethical decision making in organizations. Results indicate that moral considerations influence investment decisions, controlling for profit. Differences between the three models are discussed.
60. Malcolm Baker and Yuhai xuan, (2009), in their study entitled, “Under New management: Equity Issues and the Attribution of past Returns”, there is a strong link between measures of stock market performance and equity issues. Typically, this performance is considered a characteristic of the firm, not the CEO who happens to run the firm. In contrast, we find that equity issues depend on changes in Q and returns to a greater extent if the current CEO was at the helm when those past returns were realized. Moreover, the specific share price that the CEO inherited is an important reference point, while salient share prices prior to turnover are not. A corollary is that a firm with poor stock market performance will not raise new capital unless the current CEO is replaced.
2.6 Investors level of satisfaction and their futuristic perceptions towards retail equity investment.
61. Fieldstein and Yitzhaki, (2011), in their study entitled, “Are High Income Individuals Better Stock Market Investors?” have presented evidence to suggest that the corporate stock owned by high-income investors appreciate substantially faster than stock owned by investors with lower incomes. They have indicated that high-income individuals have larger portfolios and can therefore denote more time or resources to their investments, thus resulting in higher returns.
52 62. Panda. K, Tapan N.P and Tripathi, (2011), in their study entitled, “Recent Trends in Marketing of Public Issues: An Empirical Study of Investors Perception”, attempted to identify the investors awareness and attitude towards public issues. One hundred and twenty five investors covering the salaried and business class, from the city of Bhuvaneshwar were selected at random. The data was collected by administering a questionnaire and was analysed using simple percentage and weighted average analysis. The study revealed that majority of the investors relied on newspapers as the source of information. Financial journals and business magazines were ranked next to newspapers. A large number of investors were of the opinion that they were not in a position to get the required information from the company in time. A sizable number of investors were found to face problems while selling securities. ‘Safety and Regular Return’ stood first and second with regard to the factors associated with investment activities. Equity shares were preferred for their higher rate of return by the investors.
63. Hong Kong Exchanges and Clearing Ltd (HKEx) conducted the “Derivatives Retail Investor Survey (DRIS)”, for the first time in 2001–2002 to study retail participation in the Hong Kong derivatives market and the investment behaviour attitude and opinions of derivative investors in Hong Kong. DRIS was conducted in two stages through a mail questionnaire survey and personal interviews. The survey revealed that investors were predominantly males in their 40’s, mostly highly educated and of a high working class. HSI futures and options were the preferred ones. The median number of years of experience in trading was 4 years and the median trading frequency was 1-2 times a week. The median deal size was HK $ 60,000. Males were found to trade more frequently than females. Higher income group had a higher usual deal size. Profit was the motive behind trading derivatives. Overall, the mail survey respondents’ perceptions of HKEx derivatives market were positive.
64. Deborah Tan and Julia Henker, (2011), in their article, “Idiosyncratic volatility and retail investor preferences in the Australian market”, we explore the negative relation between idiosyncratic volatility and future stock
53 returns observed by previous researchers. We argue that, based on the observation described in prospect theory, retail investors prefer stocks with a high level of idiosyncratic volatility and are subsequently willing to overpay for those stocks. In support of our argument, we find that the negative idiosyncratic-volatility return relation is present in the Australian market, and that this relation is affected by the magnitude of retail trading. The relation is particularly strong when returns and realized volatility are measured at a daily frequency.
65. Julan Du, (2010), in his paper, “heterogeneity in investor confidence and asset market under-and overreaction”, this paper develops a behavioral finance model that may explain under reaction and overreaction in asset markets from the perspective of heterogeneous investors with different confidence levels. The model explains the occurrence of under reaction by the sequential entry of investors with different confidence levels in interpreting earnings shocks. It is shown that in repeated trading episodes with repeated earnings shocks, the average investor confidence level would be higher as a result of the biased self-attribution and confirmatory bias, causing overreaction more likely to occur. Also, the higher average confidence level of investors gauged by the later timing of winding up their asset holding positions also makes overreaction more likely to occur.
66. Lieven Baele ,Olivier De Jonghe and Rudi Vander Vennet , (2005) , in their paper, “ Does the stock market value bank diversification? “this paper investigates whether or not diversified banks have a comparative advantage in terms of long-term performance/risk profile compared to their specialized competitors. To that end, this study uses market-based measures of return potential and bank risk. We calculate the franchise value over time of European banks as a measure of their long-run performance potential. In addition, we measure risk as both the systematic and the idiosyncratic risk sensitivities derived from a bank stock return model. Finally, we analyze the return/risk trade-o¤ implied in different diversification strategies using a panel data analysis over the period 1989-2004. Diversification affects banks’
54 franchise values positively. Diversification increases the systematic risk of banks while the effect on the idiosyncratic risk component is non-linear and predominantly downward- sloping. These findings have conflicting implications for different stakeholders, such as investors, bank shareholders, bank managers and bank supervisors.
67. Andreas Kemmerer and Tom Weidig, (2005), in his study, “Reporting Value to the private Equity Fund Investor”, in this article, we look at the actual reporting behaviour and information flow of the private equity (mainly venture capital) fund manager to the fund investors, based on access to a fund investor’s database. Overall, the study revealed we find that the European private equity industry has improved their reporting qualitatively and quantitatively, especially in terms of shorter delivery times of reports. This change is mainly due to the introduction of the EVCA reporting guidelines and willingness by both, fund managers and investors, to report voluntary or contractually bind by contract to report in accordance to these standards. The study also pointed out that aspects of the relationship between the entrepreneur and fund manager are also often found at the next level, between fund managers and investors.
68. Masashi Toshino and megumi suto, (2005), in their paper, “Cognitive biases of Japanese institutional investor’s consistency with behavioral finance,” this paper investigates the cognitive biases to which Japanese institutional investors are subjects. Investors showed optimism in forecasting market returns, and this tendency was much more significant for domestic markets and for longer forecasting time-horizons. This optimism is consistent with the existence of availability heuristics. Herding behavior was also detected. In addition, Japanese institutional investors showed loss aversion, as suggested by Tversky and chainman (1979). The median of the relative weight for loss versus gain was two or three, depending on the amount of possible loss, and this number is consistent with a coefficient of 2.25 for the value function estimated in Tversky and kahneman (1992). We conclude that the concepts of behavioral finance have universality in the sense that they are
55 pertinent among institutional investors as well as students, and that they are found in an Asian country as well as the U.S.
69. John R. Graham, Alokkumar, (2006), in their study entitled, “Do Dividend Clienteles Exist? Evidence on Dividend Preferences of Retail Investors”, studied the stockholding and trading behaviour of more than 60,000 households and found evidence consistent with dividend clienteles. Retail investor stockholdings indicate a preference for dividend yield that increases with age and decreases with income, consistent with age and tax clienteles respectively. Trading patterns reinforce this evidence.
70. Ming Dong, Chris Robinson and Chris veld, (2006), in their paper, “why individual investors want dividends”, the question of why individual investors want dividends is investigated by submitting a questionnaire to a Dutch investor panel. The respondents indicate that they want dividends, partly because the transaction costs of cashing in dividends are lower than the transaction costs involved in selling shares. Their answers provide strong confirmation for the signaling theories of Bhattacharya (1979) and Miller and Rock (1985). They are inconsistent with the uncertainty resolution theory of Gordon (1961, 1962) and the agency theories of Jensen (1986) and Easterbrook (1984). The behavioral finance theory of Shefrin and Statman (1984) is not confirmed for cash dividends but is confirmed for stock dividends. Finally, the results indicate that individual investors do not tend to consume a large part of their dividends. This raises some doubt as to the effectiveness of the reduction or elimination of dividend taxes in order to stimulate the economy.
71. Michael Kaestner, (2006), in his article, “investors’ Misreaction to unexpected earnings: evidence of simultaneous overreaction and under reaction”, this article investigates the current and past earnings surprises and subsequent market reactions for listed US companies over the period 1983- 1999. The results suggest that investors simultaneously exhibit short-term under reaction to ‘earnings announcements’ and long-term overreaction to
56 ‘past highly unexpected earnings’. A potential explanation for the reported overreaction phenomenon is the representativeness bias. The author shows that overreaction and the later reversal is stronger for events which exhibit a long series of similar past earnings surprises.
72. Sadhan Kumar Chattopadhyay and Samir Ranjan Behera , (2006) , in their paper, “Financial Integration for Indian Stock Market”, the Indian stock market is considered to be one of the earliest in Asia, which is in operation since 1875. However, it remained largely outside the global integration process until 1991. The reform of the Indian stock market started with the establishment of Securities and Exchange Board of India (SEBI), although it became more effective after the stock market scam in 1991. With the establishment of SEBI and technological advancement Indian stock market has now reached the global standard. The study finds that contrary to general belief, Indian stock market is not co-integrated with the developed market as yet. It is derived from the study that although some positive steps have been taken up, which are responsible for the substantial improvement of the Indian stock market, these are perhaps not sufficient enough to become a matured one.
73. Larry D. Wall, (2007), in his article, “on investing in the equity of small firms”, this comment provides a brief discussion of the roles of different investors in small business firms. It then evaluates the contribution made in papers by in this issue by Robinson and Cottrell on informal investors in Alberta, Canada, and by Pintado, Perez de lema, and van Auken on venture capital investment in Spain.
74. Som Sankar Sen., Bidyut Kumar Ghosh and Dr. Santanu Kumar Ghosh, (2007), “Stock Market Liquidity and Exchange Rate – A Case Study on BSE & NSE “, this paper explores significant impact of exchange rate on stock market liquidity. Taking monthly data on both BSE and NSE the paper reveals the positive relationship between exchange rate and stock market liquidity in concurrent, lagged and lead forms. Using R2 statistic it shows a
57 considerable variation in liquidity is explained by exchange rate in both the major stock exchanges in India.
75. Gerben de zwart, Brian Frieser and Dick van Dijk , (2007), in their article, “ A recommitment strategy for long term Private equity fund investor”, this paper develops a reinvestment strategy for private equity which aims to keep its portfolio weight equal to a desired strategic allocation, while taking into account the illiquid nature of private equity. Historical simulations (1980{2005) show that our dynamic strategy is capable of maintaining a stable investment level that is close to the target. This does not only hold for unrestricted portfolios, but also for investments limited to buy-out or venture capital, a specific region, or management experience. This finding is of great importance for investors, because private equity funds have a finite lifetime and uncertain cash flows.
76. Michael J. Robinson and Thomas J. Cottrell , (2007), in their article, “ Investment patterns of Informal Investors in the Alberta Private Equity Market”, this study identifies three main types of informal investors in private equity markets: relationship investors, opportunity-based investors, and angel investors. We find evidence that the first two investor types are a major total source of capital and they prefer to invest smaller amounts close to home and in the context of existing relationships. With respect to angel investors, we find evidence of stratification in their desired investment amount which is consistent with a model where their investments evolve though a life cycle of investing. We also find evidence that change to capital market regulations that allow for lower investment amounts by this type of investor increase the amount of capital available for early-stage firms.
77. Costanza Consolandi, Ameeta Jaiswal-Dale, Elisa Poggiani and Alessandro Vercelli, (2008), in their article, “Global standards and ethical stock indexes: The case of the Dow Jones sustainability Stoxx Index”, this article examines whether these incentives have been so far detectable with particular reference to the Dow Jones Sustainability Stoxx Index (DJSSI) that focuses on the
58 European corporations with the highest CSR scores among those included in the Dow Jones Stoxx 600 Index. The aim of the article is twofold. First, we analyse the performance of the DJSSI over the period 2001–2006 compared to that of the Surrogate Complementary Index (SCI), a new benchmark that includes only the components of the DJ Stoxx 600 that do not belong to the ethical index to evaluate more correctly the size of possible divergent performances. Second, we perform an event study on the same data set to analyse whether the stock market evaluation reacts to the inclusion (deletion) in the DJSSI. In both cases, the results suggest that the evaluation of the CSR performance of a firm is a significant criterion for asset allocation activities.
78. Gangadhar. V and G. Naresh Reddy , (2008), in their paper, “The Impact of Foreign Institutional Investment on Stock Market Liquidity and Volatility in India”, this paper is aimed at examining the investment trends and patterns of FIIs and their impact on stock market liquidity and volatility. Liquidity with reference to capital market refers to easy conversion of capital market securities into cash. Whereas the stock market volatility implies the fluctuations in the stock market returns over a time period. Volatility is the inconsistency or variability in the returns of aggregate market portfolio.
79. AI Jun Hou , (2009), in his study, “ EMU Equity markets’ return variance and spill over effects from short-term interest rates”, this paper examines the spillover effects from the movement of short term interest rates to equity markets within the Euro area. The empirical study is carried out by estimating a Markov Switching GJR-M model with a Bayesian based Markov Chain Monte Carlo (MCMC) methodology. The result indicates that stock markets in the Euro area display a significant two regimes with distinct characteristics. The study indicates that there is a significant impact of fluctuations in the short term interest rate on the conditional variance and conditional returns in the EMU countries. Such impact is asymmetrical, and it appears to be stronger in the bear market and when the interest rate changes upward.
59 80. Batni Raghavendra Rao , (2009) , in his paper, “ Exchange traded funds - the cardinal investment option in turbulent times”, the global meltdown, international reputed firms going bankrupt, fudging of accounting numbers and dubious corporate governance have made equity investing more challenging then ever before. The investors are constantly on a look out for secure and promising bets. Stock picking is not easy as it looks and therefore construction of equity portfolio is imperative. The premise that diversification reduces the risk is beyond doubt. Diversification entails scouting of investment avenues in terms of risk and return. It calls for developing a portfolio of assets or securities in such a way to minimize the risk. The individual investors hardly can match up to the institutional investors in terms of the expertise and also majority of them are not market savvy. In this context, Exchange traded funds (ETFs) come in handy to help out the individual investors in the stock market. ETFs are the safe bets and provide scrupulous diversification. In fact in the developed markets ETFs are the most sought after means of investing in the equities. In India ETFs are yet to catch up the attention of the investors.
81. Mamunur Rashid1 and Md. Ainun Nishat, (2009), in their article, “Satisfaction of retail investors on the structural efficiency of the market: Evidence from a developing country context”, satisfied investors are a necessary element of the stock market. They help to finance rapid expansion in developing countries. This study explores the components of market structure that contribute to the satisfaction level of retail investors. Around 300 retail investors from 25 randomly selected brokerage houses registered with the Dhaka Stock Exchange, Bangladesh were surveyed using a structured questionnaire. Analyses reveal that most investors were young and inexperienced but educated, with shortages of skills and income. The study suggests the importance of effective regulation, disclosure requirements to ensure a supply of quality information, investor education and technology driven trading in brokerage houses for overall investor satisfaction.
60 82. Raja. M and J. Clement sudhakar, (2010), in their article, “An empirical test of Indian stock market efficiency in respect of bonus announcement”, as capital market is said to be efficient with respect to an information item if the prices of securities fully impound the return implications of that item. The efficiency with which the capital formation is carried out depends on the efficiency of the capital markets and financial institutions. A capital market is said to be efficient with respect to corporate event announcement (stock split, buyback, right issue, bonus announcement, merger & acquisition, dividend etc) contained information and its disseminations. How quickly and correctly the security prices reflect these event contained information show the efficiency of stock markets. Present study is an attempt to test the efficiency of Indian stock market with respect to bonus issue announcement by IT companies.
83. Roopam Kothari and Narendra Sharma, (2010), in their paper, “Testing the Beta stability of banking sector over various phases in Indian stock market”, our study aims at creating a banking stock portfolio which serves as a representative of all the banking stocks traded on Bombay Stock Exchange and testing the beta instability of the banking sector stock portfolio over various phases in the Indian stock market. We also evaluate the monthly stock price returns of the banking portfolio vis-à-vis the market portfolio from the period ranging from July 1994 to December 2008. The journey of Sensex during the span of past fourteen years in the post liberalization period has been divided into three phases based upon technical analysis. An attempt is made to evaluate the under/ over performance of the banking stock portfolio returns under various phases.
2.7 Relationship between demographics variable of investors and their investment objectives, decision and satisfaction.
84. Meenu Verma, (2008), in his article, “Wealth management and behavioral finance: The effect of demographics and personality on investment choice among Indian investors”, with the growth of the Indian economy and the rise
61 in the wealth of the people, there is a growing demand for wealth management functions. Wealth management involves understanding the clients’ financial and investment requirements and accordingly providing financial planning and portfolio management services. Behavioral finance is a nascent but growing discipline, which studies investor’s psychology while making financial decisions. This paper aims to investigate the effect of demographic profile and personality type of the investor on investment choice. Such understanding could prove to be a boon for the burgeoning wealth management industry in India.
85. Manish Mittal and R K Vyas, (2008), in their paper, “personality type and investment choice: An empirical study”, investors have certain cognitive and emotional weaknesses which come in the way of their investment decisions. Over the past few years, behavioral finance researchers have scientifically shown that investors do not always act rationally. They have behavioral biases that lead to systematic errors in the way they process information for investment decision. Empirical evidence also suggests that factors such as age, income, education and marital status affect on individual’s investment decision. This paper classifies Indian investors into different personality types and explores the relationship between various demographic factors and the investment personality exhibited by the investors. The results of this study reveal that the Indian investors can be classified into four dominant investment personalities- casual, technical, informed and cautious.
2.8 Summary
The above review of literature helps to identify the research gaps and frame suitable objectives and hypothesis.
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35. Dan Palmon and Fred Sudit,”Shareholders’ defensive security Shares”, International Journal of Disclosure and Governance Vol.4,3, Palgrave Macmillan Ltd, 2010 PP: 195-203.
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37. Sen S.S. and S.K. Ghosh, “Stock Market Liquidity of BSE and NSE: A comparative study (1999-2005),” Management Accountant ICWAI Journal Vol.43 No.2 February 2008 PP: 55-60.
38. Nissim Ben David, “An indicator for internalization of analyst’s recommendations by investors, “The ICFAI University Journal of Behavioral Finance Vol. V, No. 3, 2008, PP: 23-35.
66 39. Mohanty B.K. “Market capitalization: A suitable growth approach for share holders’ value creation”, The Management Accountant ICWAI Journal Vol.43, No. 8, August 2008, PP: 398-401.
40. Henry L. Petersen and Harrie Vreden burg, “Morals or Economics? Institutional Investor Preferences for Corporate Social Responsibility,” Journal of Business Ethics Vol. 90, 2009, PP: 1-14.
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42. Iran Peacock and Stuart Cooper, “Private equity: implications for financial efficiency and Stability,” Bank of England quarterly Bulletin, February 2000, PP: 69-76.
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44. David R. Gallagher, “Investment manager characteristics, strategy, top management changes and fund performance”, Research paper School of banking and finance, The university of new south wales, Sydney N.S.W. 2052, Australia (2001) PP 1-52.
45. Hall, John.H, “Do brokers buy, hold and sell recommendations of value to individual investors?” University of Pretoria, working paper series, 2002.
46. Santi Swarup K, “Role of Mutual Funds in Developing Investor confidence in Indian Capital Markets”, Sajosps, Vol. 2, No. 2, June 2002, pp: 58-60.
47. Mohammad Salahuddin and Md. Rabiul Islam,” Factors affecting investment in developing countries: A panel data study,” South east university Bangladesh, working paper, 2003, PP: 21-37.
67 48. Alexandra Dawson, “Investigating Decision-making criteria of private Equity investors in family firms,” Bocconi University, working paper, 2004, PP: 1-12.
49. Xuewu wang, “Sentiment strategies,” The ICFAI Journal of Behavioral Finance December 2004, PP: 60-72.
50. Arvid OI Hoffmann and wander Jager, “The effect of Different needs, Decision- making processes and Network-Structures on investor Behavior and stock market Dynamics: A simulation Approach”, The ICFAI Journal of Behavioral Finance, June 2005 PP: 49-64.
51. Qiang Cheng and Terry D. Warfield,” Equity incentives and earnings management,” The Accounting Review Vol.80, No. 2, PP: 441-476.
52. Vibha Mahajan and Dr. Poonam Aggarwal, “Foreign investment – need for a more competitive and open policy”, The Management Accountant ICWAI Journal Vol.40, No. 6, June 2005, PP: 475-480.
53. Marcela Meirelles Aurelio, “Going Global: The changing pattern of U.S. Investment Abroad,” Economic – Federal Reserve Bank of Kansas city Vol.93 No.3, Third quarter 2006 PP: 5-33.
54. Minh Quang Dao, “The impact of investment climate indicators on Gross capital formation in developing countries,” Eastern Illinois university, USA, working paper, 2006, PP: 1-10.
55. Maria May seitanidi, “Intangible economy: how can investors deliver change in business? Lessons from non profit business partnerships”, Management Decision Journal, Emerald Group publishing limited Vol.45 No.5 2007 PP: 853-865.
56. Brimberg J., P. Hansen, G. Laporte, N. Mladenovic and D. Urosevil, “ The Maximum return-on- investment plant location problem with market share,” Journal of the operational Research society Vol. 59 No. 3 2008 PP: 399-406.
68 57. Kenneth A.Froot and Tarun Ramadorai, “Institutional portfolio Flows and international investments,” The Review of Financial studies Vol. 21 No.2, 2008 PP: 1-36.
58. Shollapur M.R. and A B Kuchanur, “Identifying perceptions and perceptual Gaps: A study on individual investors in selected investment avenues”, The ICFAI University Journal of Behavioral Finance, Vol. V, No. 2, 2008, PP: 47- 61.
59. Eva Hofmann, Erik Hoelzl and Erich Kirchler, “A comparison of models describing the impact of moral decision making on investment decision”, Journal of Business Ethics, Vol. 82, 2008, PP: 171-187.
60. Sen S.S. and S.K. Ghosh, “Stock Market Liquidity of BSE and NSE: A comparative study (1999-2005),” Management Accountant ICWAI Journal Vol.43 No.2 February 2008 PP: 55-60.
61. Feldstein, Martin S., Yitzhaki, Shlomo, “Are high income individuals better stock market investors?” nber w0948, 2000.
62. Panda K, Tapan N.P and Tripathi, “Recent Trends in Marketing of Public Issues: An Empirical Study of Investors Perception”, Journal of Applied Finance, Vol. 7, No.1, 2001, pp: 1-6.
63. Hong Kong Exchanges and clearing Ltd (HKEx), (2001-02), “Derivatives Retail Investor Survey (DRIS)”.
64. Deborah Tan and Julia Henker,”Idiosyncratic volatility and Retail Investor Preferences in the Australian Market,” The Australian School of Business, University of New South Wales working paper 2002, PP: 1-55.
65. Julan Du, “heterogeneity in investor confidence and asset market under-and overreaction”, The ICFAI Journal of Behavioral Finance, June 2004, PP: 55- 85.
69 66. Lieven Baele,” Olivier De Jonghe and Rudi vander Vennet, “Does the Stock Market value bank diversification? “ Federal public planning service science policy, inter university Attraction 2005 PP: 1-27.
67. Andreas Kemmerer and Tom Weidig, “Reporting value to the private Equity Fund investor,” University of Frankfurt, working paper, 2005, PP: 1-49.
68. Masashi Toshino and Megumi suto,” Cognitive biases of Japanese institutional investor’s consistency with behavioral finance,’ The ICFAI Journal of Behavioral Finance, March 2005 PP: 7-18.
69. John R. Graham, Alokkumar, “Do Dividend Clienteles Exist? Evidence on Dividend Preferences of Retail Investors”, The Journal of Finance, Vol. 61, Issues 3, June 2006, pp: 1305-1336.
70. Ming Dong, Chris Robinson and Chris veld, “Why individual investors want dividends,” The ICFAI Journal of Behavioral Finance, Vol. III, No. 2, 2006, PP: 27-62.
71. Michael Kaestner, “investors’ Misreaction to unexpected earnings: evidence of simultaneous overreaction and under reaction,” The ICFAI Journal of Behavioral Finance, March 2006, PP: 32-42.
72. Sadhan Kumar Chattopadhyay and Samir Ranjan Behera, “Financial Integration for Indian Stock Market”, Department of Economic Analysis and policy of the RBI, Working paper, 2006, PP: 1-29.
73. Larry D. Wall, “On investing in the Equity of small firms”, Journal of small Business management 2007 45 (1) PP: 89-93.
74. Sen S.S.,B.K. Ghosh and Santanu Kumar Ghosh, “ Stock market liquidity and Exchange Rate –A case study on BSE & NSE”, The Management Accountant ICWAI Journal Vol.42, No.10 October 2007 PP: 820-821 & 830.
70 75. Gerben de zwart, Brian Frieser and Dick van Dijk, “A recommitment strategy for long term private equity fund investor,” ERIM report series research in management, ERS – 2007-097 – F&A, 2007, PP: 1-46.
76. Michael J. Robinson and Thomas J. Cottrell, “Investment patterns of informal investors in the Alberta private Equity Market,” Journal of small Business Management Vol. 45, No. 1 PP: 47-67.
77. Costanza Consolandi, Ameeta Jaiswal-Dale, Elisa Poggiani and Alessandro Vercelli,
“Global standards and ethical stock indexes: The case of the Dow Jones sustainability Stoxx Index”, Journal of Business Ethicks Vol.87. 2008, PP: 185- 197.
78. Gangadhar V. and G. Naresh Reddy, “The Impact of Foreign Institutional Investment on Stock Market Liquidity and Volatility in India”, The Management Accountant ICWAI Journal Vol. 43, No. 3, March 2008, PP: 179- 84.
79. Ai Jun Hou, “EMU Equity markets’ return variance and spill over effects from short-term interest rates,” Department of Economics, Lund university, Sweden, working paper 2009 PP: 1-35.
80. Batni Raghavendra Rao, “Exchange Traded Funds – the cardinal investment option in turbulent times,” The Management Accountant ICWAI Journal, Vol.44 No. 6, June 2009, PP: 464-467.
81. Mamunur Rashid1 and Md. Ainun Nishat, “satisfaction of retail investors on the structural efficiency of the market: Evidence from a developing country context,” Asian Academy of management Journal, Vol. 14, No. 2 , July 2009, PP: 41-64.
71 82. Raja M.and J.Clement sudhahar,” An Empirical test of Indian Stock Market Efficiency in Respect of Bonus Announcement”, Asia pacific Journal of Finance and Banking Research Vol.4 No.4, 2010 PP: 1-14.
83. Roopam Kothari and Narendra Sharma,” Testing the Beta Stability of Banking Sector over various Phases in Indian Stock market,” The Management Accountant ICWAI Journal Vol.45 No.7 July 2010 PP: 591-595.
84. Meenu Verma, “Wealth management and behavioral finance: The effect of demographics and personality on investment choice among Indian investors”, The ICFAI University Journal of Behavioral Finance, Vol. V, No. 4, 2008, PP: 31-57.
85. Manish Mittal and R K Vyas, “personality type and investment choice: An empirical study”, The ICFAI University Journal of Behavioral Finance, Vol. V, No. 3, 2008, PP: 6-22.
72 CHAPTER – III
INDIAN CAPITAL MARKETS – AN OVERVIEW
INTRODUCTION
Chapter three gives brief account of capital market developments in India under various heads like Indian capital market before 1990’s , Indian capital market after 1990’s, primary market developments, secondary market developments, SEBI registered market intermediaries, mutual funds, derivatives, foreign institutional investments, screen based trading system, depositories, clearing, processing and settlement system, risk management system, margin trading facility, Regulatory frame work for investor protection, security Regulations in force, security guidelines in force, grievances redressal mechanism, investor education, recent initiatives and Indian capital market future road map.
Capital market is the backbone of any country’s economy. It is an engine for economic growth, providing an efficient means of resource mobilisation and allocation. The literature is full of theoretical and empirical evidence that have established robust, statistically significant two-way relationship between the developments in the securities market and economic growth. Levine and Zervos (1998) argue that well developed stock markets may be able to offer financial services of different kind that may provide a different kind of impetus to the economic development1. In India, Agarwall’s (1999), study clearly supports the Levine and Zervos’s argument and proves that the two main parameters of capital market development namely, size and liquidity, are found statistically significant to explain the economic activity.2
The Indian capital market is one of the oldest capital markets in the world. It dates back to the 18th century when the securities of the East India Company were traded in Mumbai and Kolkata. However, the orderly growth of the capital market began with the setting up of The Stock Exchange of Bombay in July 1875 and Ahmedabad Stock Exchange in 1984. Eventually 19 other Stock Exchanges sprang up in various parts of the country.3 In this chapter an attempt has been made by the
73 researcher to review the Capital Market Developments that has taken place in India in two phases such as: i. Indian Capital Market – Before 1990’s ii. Indian Capital Market – After 1990’s
3.2. INDIAN CAPITAL MARKET – Before 1990’s
India’s Capital Market was dormant till the mid – 1980‘s.4 The long term financing needs of the corporate sector were met by the Development Financial Institutions (DFI’s) namely IDBI, IFCI, ICICI as well as by other investment institutions like LIC, UTI, GIC etc. Working capital needs were met by the Commercial Banks through an elaborate network of bank branches spread all over the country. Capital Market activities were limited mainly due to the easy availability of loans from banks and financial institutions and administered structure of interest rates. However, three important legislations namely Capital Issues (control) Act 1947: Securities Contracts (Regulation) Act, 1956; and Companies Act, 1956 were enacted to provide suitable legal framework for the development of capital market in India. The pricing of the primary issues was decided by the Office of the Controller of Capital Issues. A few stock exchanges, dominated by Bombay Stock Exchange (BSE) provided the trading platforms for the secondary market transactions under an open outcry system.
As of 1992, the Bombay Stock Exchange (BSE) was a monopoly.5 It was an association of brokers, and imposed entry barriers; leading to elevated costs of intermediation. Membership was limited to individuals; limited liability firms could not become brokerage firms. Trading took place by ‘open outcry’ on the trading floor, which was inaccessible to users. It was routine for brokers to charge the investor a price that was different from what is actually transacted at.
Retail investors and particularly users of the market outside Bombay, accessed market liquidity through a chain of intermediaries called “sub–brokers”. Each sub–broker in the chain introduced a mark-up in the price, in the absence of unbundling of professional fees from the trade price. It was common for investors in small towns to face four intermediaries before their order reached the BSE floor, and to face mark-ups in excess of 10% as compared with the actual trade price. The
74 market used ‘futures–style settlement’ with fortnightly settlement. A peculiar market practice called ‘badla’ allowed brokers to carry positions across settlement periods. In other words, even open positions at the end of the fortnight did not always have to be settled. The efficiencies of the exchange clearing house only applied for the largest 100 stocks. For other stocks, clearing and settlement were done bilaterally, which introduced further inefficiencies and costs.
The final leg of the trade was physical settlement, where the share certificates were printed on paper. This was intrinsically vulnerable to theft, counterfeiting, inaccurate signature verification, administrative inefficiencies, and a variety of other malpractice. Involuntary and deliberate delays in settlement could take place both at the BSE and at the firm. Many firms used the power of delaying settlement as a tool to support manipulation of their own stock. The problems were somewhat simpler for investors in Bombay, who could physically visit the BSE broker, the BSE clearinghouse, or the company’s Registrar, and accelerates transfer. For investors outside Bombay, who lacked this recourse and were crippled by the exorbitantly expensive telephone system, delays of six months between purchasing a stock and the transfer of legal title were common. If stock splits, rights issues, or dividend pay-outs took place during this period, it was common for the purchaser not to obtain the benefits.
Floor–based trading, the inefficiencies in clearing and settlement entry barriers into brokerage, and the low standards of technology and organisational complexity that accompanied the ban upon corporate membership of the BSE led to an environment where order execution was unreliable and costly. 6 These factors led to an extremely poor functioning of the capital markets till 1992.
3.3. INDIAN CAPITAL MARKET – After 1990’s
The Indian capital markets have witnessed a major transformation and structural change during the past one and half decades, since the early 1990’s.7 The Financial Sector Reforms in general and the Capital Market Reforms in particular were initiated in India in a big way since 1991 – 1992. These reforms have been aimed at improving market efficiency, enhancing transparency, checking unfair trade practices and bringing the Indian capital market up to the International
75 Standards. The Capital Issues (control) Act, 1947 was repealed in May 1992 and the office of the Controller of Capital Issues was abolished in the same year. The National Stock Exchange (NSE) was incorporated in 1992 and was given recognition as a Stock Exchange in April 1993, which has been playing a lead role as a change agent in transforming the Indian Capital Market to its present form.8 The Securities and Exchange Board of India (SEBI) was set up in 1988 and acquired the statutory status in 1992. Since 1992, SEBI has emerged as an autonomous and independent statutory body with definite mandate such as: (a) to protect the interests of investors in securities, (b) to promote the development of securities market and (c) to regulate the securities market. In order to achieve these objectives, SEBI has been exercising power under: (a) Securities and Exchange Board of India Act, 1992, (b) Securities Contracts (Regulation) Act, 1956, (c) Depositories Act, 1996 and delegated powers under the (d) Companies Act, 1956. Indian Capital Market has made commendable progress since the inception of SEBI and has been transformed into one of the dynamic capital markets of the world.9 The statistics on International equity Markets as on December 31, 2009 given in Table-1 clearly highlights this.
Table – 3.1
International Equity markets (End December 2010) 10
Market No. of Value of Share No. of Exchange Capitalisation Listed trading trading (US $ Million) Companies (US $ Million) days Americans American SE 132367 486 561603 253 Lima SE 71663 241 4532 249 Mexican Exchange 352045 406 84255 252 Nasdaq 3239492 2852 28951349 252 NYSE 11837793 2327 17784586 252 Santiago SE 230732 236 38103 250 Sao Paulo SE 591966 392 724199 249
76 Europe-Africa Middle East 112632 288 66702 248 Athens Exchange - - - - Copenhagen SE 783 2186433 254 Deutsche Borse 1292355 1002 4411249 256 Euronext 2101746 64 35077 253 Irish SE 61291 411 395235 251 JSE South Africa 482700 76 1216 251 Ljubljana SE 12141 2792 3391103 253 London SE 2796444 267 281 253 Luxembourg SE 105048 238 245008 251 Oslo Bors 227233 339 759369 251 Swiss Exchange 1064687 486 57012 252 Warsaw SE 150962 115 47952 248 Wiener Borse 114076 Asia – Pacific Australian SE 1261909 1966 931555 254 BSE the SE 1306520 4955 263352 243 Mumbai 286157 959 86033 250 Bursa Malaysia 9547 231 1238 240 Colombo SE 2305143 1319 1501638 249 Hong Kong 89567 889 31169 243 Exchanges 834597 1788 1559040 253 Jakarta SE 1224806 1453 786684 243 Korea Exchange 35507 165 14901 252 National SE of India 138330 432 139868 243 New Zealand 86349 248 20802 242 Exchange 2704779 870 2061643 244 Osaka SE 868374 830 2774065 244 Philippine SE 481247 773 245425 253 Shanghai SE 657610 755 905131 251 Shenzhen SE 176956 535 126097 243 Singapore Exchange 3306082 2335 3990909 243 Taiwan SE Corp. Thailand SE Tokyo SE Source: World Federation of Exchanges.
The milestones achieved during the past one and half decades are discussed below:
77 3.3.1 Primary Market Developments
The 1990’s witnessed the emergence of the Capital Market as a major source of finance for trade and industry in India. A growing number of companies have been accessing the Capital Market rather than depending on loans from financial institutions.11 Tremendous developments have taken place in the primary market where the corporates issue fresh securities through public issues as well as private placements. Huge amount of resources have been mobilised by the corporates from the primary market which is shown in Table-2 below: -
Table – 3.2 Resources Mobilised from the Primary Market12 (Rs. in Crores)
Instrument Wise Year Total Amount Equities CCPS Bonds Others 1998-99 14276 7845 75 5400 957 1999-00 4570 1881 10 1550 1128 2000-01 5587 857 78 4450 202 2001-02 7817 4566 0 3200 51 2002-03 6108 3226 142 2704 36 2003-04 7543 1272 0 5601 670 2004-05 4070 1457 0 2600 13 2005-06 23272 18958 0 4324 0 2006-07 28256 24388 0 3867 0 2007-08 27382 27372 0 0 10 2008-09 33506 32901 0 356 249 2009-10 87029 79739 5687 1603 0 2010-11 14720 14272 0 448 0 Source: SEBI
As on March 31, 2011, Rs. 14,720 crores has been mobilised from the Primary market, out of which Rs. 14,272 crores has been raised through equities and Rs. 448 crores through bonds capital market instruments.
Since the early 1990’s, there has been a paradigm shift from merit based regulated regime to disclosure based regime. Comprehensive guidelines on
78 disclosures and investor protection were issued and were amended by SEBI from time to time. The companies accessing the capital market through public issues have to comply with adequate disclosure norms on initial as well as continuous basis. India’s disclosure norms are considered as one of the best in the world and are often cited as benchmark for the global standards.13 Indian accounting standards are principle based and aligned to international accounting standards. In terms of consolidation segmental reporting, deferred tax accounting and related party transactions, the gap between India and the US is minimal. In addition to sound accounting standards, the issues relating to corporate governance have been pursued in right earnest consistent with the best international practices.
In a deregulated regime, the market determines the price of the public issues, i.e., either by the issuer through fixed price or by the investors through book- building process. A fair system of proportionate allotment of shares has been put in place. The share of retail investors in the allotment of book-built issues has been increased to 35 percent.14 Discretionary allotment to the Qualified Institutional Buyers (QIBs) has been withdrawn. Companies are allowed to issue ADRs/ GDRs and also raise funds through external commercial borrowing. The ADR / GDR’s have two–way functionality. The Foreign Institutional Investors have been allowed to invest in primary issues within the sectoral limits set by the Government.
3.3.2. Secondary Market Developments
The securities issued in the Primary Market are traded in the Secondary Market. Exchanges in India offer screen based, electronic trading. The trading system is connected using the VSAT technology from around 201 cities. There are 8652 trading members registered with SEBI at the end of March 2009. Enormous amount of developments have taken place in the secondary market during the last one decade. The selected indicators in Table-3 below clearly indicate this.
79 Table – 3.3
Secondary Markets – Selected Indicators15
(Amount in Rs. mn)
Capital Market Segment of Stock Exchanges No. No. of S & P Market Year Market Turnover of Listed CNX Sensex Capitalisation Turnover Capitalisation Ratio (%) Brokers Companies Nifty Ratio (%) 1997-1998 8,476 9,100 985.30 3366.61 5,722,570 47.0 2,273,680 39.7 1998-1999 8,867 9,890 968.85 3360.89 4,883,320 34.6 6,461,160 132.3 1999-2000 9,005 9,833 1116.65 3892.75 5,898,750 37.7 9,086,810 154.1 2000-01 9,069 9,877 1078.05 3739.96 5,740,640 34.1 10,233,820 178.3 2001-02 9,192 9,871 1528.45 5001.28 11,926,300 84.7 20,670,310 173.3 2002-03 9,782 9,954 1148.20 3604.38 7,688,630 54.5 28,809,900 374.7 2003-04 9,687 9,644 1129.55 3469.35 7,492,480 36.4 8,958,180 119.6 2004-05 9,519 9,413 978.20 3048.72 6,319,212 28.5 9,689,098 153.3 2005-06 9,368 - 1771.90 5590.60 13,187,953 52.3 16,204,977 122.9 2006-07 9,128 - 2035.65 6492.82 16,984,280 119.1 16,668,963 98.1 2007-08 9,335 - 3402.55 11280.00 30,221,900 85.58 23,901,030 79.09 2008-09 9,443 - 3821.55 13072.10 35,488,081 86.02 29,014,715 81.76 2009-10 9,487 - 4734.50 15644.44 51,497,010 109.3 51,308,160 99.63 2010-11 9,628 - 3020.95 9708.50 30,929,738 58.12 38,520,970 124.54 Source: SEBI & NSE.
73
Market capitalization as percentage to GDP in India reached nearly 58 percent in 2008–09 and still further on a fluctuating trend. The rate of growth in market capitalisation and turnover over the period indicates that more companies have started using the trading platform of the Stock Exchanges. Although there are 22 stock exchanges, the National Stock Exchange (NSE) and the BSE together account for more than 99 percent of the total turnover.
Recently, a separate trading platform, namely BSE Indonext, has been set up jointly by BSE and the Federation of Indian Stock Exchanges to facilitate transactions of shares exclusively relating to the small and medium enterprises. 16
3.3.3. SEBI Registered Market Intermediaries
Various institutions / intermediaries associated with primary as well as secondary markets such as merchant bankers, registrars to issues, portfolio managers, underwriters, bankers to issues, stock exchanges, brokers and sub- brokers, share transfer agents, depositories, FIIs, custodians, credit rating agencies, venture capital funds, collective investment schemes including mutual funds have to register with SEBI and operate within the guidelines issued from time to time. SEBI also promotes self-regulatory organizations. SEBI registered market intermediaries from 1996 which are listed below in Table-4.
74
Table – 3.4
SEBI Registered Market Intermediaries17
As on 31st March
Market
Intermediaries
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Stock Exchanges 22 22 22 23 23 23 23 23 23 22 22 21 19 19 (Cash Market)
Stock Exchanges - - - - 2 2 2 2 2 2 2 2 2 3 (Derivatives Market)
Brokers 8476 8867 9005 9069 9192 9782 9687 9519 9368 9128 9335 9384 8517 8652 (Cash Segment)
Corporate Brokers 1917 2360 2976 3173 3316 3808 3862 3835 3746 3733 3961 4101 3955 4079 (Cash Segment)
Sub Brokers - 1768 3760 4589 5675 9957 12208 13291 12815 13684 23479 27540 43874 62471 (Cash Segment)
75
Brokers (Derivative) - - - - - 519 705 795 829 994 1120 1258 1442 1587
Foreign Institutional 367 439 496 450 506 527 490 502 540 685 882 997 1319 1635 Investors
Custodians - - - - 15 14 12 11 11 11 11 11 15 16
Depositories - 1 1 2 2 2 2 2 2 2 2 2 2 2
Depository - 28 52 96 191 335 380 438 431 477 526 593 654 714 Participants
Merchant Bankers 1012 1163 802 415 186 233 145 124 123 128 130 152 155 134
Bankers to an issue 77 80 72 66 68 69 68 67 55 59 60 47 50 51
Underwriters 40 38 43 17 42 57 54 43 47 59 57 45 35 19
Debenture Trustees 23 27 32 34 38 37 40 35 34 35 32 30 28 30
Credit Rating - - - - 4 4 4 4 4 4 4 4 5 5 Agencies
Venture Capital - - - - - 35 34 43 45 50 80 90 106 132 Funds
Foreign Venture - - - - - 1 2 6 9 14 39 78 97 129 Capital investors
76 Registrars to an Issue & Share Transfer 334 386 334 251 242 186 161 143 78 83 83 82 76 71 Agents
Portfolio Managers 13 16 16 18 23 39 47 54 60 84 132 158 205 232
Mutual Funds 27 37 38 41 38 39 38 38 37 39 38 40 40 44
Collective investment - - - - 0 0 0 0 0 0 0 0 0 1 Schemes
Approved Intermediaries(Stock - 1 1 4 6 8 10 4 3 3 3 3 2 3 Lending Schemes)
Source: SEBI
77 As on March 31, 2009, there were 19 Stock Exchanges, 8635 Brokers (cash segment) and 62,471 Sub-brokers, over 9,000 Listed Companies, 2 Depositories, 714 Depository Participants, 134 Merchant Bankers, 19 Underwriters, 5 Credit Rating Agencies and 1635 Foreign Institutional Investors in India.
3.3.4. Mutual Funds
In order to develop the security cult and also to encourage indirect participation of households in the Indian Securities Market, Mutual Funds have been encouraged, both in the public and private sectors. Huge resources have been mobilised through Mutual Funds. The trend in resource mobilisation by Mutual Funds is indicated in Table-5 below: -
Table – 3.5 Trends in Resource Mobilisation by Mutual Funds18 (Rs. in Crores)
Assets at the Gross Year Redemption Net Inflow end of the Mobilisation period 1993-94 62076 - - - 1994-95 13727 - - - 1995-96 6508 - - - 1996-97 4777 - - - 1997-98 11406 - - - 1998-99 22710 23660 -949 68193 1999-00 61241 52271 18970 107946 2000-01 92957 83829 9128 90587 2001-02 164523 157348 7175 100594 2002-03 314706 310510 4196 109299 2003-04 590190 543381 46808 139616 2004-05 839708 837508 2200 149600 2005-06 1098149 1045370 52779 231862 2006-07 1938493 1844508 93985 326292 2007-08 4464377 4310575 53802 505152 2008-09 5426354 5454650 - 28296 417300 Source: SEBI 77
Currently, there are 44 Mutual Funds including foreign mutual funds, offering more than 400 schemes to the investors .The cumulative Assets Under Management (AUM) of all the Mutual Funds which were Rs. 3,26,292 crores as on March 31, 2007 and has increased to Rs.5,05,152 crores by March 31, 2008. At the end of March 2009 there is a sudden decrease when compared to end of March 2009. For an orderly growth of the mutual funds, prudential regulations have been put in place keeping in view the interest of the investors.
3.3.5. Derivatives
Introduction of securities related derivatives in India is another milestone which provides an important avenue to the investors, mainly for hedging. The securities contract (Regulation) Act, 1956 was amended in December 1999 to expand the definition of securities to include derivatives so that the entire regulatory framework governing trading of securities could apply to trading in derivatives. Derivatives trading began in India with the launch of index futures in June 2000 followed by index options, single stock options and single stock futures in 2001. 19 Interest rate futures were introduced in June 2003. The derivative products have a monthly maturity cycle. From September 13th, 2004 weekly stock and index option was launched on the derivative segment of BSE .Two premier stock exchanges, namely BSE and NSE, provide trading platforms for derivative transactions.
The growth of the derivatives segment at BSE and NSE is indicated below in Table-6.
78 Table – 3.6
Derivatives Segment at BSE and NSE20
No. of No. of Turnover Year Trading Days Contracts (Rs.Crore) BSE 2003-04 207 77743 1673 2004-05 247 99918 1812 2005-06 251 137209 2456 2006-07 254 374637 11743 2007-08 253 531630 16111 2008-09 251 201 9 2009-10 249 1781214 59006 2010-11 243 515588 12268 NSE Jun-00 toMar01 211 90580 2365 2003-04 247 3159344 76764 2004-05 251 13245847 339731 2005-06 254 51303705 1913436 2006-07 253 71972073 2378195 2007-08 251 152378495 4643981 2008-09 249 211600263 7162459 2009-10 251 415552569 12731341 2010-11 243 644094527 10781254 Source: BSE & NSE
Bulk of the derivative trading is done in the NSE. The combined turnover in derivatives on BSE and NSE surpassed the combined turnover in the cash segments since early 2009. During 2009-10, the turnover in the derivative segments of NSE was 223 percent of its cash segment turnover. Similar to international trend, single stock futures emerged as the most popular derivative product, followed by index futures, stock options and index options. NSE ranks first in terms of number of contracts traded in the single stock futures, second in Asia in terms of number of contracts traded in equity derivatives instrument. 21
79 3.3.6. Foreign Institutional Investments
The Foreign Institutional Investors (FIIs) were allowed to invest in India in 1992 under the portfolio investment scheme. They are also allowed to participate in the public issues of debt and equities within the sectoral limits set for equities and the overall limit fixed for the debt instruments by the Government. India has been a centre of attraction for the FIIS. The growth in foreign investment inflows is indicated in below in Table-7.
Table – 3.7
Foreign Investment Inflows22
Year A. Direct Investment B. Portfolio Total (A +B) Investment (Rs. (Us $ (Rs. (US $ (Rs. (US $ Crore) Million) Crore) Million) Crore) Million) 1992-93 174 97 11 6 185 103 1993-94 316 129 10 4 326 133 1994-95 965 315 748 244 1713 559 1995-96 1838 586 11188 3567 13026 4153 1996-97 4126 1314 12007 3824 16133 5138 1997-98 7172 2144 9192 2748 16364 4892 1998-99 10015 2821 11758 3312 21773 6133 1999-00 13220 3557 6794 1828 20014 5385 2000-01 10358 2462 -257 -61 10101 2401 2001-02 9338 2155 13112 3026 22450 5181 2002-03 18406 4029 12609 2760 31015 6789 2003-04 29235 6130 9639 2021 38874 8151 2004-05 24367 5035 4738 979 29105 6014 2005-06 19860 4322 52279 11377 72139 15699 2006-07 27188 6051 41854 9315 69042 15366 2007-08 39674 8961 55307 12492 94981 21453 2008-09 103367 22826 31713 7003 135080 29829 2009-10 138276 34362 109741 27271 248017 61633 2010-11 161481 35168 -63618 -13855 97863 21313 Source: RBl Bulletin
80 Foreign investment inflows both by direct investment and portfolio investment amounted to Rs. 97863 crores and US $ 21313 million as on March 31, 2009.
FIIs have been bullish on the Indian securities. Their net investment every year was positive ever since they were allowed to invest in India except in 1998- 99 & 2008-09 as shown in Table-8 below:
Table – 3.8
Trends in FII Investment23
Gross Cumulative Net Net Gross Sales Net Year Investment Investment Investment Purchases (Rs. (Rs. Crore) (US $ mn) Crore) (US $ mn)
1989-90 18 4 13 4 4
1990-91 5593 467 5127 1634 1638
1991-92 7631 2835 4796 1528 3167
1992-93 9694 2752 6942 2036 5202
1993-94 15554 6980 8575 2432 7635
1994-95 18695 12737 5958 1650 9285
1995-96 16116 17699 -1584 -386 8899
2001-02 56857 46735 10122 2474 11372
2002-03 74051 64118 9933 2160 13531
2003-04 50071 41308 8763 1839 15371
2004-05 47061 44372 2689 566 15936
2005-06 144855 99091 45764 10005 25942
2006-07 216951 171071 45880 10352 36293
81 2007-08 346976 305509 41467 9363 45657
2008-09 520506 489665 30841 6821 52477 2009-10 948018 881839 66179 16442 68919 2010-11 614576 660386 -45811 -9837 59081
Source: RBI Bulletin.
The cumulative net investment by FIIs, which stood at US $ 52,477 million at the end of March 2010, further increased to US $ 68,919 million by the end of March 2011. At the end of March 2009 there is a sudden decrease when compared to end of March 2008. Net investment by FIIs to the tune of roughly US $ 10 billion each for the last two consecutive years vindicated the growth story of the subcontinent. As on March 31, 2010, the number of FIIs registered with SEBI stood at 1319 which further increased to 1635 by the end of March 2011. 24 About 41 percent of total FIIs originate from the USA, followed by the UK (18 percent).
During the last two and half years, the FIIs have identified India as a preferred destination. Strong macro economic fundamentals, favorable tax treatment, attractive valuation of shares and encouraging corporate results have been cited as underlying causes of large portfolio investment by the FIIs in India.
3.3.7. Screen Based Trading System
The screen based trading system is a landmark achievement of the Indian capital market.25 The NSE introduced the screen-based trading since its inception followed by other stock exchanges. The screen-based trading enables the participants for online, electronic, anonymous and order-driven transaction with the help of over 10,000 terminals spread over 400 cities in India and abroad. This is perhaps the biggest trading network in any country of the world. The order matching is done strictly on price/ time priority. The screen-based trading is transparent and provides equal access to all investors irrespective of their geographical locations. Screen-based trading has significantly improved depth and liquidity of the market.
82 3.3.8. Depositories
Depositories Act, 1996 was another landmark development in the history of India’s capital market.26 Thereafter two depositories namely, Central Depository Services Limited (CDSL) and National Securities Depository Limited (NSDL) were set up. NSDL and CDSL have been successful in the dematerialisation of securities to the extent of 99 percent of the total market capitalisation. Currently the transfer of ownership is mostly done through book-entry form. This has tremendously improved the speed, accuracy and security of the settlement system. About 99.9 percent of trades in BSE and 100 percent of trades in NSE as shown in Table-9 below are currently settled through delivery, which is possible only due to dematerialisation of scrip by the two depositories.
83 Table – 3.9
Settlement Statistics for Cash Segment of BSE and NSE27
Year livered
No. of of No.
Trades Trades
(Lakhs)
InDemat
Delivered Turnover Turnover Delivered
(Rs .crore) (Rs
(Rs. Crore) (Rs.
% of Demat Demat of %
Quantity To
Mode (Lakh) Mode
Value to Total to Value
% of Delivered Delivered of % De of %
Delivered Value Delivered
Traded Quantity Traded
Traded Quantity Traded
Quantity(Lakhs)
QuantityTotal to
Delivered Quantity Delivered Quantity Delivered 1 2 3 4 5 6 7 8 9 10 BSE 1992- 93 126 35031 - - 45696 - - - 1993-94 123 75834 - - 84536 15861 18.76 - - 1994-95 196 107248 44696 41.68 67749 26641 39.32 - - 1995-96 171 77185 26763 34.67 50064 11527 23.02 - - 1996-97 155 80926 21188 26.18 124190 10993 8.85 - - 1997-98 196 85877 24360 28.37 207113 22512 10.87 - - 1998-99 354 129272 50570 39.12 310750 85617 27.55 - - 1999-00 740 208635 94312 45.20 686428 174740 25.46 - - 2000-01 1428 258511 86684 33.53 1000032 1666941 16.69 - - 2001-02 1277 182196 57668 31.65 307292 59980 19.52 - - 2002-03 1413 221401 69893 31.57 314073 48741 15.52 - - 2003-04 2005 385806 133240 34.54 503053 107153 21.30 132941 99.78 84
2004-05 2374 477171 187519 39.30 518716 140056 27.00 187347 99.91 2005-06 2643 664467 300653 45.25 816074 271227 33.24 300497 99.95 2006-07 3462 560780 229685 40.96 956185 297660 31.13 229573 99.95 2007-08 5303 986009 361628 36.68 1578855 476196 30.16 361542 99.98 2008-09 5408 739601 196630 26.59 1100074 230332 20.94 196096 99.73 NSE Nov 94 – 3 1330 688 51.74 1728 898 51.98 - - Mar- 95 1995-96 64 39010 7264 18.62 65742 11775 17.91 - - 1996-97 262 134317 16453 12.25 292314 32640 11.17 - - 1997-98 383 135217 22051 16.31 370010 59775 16.15 - - 1998-99 550 165310 27991 16.93 413573 66204 16.01 6179 22.08 1999.00 958 238605 48713 20.42 803050 82607 10.29 26063 53.50 2000-01 1614 304196 50203 16.50 1263898 106277 8.41 47257 94.13 2001-02 1720 274695 59299 21.59 508121 71766 14.12 59169 99.78 2002-03 2403 365403 82305 22.52 621569 87895 14.14 82305 100.00 2003-04 3751 704539 174538 24.77 1090963 220341 20.20 174538 100.00 2004-05 4494 787996 201405 25.56 1140969 276120 24.20 201405 100.00 2005.06 6000 818438 226346 27.66 1516839 407976 26.90 226346 100.00 2006-07 7857 850515 238571 28.05 1940094 543533 28.02 238571 100.00 2007-08 11645 1481229 366974 24.77 3519919 970618 27.58 366974 100.00 2008-09 13639 1418928 303299 21.38 2749450 610498 22.20 303299 100.00 Source: BSE & NSE
85 3.3.9. Clearing, Processing and Settlement System
The setting of the Clearing Houses / Clearing Corporations (CCs) has been a critical institutional arrangement to improve the market microstructure of the Indian stock market. NSE has a dedicated subsidiary namely, National Securities Clearing Corporation Limited (NSCCL) which performs the role of a central counterparty. The CCs provide full innovation with multilateral netting. Trade and Settlement Guarantee Funds have been set up to guarantee settlement in case of default by brokers. There is also a system of security lending and borrowing to obviate settlement risk .As CCs provide guaranteed settlement, there is no counterparty risk in India. Moreover, India is one of the few countries of the world to implement full- fledged Straight Through Processing (STP). The STP has been made mandatory for all institutional trades.28
Another notable achievement has been the short ending of the settlement cycle and adoption of the rolling settlement. The settlement cycle was as high as 14 days for specified scrips and 30days for others. The settlement risk was very high as many things can happen between the transaction and the settlement. Initially, the settlement cycle was reduced to a week. There after the settlement vehicle was further reduced to T+3 from April 2002 and to T+2 from April 2003. Efforts are being made to reduce the settlement cycle further to T+1 basis. India’s settlement cycle is one of the best in the world.29
3.3.10. Risk Management System
SEBI has put in place a comprehensive risk management system. The major features of the dynamic risk management system include, interalia, capital adequacy norms, trading and exposure limits, margin requirement based or mark to market and Var based margins, market-wide circuit filters, on-line position monitoring and automatic disablement of broker’s terminals.30 Indian capital market remained insulated against the South-East Asian meltdown in the late 90s. The May 17, 2004, crash of the stock market in India was short-lived due to comprehensive risk management system. The T+2 trading cycle, settlement guarantee funds, guaranteed settlement by CCs together with risk management system have significantly reduced the risk perception of the Indian stock market.
86 3.3.11. Margin Trading Facility
SEBI has allowed the member brokers to provide margin trading facility to their clients in the cash segment since April 1, 2004. Securities with mean impact cost of less than or equal to one and traded at least 80 per cent of the days during the previous 18 months would be eligible for margin trading. Only corporate brokers with net-worth of at least Rs. 3 crore would be eligible to offer this facility after obtaining prior permission from the exchanges.31
3.3.12. Regulatory Framework for Investor Protection
Investors are the major stakeholders in the securities market. It is mandatory for SEBI to protect the interests of the investors. As a matter of fact, protection of investors’ interest is pursued by the securities market regulators throughout the world. Although the objective is more or less the same for most of the regulators, the means to achieve it varies from one jurisdiction to another. In India, one of the major achievements has been to shift from merit-based regime to disclosure-based regime. SEBI issued Disclosure and Investor Protection (DIP) Guidelines in 2000 and amended the same from time to time keeping in view the investors’ interest. The disclosure norms in India are considered as one of the best in the world.32 Listed companies have to comply with the disclosure norms on an initial as well as on a continuous basis. The major objectives of the disclosure norms have been to ensure transparency and provide adequate protection to the investors.
Pricing of the public issues has been deregulated since the early 1990s. In a deregulated regime, disclosures play a crucial role for the investors to take informed decisions about their investment. Nevertheless, many companies, which flooded the primary market in the early 1990s, have vanished. Hence, the disclosure norms have been tightened from time to time.
Disclosure ought to be done on the stock exchange in addition to filing of regular returns to stock exchange where it is listed, as well as to the Registrar of Companies. Any price sensitive information about the company disclosed elsewhere attracts penal action.
87 Moreover, unfair trade practices, including insider trading, is prohibited in India in order to provide a level playing field to all investors. If any person indulges in fraudulent and unfair practices, he shall be liable to a maximum penalty of Rs. 25 crore or three times the amount of profits made out of such practices, whichever is higher. 33
There is a system of proportional allotment of public issues in India. In case of fixed price public issues, 50 per cent shares are being allotted to the retail investors. In case of book-built issues, the share of allotment for the retail investors has been raised from 25 per cent to 35 per cent. Keeping in view the possible misuse, the discretionary allotment to the Qualified Institutional Buyers (QIBs) has been withdrawn. In a move towards providing a level playing field, QIBs have been asked to deposit 10 per cent of the bid amount.34
SEBI has given in-principle approval for the introduction of IPO grading at the option of the issuer.35 IPO grading would be done by credit rating agencies registered with SEBI. The grading is intended to be an independent and unbiased opinion of the concerned agency. It would be a one time exercise and would focus on assisting the investor, particularly the retail investors, for taking informed investment decision, SEBI will not certify the assessment made by the rating agency. An issuer, who has opted for IPO grading, has to disclose all gradings in the offer document. Cost of IPO grading can be met by stock exchanges or out of the corpus maintained for Investor Education and Protection Funds.
It has been recognised the world over that investors’ protection can be strengthened by adhering to high corporate governance standards. Corporate governance standards prescribed in India are based on international best practices.36Following recommendations of the expert committees, SEBI prescribed several governance standards to be achieved by the companies by December 31, 2005, under the revised Clause 49 of the Listing Agreement with the stock exchanges. Violation of this would now attract penalty under the Listing Agreement. Corporate governance needs to be seen not as compliance, but as a way of life. In this context, the quality of compliance assumes significance. High corporate governance standards are not only desirable within the economy, but also helpful for companies accessing the international capital market. SEBI
88 gives utmost importance to the corporate governance including mandatory induction of independent directors.
The governance standards of the stock exchanges are also being improved through the process called Corporatisation and Demutualisation (C & D) of stock exchanges.37 The stock exchanges world over have been generally formed as mutual organisations. The ownership, trading rights and management are often vested with the same set of persons. This leads to conflicting interest between ownership and management. In order to segregate the management function from the ownership and trading rights, there is a need for demutualisation of stock exchanges. Moreover, stock exchanges should function as body corporate similar to any other ‘for-profit’ corporate entity. In India, NSE has been a corporate entity while NSE and OTCEI have been demutualised from their inception. Corporatisation and Demutualisation of stock exchanges is a priority item in the SEBI agenda. The oldest stock exchange of the country, namely, the Bombay Stock Exchange became a limited company on August 19, 2005. The Corporatisation and Demutualisation process has been notified for most of the remaining Regional Stock Exchanges (RSEs). The future of the RSEs post- demutualisation is being worked out so that the viable among them can actively participate in the mainstream market, besides catering to the regional requirements. A professionally managed stock exchange with at least 50 per cent non-broking share- holders is expected to play an important role for investor protection.
Security Regulations in Force38
The various security regulations in force are:-
1. SEBI (Stock Broker and Sub Broker) Regulations, 1992. 2. SEBI (Prohibition of Insider Trading) Regulation, 1992. 3. SEBI (Merchant Bankers) Regulations, 1992. 4. SEBI (Portfolio Managers) Regulations, 1993.
5. SEBI (Registrars to an Issue and Share Transfer Agents) Regulations, 1993. 6. SEBI (Underwriters) Regulations, 1993. 7. SEBI (Debenture Trustees) Regulations, 1993.
89 8. SEBI (Bankers to an Issue) Regulations, 1994. 9. SEBI (Foreign Institutional Investors) Regulations, 1995. 10. SEBI (Custodian of Securities) Regulations, 1996. 11. SEBI (Depositories and Participants) Regulations, 1996. 12. SEBI (Venture Capital Funds) Regulations, 1996.
13. SEBI (Mutual Funds) Regulations, 1996.
14. SEBI (Substantial Acquisition of Shares and Takeovers) Regulations, 1997.
15. SEBI (Buy- Back of Securities) Regulations, 1998.
16. SEBI (Credit Rating Agencies) Regulations, 1999.
17. SEBI (Collective Investment Schemes) Regulations, 1999.
18. SEBI (Foreign Venture Capital Investors) Regulations, 2000.
19. SEBI (Procedure for Board Meeting) Regulations, 2001.
20. SEBI (Issues of Sweat Equity) Regulations, 2002.
21. SEBI (Procedure for Holding Enquiry by Enquiry Officer and Imposing Penalty) Regulations, 2002.
22. SEBI (Prohibition of Fraudulent and Unfair Trade Practices relating to Securities Markets) Regulations, 2003.
23. SEBI (Central Listing Authority) Regulations, 2003.
24. SEBI (Ombudsman) Regulations, 2003.
25. SEBI (Central Database of Market Participants) Regulations, 2003.
26. SEBI (Criteria for Fit and Proper Person) Regulations, 2004.
27. SEBI (Self – Regulatory Organisations) Regulations, 2004.
28. SEBI (Regulatory Fee on stock exchanges) Regulations, 2006.
29. SEBI (Certification of Associated persons in the securities market) Regulations, 2007.
90 30. SEBI (Issue and listing of debt securities) Regulations, 2008.
31. SEBI (Intermediaries) Regulations, 2008.
32. SEBI (Delisting of Equity Shares) Regulations, 2009.
33. SEBI (Issue of Capital and Disclosure Requirements), 2010.
Security Guidelines in Force
The various security guidelines in force are:
1. SEBI (Employee Stock Option Scheme and Employee Stock Purchase Scheme) Guidelines, 1999.
2. Guidelines for Opening of Trading Terminals Abroad (Issued in 1999).
3. SEBI (Disclosure & Investor Protection) Guidelines, 2000.
4. SEBI (Delisting of Securities) Guidelines, 2003.
5. SEBI (STP Centralized Hub and STP Service Providers) Guidelines, 2004.
6. Comprehensive Guidelines for Investor Protection Fund / Customer protection Fund at Stock Exchanges (Issued in 2004).
Security Schemes in Force
The various security schemes in force are:
1. Securities Lending Scheme, 1997 2. SEBI (Informal Guidance) Scheme, 2003)
3.3.13. Grievances Redressal Mechanism
There is a comprehensive investor grievances redressal mechanism at its head office as well as at the regional offices of SEBI. The Office of Investor Assistance and Education (OIAE) is the single window interface through which SEBI interacts with investors. SEBI takes up investor complaints with companies and registered intermediaries on a regular basis. In order to file complaints, there is a standardised format which is available at all SEBI offices and on the SEBI website for the
91 convenience of investors. SEBI has a simple and efficient internet based response system for investor complaints. A system generated acknowledgement letter is issued to the investors as soon as a complaint is received electronically. Investors have the option of filing the complaints online or submitting the same on plain paper. Investors who visit the SEBI offices or access the investor helpline are guided regarding the appropriate authority to lodge their complaints which are outside the jurisdiction of SEBI. An account of receipt and redressal of investor grievances by SEBI is highlighted in Table-10 below:-
Table – 3.10
Receipt and Redressal of Investor Grievances39
Year Grievances Received Grievances Redressed Cumulative During the Cumulative During the Cumulative Redressal period period Rate (%) 1991-92 18794 18794 4061 4061 21.6 1992-93 110317 129111 22946 27007 20.9 1993-94 584662 713773 339517 366524 51.4 1994-95 516080 1229853 351842 718366 58.4 1995-96 376478 1606331 315652 1034018 64.4 1996-97 217394 1823725 431865 1465883 80.4 1997-98 511507 2335232 676555 2142438 91.7 1998-99 99132 2434364 127227 2269665 93.2 1999-00 98605 2532969 146553 2416218 95.4 2000-01 96913 2629882 85583 2501801 95.1 2001-02 81600 2711482 70328 2572129 94.9 2002.03 37434 2748916 38972 2611101 95.0 2003-04 36744 2785660 21531 2632632 94.5 2004-05 54435 2840095 53361 2685993 94.6 2005-06 40485 2880580 37067 2723060 94.5 2006-07 26473 2907053 17899 2740959 94.3 2007-08 54933 2961980 31676 2772577 93.6 2008-09 57580 3019560 75989 2848566 94.3 Source: SEBI
92 During the period 1991-92 to 2008-09, the SEBI received 30, 19,560 grievances from the investors of which a total of 28, 48,566 grievances were redressed by the respective entities, indicating a redressal rate of 94.3 per cent.
In case the companies fail to redress complaints in spite of repeated reminders by SEBI, regulatory actions are initiated under section 11B (debarring companies form accessing the capital markets) and 15C (imposing of monetary penalty) of the SEBI Act, 1992. Up to March 31, 2009, 33 companies have been referred for adjudication proceedings under Section 15C of the SEBI Act, 1992. Prohibitory orders have also been passed under Section 11B of the SEBI Act, 1992 against errant companies which did not redress the investor grievances. Such orders have been passed against 12 companies and 62 directors till March 31, 2009.40 Moreover, SEBI also issues the status of investor grievances every fortnight for public information and uploads the same on SEBI Website.
3.3.14. Investor Education41
Investor education plays a crucial role for the securities market awareness, particularly for the retail investors. A major initiative in this regard during the recent past has been launching of a comprehensive Securities Market Awareness Campaign (SMAC) on January 17, 2003. The campaign includes workshops, audio-visual clippings, and distribution of educative materials in English, Hindi and also in regional languages. There is a dedicated investor website which archives the booklets / pamphlets / FAQs etc. SEBI, in co-ordination with other agencies, conducted about 2188 workshops throughout the country till date under the SMAC. (Tamilnadu-134)
SEBI recognises investor associations and extends financial support for conducting investor education programmes. SEBI has recognised 24 investor associations up to November 2010.
There has been a long-standing request from the financial journalists of the print and electronic media to have an interface with SEBI on issues relating to the capital market. As financial journalists play a critical role for investors’ education, SEBI decided
93 to conduct a one-day workshop on capital market for the financial journalists at different centres. The objective of the programme is to provide adequate inputs to the financial journalists for balanced reporting of financial events and shoulder the responsibility of accurate dissemination of information on the developments that are taking place on a day-to-day basis in the securities market. This programme was organised at New Delhi and Chennai during 2005-06. At both the places, the programme was inaugurated by Shri M. Damodaran, Chairman, SEBI. A few outside experts, including professors and practitioners were invited for an interface with the participants in addition to presentations given by the senior officers of SEBI. As the response was encouraging, SEBI is contemplating to conduct the same programme in other centres during 2006-07.
3.4. RECENT INITIATIVES42
SEBI introduced the Application Supported by Blocked Amount (ASBA) as a new mode of payment in public issue. In this kind of mechanism the application money remains blocked in the bank account of the applicant till the allotment is finalized.
Direct Market Access facility was introduced for institutional investors in April 2008 by SEBI.
In an endeavour to strengthen the risk management framework, margining for institutional trades was made mandatory by SEBI.
Reduction in time for Right Issues was reduced from 16 weeks to 6 weeks.
A change in Securities Lending and Borrowing (SLB) Scheme was introduced in April 2008.
Currency Futures were launched on USD-INR pair in India in August 2008 by NSE, and October 2008 by BSE and MCX.
Removal of Quantitative restrictions imposed on the Overseas Derivatives Instruments (ODIs) for FII.
94 Exit Option to Regional Stock Exchanges (RSEs).
Listing of close-ended schemes launched on or after December 12, 2008 along with daily computation of NAV was made compulsory.
SEBI permitted NSE to launch Interest Rate Futures on August 31, 2009.
3.5. INDIAN CAPITAL MARKET – FUTURE ROAD MAP43
SEBI may go in for fresh investor survey at the earliest to understand the investment behaviour of the households during the more recent period.
Hon’ble Union Finance Minister has proposed to set up an investor protection fund under the aegis of SEBI which would be funded by fines and penalties recovered by SEBI.
SEBI would continue to nurture the Mutual Fund Industry and thereby attract more and more household participation in the capital market.
Gold Exchange Traded Fund (GETF) has been introduced in India and in addition, SEBI is also working for the introduction of the Real Estate Mutual Fund, which is likely to mitigate the housing requirement of many households.
SEBI has been authorized to set up a National Institute of Securities Markets (NISM) for teaching and training intermediaries in the securities market and promoting research.
3.6. SUMMARY
Thus the Indian Capital Market is in transition. There has been a revolutionary change over a period of time. In fact, on almost all the operational and systematic risk management parameters, settlement system, disclosures, accounting standards, the Indian Capital Market is at par with the global standards. The goal of SEBI is to make the Indian Capital Market truly world class, competitive, transparent and efficient. A
95 perception is steadily growing about the Indian Capital Market, as a dynamic market, among the international community. Let us dream to make our Indian Capital Market a benchmark for the rest of the world.
REFERENCES
1. Levine, Ross and S. Zervos, “Stock Market Development and Economic Growth”, The World Bank Economic Review, Vol.1012, PP.323-339, 2006.
2. Agarwal R.N, “Financial Liberalization in India: Banking system and stock Markets”, Delhi: D.K. Publishers, 2007.
3. Bajpai G.N., “Developments of capital Markets in India”, cited at London School of Economics on 2nd October 2009, www.sebi.gov.in
4. Fama E, “Efficient Capital Markets: II”, Journal of Finance, Vol. XLVI(5), PP.1575-1617
5. Shah. A and Thomas., S, “Developing the Indian Capital Markets” in J.A. Hanson and S.Kasthuria, eds, “A Financial sector for the Twenty first century, India,”: Oxford University Press, Chapter 71, PP.225 -265
6. Ibid., P.270
7. Shirin Rathore, Muneesh Kumar, Amitabh Gupta, “Indian Capital Market – An Empirical Study”, New Delhi: Anmol publications Pvt. Ltd., Cover page.
8. NSE-Fact book: 2009, www.nseindia.com,p.1.
9. Damodharan.M, “Capital Market in India: A country Profile”, SEBI bulletin, Vol.3, No.11, Nov2009,P 5.
10. SEBI, Handbook of Statistics on the Indian Securities Market: 2009, www.sebi.gov.in, PP. 247-250.
96 11. Indian Securities Market – A Review: 2005, National Stock Exchange publication, Vol.VIII, P.5.
12. SEBI, Handbook of Statistics on the Indian Securities Market: 2009, www.sebi.gov.in PP.22-23.
13. Sachdeva, “Emerging Securities Market – Challenges and Prospects”, Chartered Financial Analyst, Feb 2005, PP.53-56.
14. Ibid., pp.70-75
15. Indian Securities Market – A Review: 2011, National Stock Exchange publication, PP.15.
16. Damodharan.M, “Capital Market in India: A country Profile”, SEBI bulletin, PP.6.
17. SEBI, Handbook of Statistics on the Indian Securities Market:2009, www.sebi.gov.in PP.3
18. Ibid., PP.52
19. NSE-Fact book: 2011, www.nseindia.com,p.1, PP.85
20. SEBI, Handbook of Statistics on the Indian Securities Market: 2009, www.sebi.gov.in, PP.43.44.
21. Indian Securities Market – A Review: 2011, National Stock Exchange publication, PP.85.
22. Ibid., PP.50.
23. Ibid., PP.51.
24. Ibid., PP.3.
97 25. Damodharan.M, “Capital Market in India: A country Profile”, SEBI bulletin, Vol.3, No.11, Nov2010 PP.7.
26. Ibid., pp.10-12.
27. SEBI, Handbook of Statistics on the Indian Securities Market:2009, www.sebi.gov.in, PP.40-43.
28. Damodharan.M, “Capital Market in India: A country Profile”, SEBI bulletin, Vol.3, No.11, Nov2005
29. Ibid.,
30. Ibid., PP.8.
31. Indian Securities Market – A Review: 2005, National Stock Exchange publication, Vol.VIII, PP:112-113.
32. Chopra V.K, “Investor Protection: An Indian Perspective”, SEBI bulletin, Nov 2006,
33. Chopra V.K. “Capital Market Reforms in India: Recent Initiatives”, SEBI bulletin Nov 2011,
34. Ibid.,pp.5
35. Chopra V.K, “Investor Protection: An Indian Perspective”, SEBI bulletin, Nov 2010,
36. Ibid.,pp.6.
37. Chopra V.K. “Capital Market Reforms in India: Recent Initiatives”, SEBI bulletin Nov 2006
38. Security Regulations, Guidelines, Schemes in Force, SEBI bulletin, Vol.3, No.11, Nov 2010, PP.13
98 39. SEBI, Handbook of Statistics on the Indian Securities Market:2011, www.sebi.gov.in PP.70.
40. Chopra V.K, “Investor Protection: An Indian Perspective”, SEBI bulletin, Nov 2009,
41. Ibid., pp. 20
42. Chopra V.K. “Capital Market Reforms in India: Recent Initiatives”, SEBI bulletin Nov 2008
43. Chopra V.K, “Investor Protection: An Indian Perspective”, SEBI bulletin, Nov 2011.
99 CHAPTER - IV
INVESTMENT PREFERENCE AND DECISION
INTRODUCTION
This Chapter examines the investment pattern of the retail equity investors in general and investment preferences, risk-return perceptions and investment objectives of the retail equity investors based on the socio-economic variables and selective investment profile factors.
An investment in equity shares is one of the welcoming trends in the investment sector. These investments have been found in the primary market, secondary market, changes in project details and financial parameters. The equity share is always dominated by the primary market and secondary market and the investors select one of these to their investment processes and lucrative approach. In this chapter, perception of investors on primary and Details of present values are analysed with respect to their various investment options and procedures. The ideas of financial parameters and changes of project details contribute to the retail investment and their progress. So their elements and consequences in the present scenario are ascertained through the opinions of respondents. Several sophisticated and multivariate tools are exploited to obtain the torrent of results useful for the study. The general impact of financial investments on the equity shares will be analysed with the support of data collected by using appropriate statistical tools, of course with necessary interpretations.
As already mentioned though the study related to financial investments and their impact on the equity shares, the main concentration will be on the perception of the investors, who are the part and parcel of the equity shares. Hence, the study of demographic variables regarding the investors is necessary and let us book at them in the following lines.
100 4.2 Age of the Investors
Investment factor often goes with age. Age factor distinguishes the investor behaviour. Many investing options have carved out a place in the equity shares by concentrating on a specific age segment. The age of the investors plays a crucial role to identify the investment behaviour. It is considered as a useful demographic variable to segment the investors based on their perception of the investment pattern. The respondents have been divided into four groups, namely, less than 25, 26-40, 41-60 and above 60. Table 4.1 shows the age of frequency distribution of the sample investors.
Table - 4.1 Age Frequency of Investors
Age Frequency Percentage Below 25 29 5.7
26-40 278 54.9
41-60 169 33.3
Above 60 31 6.2
Total 507 100
Source: Primary Data
The above table clearly indicates that a maximum percentage of 54.9% of investors are in the age group of 26 to 40 followed by the investors in the age group 41 to 60 which is 33.3%. It is also found that a less percent of 6.2% of the investors are in the age group of above 60.
101 Figure – 4.1: Age of the Investors
4.3 Gender of the Investors
Gender is a useful variable for the equity shares investment because it seems to reflect the attitudes, options and prudential motives of the investors. Gender is an important factor to identify the behaviour of the investors. In general, most of the investors in the equity shares are males. Females are not much exposed to the effectiveness of retail investment and their consequences. Table - 4.2 shows the distribution of male and female investors.
Table - 4.2: Gender of the Investors
Gender Frequency Percentage Male 468 92.4 Female 39 7.6 Total 507 100
102 Source: Primary Data
From the above table, it is clear that 92.4% of the investors are males and 7.6% are females. This profoundly reveals that males are more enthusiastic than females in equity shares investment. These results are also shown in Figure – 4.2.
Figure – 4.2: Gender of the Investors
Percentage
4.4 Marital Status of the Investors
Marital status affects the investment pattern of investors. The marital sentiments force them to invest for their future prospects. This state makes the investor to think twice before investment. The martial status is considered to be one of the major determinants for investors. Due to various family commitments, the married investors are not able to concentrate more on investment in the equity shares. Table - 4.3 indicates the marital status of the investors.
103 Table - 4.3: Marital Status of the Investors
Marital Status Frequency Percentage
Married 407 80.3
Unmarried 93 18.4
Separated 07 1.2
Total 507 100
Source: Primary Data
It is found from the above table that 80.3% investors are married and 18.4% are unmarried and the remaining 1.2% is separated according to martial status. The married investors view these investments for their prudential purpose. The graphic figure – 4.3 also supports the above interpretation.
Figure – 4.3: Marital Status of the Investors
Percentage
4.5 Education of the Investors
Education completely expresses the values of investment, creates attitudinal changes among investors, more broadly, it reflects a life style with many investment options in the equity shares. Education is a powerful background for the investor’s analysis about the pros and cons of investment in equity shares. Table - 4.4 presents education wise distribution of the investors.
104
Table - 4.4: Education of the Investors
Education Frequency Percentage School 40 7.9 Diploma 54 10.7 Graduate 247 48.8 Postgraduate 104 20.6 Professional 62 12.0 Total 507 100 Source: Primary Data
It is found that most of the investors are have a good education background. 48.8% of the investors are graduates, 20.6% are post graduates and 12% are professionals. This shows that the educated investors are able to analyze the advantages and disadvantages of investment in equity shares and they also concede that they are able to get transparent information through television and magazines regarding equity shares in India.
Figure – 4.4: Education of the Investors
Education of the investors 60
50
40
30 Percentage
20
10
0
105 4.6 Occupation of the Investors
Many investment companies and stock brokers have found that occupational category can also be used to distinguish the investment pattern. Occupation of the investors paves the way and also induces the investment pattern of the investors. Table - 4.5 depicts the occupation of investors surveyed, among five groups according to their occupation.
Table - 4.5: Occupation of the Investors
Occupation Frequency Percentage
Government 70 13.8
Private 218 43.0
Self-employed 166 32.7
Agriculture 07 1.3
Retired 46 9.2
Total 507 100
Source: Primary Data
In this table, it is identified that most of the investors are working in private concerns or running their own business, that is 43% and 32.7% of investors are employed in private or in their business concerns. The Government employees are not enthusiastic more in equity shares investment and retired people and agriculturalists also show the least interest in investing their surplus in equity shares project details. The above facts have been shown in Figure – 4.5 also.
106 Figure – 4.5: Occupation of the Investors
4.7 Income of the Investors
Income has long been an important variable for distinguishing investment segments. It is known that affluent investors are much enthusiastic in investment and need better returns. The respondents are divided into four income groups according to their annual income. Income is the most important factor for all the investors to allot separate amount for the investment, which will be used for their future purpose. Table - 4.6 explicitly shows the income of the respondents.
Table - 4.6: Income of the Investors
Income Frequency Percentage Below 1 lakh 135 26.6 1-2 lakhs 198 39.1 2-3 lakhs 116 22.9 Above 3 lakhs 58 11.4 Total 507 100 Source: Primary Data
107 It is found from the table that 39.1% investors belong to the income groups of Rs. 1 - 2 lakhs and 26.6% investors have the income less then Rs. 1 lakhs, 22.9% are in the income of groups of Rs. 2 - 3 lakhs. The investors with more than Rs. 3 lakhs income do not show more interest on investments in equity shares. Figure – 4.6 also illustrates the above data.
Figure – 4.6: Income of the Investors
4.8 Nature of Family of the Investors
Nature of family is an important factor affecting the regular investment pattern. Family nature is considered as one of the burdens affecting the investment behaviour of investors. Family members of investors are classified into three groups as shown in the table - 4.7.
108 Table - 4.7: Nature of Family of the Investors
Nature of family Frequency Percentage Joint 194 38.3 Nuclear 313 61.7 Total 507 100 Source: Primary Data
From the above table, it is clear that the investors in the joint family are not much enthusiastic in investment in the equity shares and the investors of nuclear family are able to invest more amount of their income in equity shares. Figure – 4.7 also indicates the above observation.
Figure – 4.7: Nature of the Family of Investors
4.9 Number of Dependents of the Investors
The number of dependents is playing a significant role in deciding the investment amount of the investors and it is presented in table - 4.8.
109 Table - 4.8: Number of Dependents of the Investors
Number of Dependents Frequency Percentage No dependents 70 13.8 1 dependent 49 9.7 2 dependents 121 23.9 3 dependents 138 27.2 4 dependents 60 11.9 More than 4 dependents 69 13.5 Total 507 100 Source: Primary Data
When the number of dependents is more in the family, their investment behaviour pattern also changes significantly. The number of dependents and investment are inversely proportional to each other. When the number of dependents is more in the family, they do not have ample money for investment in this present economic situation. Figure – 4.8 also indicates the same inference.
Figure – 4.8: Number of Dependents of the Investors
110 4.10 House Ownership of the Investors
Own house and rented house investors behave in a different manner during their investment proceedings. Rented house exploits their income and hampers them from investment. Table - 4.9 indicates two types of investors.
Table - 4.9: House Ownership of the Investors
House Ownership Frequency Percentage
Own 434 85.7
Rented 73 14.3
Total 507 100
Source: Primary Data
It is inferred from the table that most of the investors in equity shares have their own house. If they have their own houses, they divert their income in the form of investment in equity shares. It is also found that 85.7% of the investors have their own houses and 14.3% are in rented house. Figure – 4.9 also supports the above facts.
Figure – 4.9: House Ownership of the Investors
111 4.11 Type of Investors
There are two types’ of investors in share market of India. The hereditary investors develop the investment habit as their character and some investors are induced by the liberalization and transparency of share market investment. The following Frequency Distribution Table 4.10 reveals the response of investors about their type towards share market investment:
Table -4.10: Type of investors
Valid Cumulative Type Frequency Percentage Percentage Percentage
New 428 84.4 84.4 84.4 generation Options Hereditary 79 15.6 15.6 100.0
Total 507 100.0 100.0
From the above table it is found that 84.4% of the respondents in Chennai are new generation investors who know about the risk and return in equities, whereas, 15.6% of them are hereditary investors. This implies that maximum number of investors is new generation and induced by policies of liberalization and transparency in Indian capital market.
4.12 Category of investors
The investors differ in their category based on their long term investment pattern and daily trading approach in Indian share market. The following frequency distribution Table 4.11 presents two different categories of investors
112 Table – 4.11: Category of Investors
Category Frequency Valid Percent Cumulative Percent
Both 365 72 72
Daily traders 64 12.6 84.6
Long term 78 15.4 100
Total 507 100
From the above table it is found that 72% of the respondents establish themselves as both long term investors and daily traders and 12.6%of them operate equity investment daily. It is also found that 15.4% of the investors have the habit of long term investment in equities.
From the above analysis it is inferred that maximum number of respondents are interested towards long term investment and daily trading of shares.
4.13 Number of Years of Dealing with Securities Markets
Investment Behaviour of the investor can be easily analyzed through the number of years of dealing with securities markets. In fact, the experience makes a man perfect by dealing in the securities markets so that the investor may come to know the changes in securities markets. It is believed that wisdom comes only form ones own experience. In this study four classification have been considered namely below 5 years, 6 – 10 years, 11 - 15 years and above 15 years. The following frequency distribution Table 4.12 expresses the distribution of the samples according to the number of years dealing with securities markets.
113 Table-4.12: Frequency Distribution of Number of Years of Dealing with Securities Markets
Cumulative years Frequency Valid Percent Percent
Valid Below 5 years 277 54.7 54.7
6 – 10 years 130 25.6 80.2
11 – 15 years 89 17.6 97.8
Above 15 years 11 2.2 100.0
Total 507 100.0
Source: Primary data
From the above table it is revealed that a maximum of 54.7% of investors are dealing less then 5 years of experience in the securities market followed by 25.6% of investors are having the experience in the securities market for 6 to 10 years , 17.6% of the investors have been dealing for the period of more than 11 years but less than 15 years of experience and only 2.2% of the investors are dealing in the securities market with the experience of more than 15 years of experience with securities market. So the percentage analysis revealed that most of the investors are having the experience in the securities market just below 5 years which shows that young investors and educated person are now entering into the securities markets.
4.14 Number of companies invested.
People have several means to get to know about the available investment schemes in different companies in different sectors and these sources are motivating the potential investors to make investments in particular companies.
The following Frequency Distribution Table 4.13 reveals the response of investors pertaining to number of companies invested:
114
Table-4.13: Number of companies invested
Number of companies Frequency Percent Valid Percent Cumulative Percent
Response Less than 10 376 74.1 74.1 74.1
More than 10 131 25.9 25.9 100.0
Total 507 100.0 100.0
From the above table it is found that 74.1% of the respondents in Chennai invested in less than 10 companies and remaining 25.9% of them are attracted towards more than 10 companies share market investment. This denotes that maximum number of customers possess the updated knowledge about less than 10 companies for their investment.
4.15 Size of Investment
The size of investment has an important bearing on the share market investment of the individuals. The investment habits of the individuals will be highly influenced by the size of investment in their hands. The following frequency distribution Table 4.14 expresses the distribution of the samples according Size of investment dealing with securities markets.
Table-4.14 Distribution of Samples on the Basis of size of investment
Size of Investment Frequency Valid Percent Cumulative Percent
Less than Rs. 1,00,000 54 10.7 10.7
Rs. 1,00,000- Rs. 2,00,000 180 35.4 46.1
115 Rs. 2,00,000-Rs. 3,00,000 119 23.5 69.6
Rs. 3,00,000 and above 154 30.4 100.0
Total 507 100.0
From the above table it is found that 10.7 % of the respondents have an investment of less than Rs. 1, 00,000. The investment level of 35.4 % of the respondents is between Rs. 1, 00,000 and Rs. 2, 00,000. 23.5 % of them have an investment size which ranges from Rs.2, 00,000 to Rs. 3, 00,000. The annual size of 30.4 % of the sample ranges above Rs.3, 00,000. From the above analysis it is clear that large number of respondents have an annual income ranging between Rs. 1, 00,000 and Rs.2, 00,000.
4.16 Source of Investment.
The investors enthusiastically invest their own funds or borrowed funds to derive maximum return with in the short span of time.
The following Frequency Distribution Table 4.15 reveals the response of investors about their source of funds to invest in equities:
Table-4.15 Source of Investment
Valid Cumulative Internet Banking Frequency Percent Percent Percent
Response Own funds 489 90.6 90.6 90.6
Borrowed 51 9.4 9.4 100.0 funds
Total 540 100.0 100.0
116 From the above table it is found that 90.6% of the respondents in Chennai are able to invest own funds in equities whereas, 9.4% of them borrow funds to invest in equities. This indicates that maximum number of investors invest own funds to obtain better returns.
4.17 Percentage of Savings Invested In Securities Markets
The Behaviour of investors can be easily analyzed through the percentage of savings invested in the securities markets. In fact the surplus income induces the investors to participate in the securities market in order to earn high returns. Propensity to invest can be defined as the percentage of current income invested; it’s known that investments are made out of surplus income. If the proportion of investment to income is higher, then the propensity is said to be higher. In this study four classifications have been considered namely below 25%, 26 – 50%, 51 – 75%, and 76 – 100 % of savings invested in to the securities markets. The following frequency distribution Table 4.16 expresses the distribution of the sample according to the percentage of savings invested in the securities markets.
Table-4.16 Frequency Distribution of Percentage of Savings Invested In Securities Markets
Valid Cumulative Percentage of savings Frequency Percent Percent
Valid Below 25% 528 64.0 64.0
26% - 50% 188 22.8 86.8
51% – 75% 104 12.6 99.4
76% - 100% 5 0.6 100.0
Total 507 100.0
Source: Primary data
117 From the above table it is ascertained that a maximum of 64% of sample size are investing their fund out of their savings below 25%, followed by 22.8% of sample size are participating in the securities market out of their savings between 26 – 50%, on sample size of 12.6% of the investors are investing their fund out of their saving between 51 – 75% and only 0.6% of the sample size are investing their saving between 76 – 100%. So the percentage analysis revealed that most of the investor are invest their money out of their saving below 25% of the surplus money that they had.
4.18 Sources of Information
A successful investor in securities market must keep himself abreast of the latest information, all the required information especially the one relating to specific companies / industries is not available at one place, so investors are able to get transparent information about their dealings in securities market through various avenues like News Paper, Journals and Magazines, Television Channels, Stock Brokers, Investment Consultancy, Web sites and friends and Relatives. The following table 4.17 presents the combined frequency distribution of various avenues of information.
Table 4.17 : Sources of Information
Sources Of Information No. Of Responded Percentage
News Papers 400 77.6
Television Channels 336 66.4
Stock Brokers 286 56.5
Journals & Magazines 256 50.8
Friends & Relatives 203 40
Investment Consultant 200 39.4
Web Sites 179 35.3
Source: Primary data
118 From the above combined frequency distribution table it is ascertained that a maximum of 77.6% of investors get the information about the securities market through news papers followed by 66.4% of investors get the information through television media, 56.5% of investors receive the information through the stock brokers, 50.8% , 40%, 39.4% and 35.3% of the investors obtain the information about the securities through journals and magazines, friends and relatives, investment consultant and web sites respectively. So the combined frequency distribution analysis revealed that a major percentage of the investors are getting the information through news papers television and stock brokers.
4.19 Criteria for Investments
Table 4.18: Criteria for Investments
Cumulative Criteria Frequency Valid Percent Percent
Sector based 253 49.9 50.2
Financial performance 252 49.6 99.5
other 2 0.5 100
Total 507 100.0
Source: Primary data
From the above table 4.18 it is found that a maximum of 49.9 percent of investors investing their investment after a careful analysis of company based on their sector in which it belongs. Some 49.6 percent of investors are investing their money after analyzing the financial performance of the companies and only 0.5 percent of investors are considering some other factors like present market condition and new production strategies. So it is highlighted from the above table that most of the investors are channalised their investment after a careful analysis of the sector considered in which the company belonging.
119 4.20 Member of investors’ forum
Investors’ awareness about criteria, forum, malpractices of intermediaries, and mode of trading financial sector reforms are highlighted in the following discussion.
Table 4.19: Member of investors’ forum
Frequency Valid Percent Cumulative Percent
Yes 435 85.8 85.8
No 72 14.2 100.0
Total 507 100.0
Source: Primary data
From the above table 4.19 it is ascertained that a maximum of 85.8 percent of investor are possessing experience in dealing their investment forums followed by 14.2 percent of investor doesn’t have any experience with the forum of investors So the percentage analysis table reveals that most of the investors in securities market are having much experience with forum of investors in dealing their investment affairs.
4.21 Awareness of Malpractice of Intermediaries Table 4.20: Awareness of Malpractice of Intermediaries
Frequency Valid Percent Cumulative Percent Yes 416 82.1 82.1
No 91 17.9 100.0
Total 507 100.0
Source: Primary data
120 From the above frequency table 4.20 it is ascertained that a maximum of 82.1 percent of investors in securities market are aware of the malpractice of intermediaries followed by 17.9 percent of investors are not known the malpractices done by the intermediaries. So the percentage analysis reveals that most of the investors in Indian securities market are having the knowledge about the malpractices done by the intermediaries like share brokers etc.
4.22 Mode of Trading
Table 4.21: Mode of trading
Frequency Valid Percent Cumulative Percent
Online 416 82.1 82.1
Off line 91 17.9 100.0
Total 507 100.0
Source: Primary data
From the above frequency table 4.21 it is ascertained that a maximum of 82.1 percent of investors in securities market are aware of the online trading and they buy and sell their equities followed by 17.9 percent of investors deal with offline trading. So the percentage analysis reveals that most of the investors in Indian securities market are having the knowledge about the on line trading conveniently.
4.23 Awareness of Financial Sector Reforms in India
Table 4.22: Awareness of Financial Sector Reforms in India
121 Frequency Valid Percent Cumulative Percent
Yes 504 99.5 99.5
No 3 0.5 100.0
Total 507 100.0
Source: Primary data
From the above table 4.22 it is ascertained that a maximum of 99.5 percent of investors in the Indian securities market are aware of the reforms made in the Indian financial system, followed by only 0.5 percent of investors are don’t have the awareness of financial sector reforms in India. So it is inferred by the percentage analysis that majority of the investors in Indian securities market are aware of the financial sector reforms made by the Government of India.
4.24 The Impact of Indices on investors
People have several means to get to know about the available investment schemes and these sources are motivating the potential investors to make investments in a particular investment avenue. Investment decision making is the process of identifying various alternatives, evaluating each alternative and choosing the best alternative based on the priorities, expectations and risk tolerance of the investor. Investors could make decision on their own or can rely on the advice of another person. It is very important that the investors do their home work whether they take independent decisions or rely on others. In this study five classifications of indices have been considered namely sensex, CNX nifty, CNX Nifty Junior, CNX midcap and CNX Midcap 200. The following frequency distribution Table 4.23 expresses the distribution of the samples according to the source of index about investment avenues.
122 Table 4.23: Frequency Distribution Of index
Valid Cumulative Influencers Frequency Percent Percent
Valid Sensex 217 42.9 42.9
CNX Nifty 47 9.2 52.1
CNX Nifty Junior 161 31.9 84.0
CNX Mid cap 62 12.1 96.1
CNX Midcap 200 20 3.9 100.0
Total 507 100.0
Source: Primary data
In can be seen that out of the sample size 42.9% of the investment decisions are taken based on sensex index followed by 31.9% of the investors’ decisions are influenced by the index of Nifty, 12.1% of the investors’ decisions are influenced by the index of Nifty junior, 9.2% of the sample size of investors’ decisions are influenced by the index of CNX Midcap and only 3.9% of the investors’ decisions are influenced by the CNX madcap 200. So the percentage analysis revealed that most of the investor’s decisions are influenced and taken by the observations of sensex index.
4.25 Association between Sources of Information and Preference of Industry
The non-parametric chi-square test is applied to find the association between source of the information useful for the investors and their ranking preference of their investment industry. Different sources of information stated in the questionnaire are considered for the analysis. a) News papers and Investment in Different Industries
The association between information through newspapers and different industry is displayed in table – 4.24.
123 Table – 4.24: Chi-square Value for Sources of Information with regard to Newspapers
Industry Chi-square value Sig Result
Banking 27.538 0.001 Association
Steel 27.654 0.001 Association
Cement 27.087 0.000 Association
IT 10.517 0.161 No association
Pharma 18.236 0.011 Association
Manufacturing 28.220 0.000 Association
Textile 16.320 0.022 Association
Automobile 29.118 0.000 Association
Source: Primary Data
From the above table, it is found that the information through Newspaper plays a crucial role in identifying all the industries except IT industry. b) Journals, Magazines and Investment in Different Industries
The association between information through Journals, magazines and different industries is presented in table – 4.25.
124 Table – 4.25: Chi-square Value for Sources of Information with regard to Journals and Magazines
Industry Chi-square value Sig Result
Banking 20.528 0.009 Association
Steel 10.748 0.150 No Association
Cement 12.742 0.079 No Association
IT 11.709 0.111 No association
Pharma 8.385 0.300 No Association
Manufacturing 24.560 0.001 Association
Textile 35.520 0.000 Association
Automobile 24.562 0.001 Association
Source: Primary Data
From the above table it is found that the information through Journals and magazines is useful for investors to invest in banking, manufacturing, textile and automobile industries. c) TV channels and Investment in Different Industries
The association between information through TV channels and different industry is presented in table – 4.26.
Table – 4.26: Chi-square Value for Sources of Information with regard to TV Industry Chi-square value Sig Result
Banking 31.851 0.001 Association
Steel 22.836 0.002 Association
Cement 20.851 0.004 Association
125 IT 10.659 0.154 No association
Pharma 8.391 0.299 No Association
Manufacturing 7.386 0.390 No Association
Textile 6.760 0.454 No Association
Automobile 12.086 0.098 No Association
Source: Primary Data
From the above table it is inferred that banking, steel and cement industry are concentrated by the investors with the help of information through TV channels. d) Stock Brokers and Investment in Different Industries
The association between information through stockbrokers and different industry is presented in the table – 4.27.
Table – 4.27: Chi-square Value for Sources of Information with regard to Stock Brokers
Industry Chi-square value Sig Result
Banking 35.153 0.000 Association
Steel 16.788 0.019 Association
Cement 31.592 0.000 Association
IT 36.211 0.000 Association
Pharma 21.012 0.004 Association
Manufacturing 46.884 0.000 Association
Textile 34.238 0.000 Association
Automobile 46.300 0.000 Association
Source: Primary Data
126 As far as the capital market investment and selection of industry is concerned, the stockbrokers give more information to the investors in selecting the industry. e) Investment Consultants and Investment in Different Industries
The association between information through investment consultants and different industries is presented in the table – 4.28.
Table – 4.28: Chi-square Value for Sources of Information with regard to Investment Consultant
Industry Chi-square value Sig Result
Banking 44.737 0.000 Association
Steel 27.701 0.003 Association
Cement 12.014 0.100 No Association
IT 34.831 0.000 Association
Pharma 12.318 0.091 No Association
Manufacturing 35.602 0.000 Association
Textile 14.770 0.039 Association
Automobile 38.860 0.000 Association
Source: Primary Data
From the above table, it is ascertained that the investment consultants significantly guide the investors to invest in banking, steel, IT, manufacturing, textile and automobile industries respectively. f) On line Websites and Investment in Different Industries
The association between information through on line websites and different industry is presented in table – 4.29.
127 Table – 4.29: Chi-square Value for Sources of Information with regard to On Line Website
Industry Chi-square value Sig Result
Banking 22.625 0.004 Association
Steel 4.651 0.702 No Association
Cement 21.946 0.002 Association
IT 28.077 0.000 Association
Pharma 22.309 0.002 Association
Manufacturing 20.764 0.004 Association
Textile 4.928 0.669 No Association
Automobile 23.926 0.001 Association
Source: Primary Data From the above table it is found that web sites give profuse source of information for investors about the performance of banking, cement, IT, pharma, manufacturing, and automobile industries. g) Friends, Relatives and Investment in Different Industries
The association between information through friends, relatives and different industries is presented in the table – 4.30.
Table – 4.30: Chi-square Value for Sources of Information with regard to Friends and Relatives
Industry Chi-square value Sig Result
Banking 26.457 0.001 Association
Steel 7.682 0.361 No Association
Cement 32.744 0.000 Association
128 IT 30.304 0.000 Association
Pharma 15.128 0.034 Association
Manufacturing 24.861 0.001 Association
Textile 9.537 0.216 No Association
Automobile 31.877 0.000 Association
Source: Primary Data
From the above table it is found that friends and relatives are give more useful information about the performance of banking, cement, IT, pharma, manufacturing, and automobile industries.
It is concluded that the different sources of information play the vital role in the investor’s behaviour they promote the knowledge of every investor to think prudently about the consequences of their investment.
4.26 Preference of Investments and their Ranks with regard to equity investment
The ranking method helps the researcher to identify which investment avenues are most preferred. Table - 4.31 presents the mean, standard deviation and their respective rankings based on the mean.
Table - 4.31: Mean and Standard Deviation for Preference of Investments and their Ranks
Variable Mean S.D. Rank Shares 1.86 1.42 1 Fixed Deposit 3.72 1.81 2 Real Estates 3.93 1.88 3 Mutual Funds 4.33 1.73 4 Government Bonds 4.40 1.79 5
129 Gold 4.81 2.02 6 Debentures 4.99 1.62 7 Source: Primary Data
It is inferred from the above table that the mean is found according to the ranks assigned to the variables by the investors. The most preferred investments are well established and the investors strongly agree that the investment in capital market alone gives more returns with minimum market risk. So they prefer share market as rank 1 followed by fixed deposit, real estate, mutual funds, government bonds, gold and debentures in order. The first preference is due to appreciable returns besides the maximum risk.
4.27 Ranking Analysis for Preference of Investments in Industry
The ranking analysis is executed for the different preference of investment in industry such as banking industry, steel industry, cement industry, IT industry, Pharma industry, manufacturing industries, textile industry and automobile industry and the following preferences are arranged in order in table - 4.32.
Table - 4.32: Mean and Standard Deviation for Ranking of Industries
Variable Mean S.D. Rank Banking Industry 3.17 2.20 1 IT Industry 3.45 2.43 2 Cement Industry 4.51 1.20 3 Pharma Industry 4.81 1.76 4 Automobile Industry 4.87 2.37 5 Manufacturing Industry 4.88 2.17 6 Textile Industry 6.02 2.07 7 Source: Primary Data
From the above table, it is found that according to the rank of preference, the investors invest their money in the above mentioned industries. They invest their money safely in banks in the form of deposits and give second preference to IT industry
130 followed by cement and pharma industry. This also shows that the investors concentrate more on the safety of their investments in banks.
4.28 Reasons for Investments and their Ranks in equity Market.
Investments return, tax benefits and liquidity are preferred by investors for different reasons. The result of the sample means, standard deviations and their ranks are established below in table - 4.33.
Table - 4.33: Mean and Standard Deviation of Reasons for Investments and their Ranks
Variable Mean S.D. Rank Return 1.27 .550 1 Liquidity 2.18 .678 2 Tax benefits 2.54 .616 3 Source: Primary Data
From the above table, it is concluded that the investors give first preference to better returns followed by liquidity and tax benefits. So, it can be concluded that all type of investors demand more returns with no risk. So they prefer share market fabricated with minimal risk.
4.29 Ranking Analysis for Investment Style in equity Market
Different style of investments like conservative, calculative, intuitive, impulsive, risk taking are verified to identify the most popular investment style of the investors. Table - 4.34 presents the mean and standard deviation and rank of preference of investment style.
131 Table - 4.34: Mean and Standard Deviation of Preference of Investment Style
Variable Mean S.D. Rank Calculative 1.94 1.19 1 Conservative 2.78 1.35 2 Risk taking 2.97 1.43 3 Impulsive 3.45 1.07 4 Intuitive 3.88 1.24 5 Source: Primary Data
From the above table, it is found that the investors adopt the modes of calculative, conservative, risk taking, impulsive and intuitive in the respective order. The investors’ first notion of investment is the strategic calculation regarding safety, return and liquidity. They also give less importance to conservative and risk taking separately. It also reveals that the investors are very calculative in earning more profit from their investments.
4.30 Ranking Analysis for the Preference of Stock Exchange for Investing in equity market
The different stock exchanges like NSE, BSE and MSE are useful for the investors to deal with the capital market. Generally the investors in Tamil Nadu prefer these three stock exchanges for their investment in secondary market. Table - 4.35 presents the rank of preference of investors of secondary market.
Table - 4.35: Mean and Standard Deviations for Preference in Choosing Stock Exchanges
Variable Mean S.D. Rank NSE 1.44 0.684 1 BSE 2.04 0.689 2 MSE 2.49 0.741 3 Source: Primary Data
132 It is inferred from the above table that the investors investing in secondary market, give their first preference to NSE followed by BSE and MSE respectively. The NSE is the most popular among the investors of capital market.
Paired sample t-test is to identify the significant difference in the means among the five factors of the risk and return in equity market. This tool is also useful to identify the most popular factors of risk and return. The mean scores of each factor is presented in the table - 4.36, which is useful to identify the popular factor among the investors
Table – 4.36: Paired Samples Statistics for the Factors of the risk and return
Std. Std. Error Pair Factors Mean N Deviation Mean Pair 1 Shares 4.1576 507 .58216 .02028 Debentures 4.0445 507 .56689 .01975 Pair 2 Shares 4.1576 507 .58216 .02028 Mutual funds 4.1675 507 .58990 .02055 Pair 3 Shares 4.1576 507 .58216 .02028 Stock futures 4.2031 507 .58191 .02027 Pair 4 Shares 4.1576 507 .58216 .02028 Real estates 3.8706 507 .55730 .01941 Pair 5 Debentures 4.0445 507 .56689 .01975 Mutual funds 4.1675 507 .58990 .02055 Pair 6 Debentures 4.0445 507 .56689 .01975 Stock futures 4.2031 507 .58191 .02027 Pair 7 Debentures 4.0445 507 .56689 .01975 Real estates 3.8706 507 .55730 .01941 Pair 8 Mutual funds 4.1675 507 .58990 .02055 Stock futures 4.2031 507 .58191 .02027 Pair 9 Mutual funds 4.1675 507 .58990 .02055
133 Real estates 3.8706 507 .55730 .01941 Pair 10 Stock futures 4.2031 507 .58191 .02027 Real estates 3.8706 507 .55730 .01941 Source: Primary Data
The above table indicates the mean values of the factors of capital market reforms. It ranges from the minimum mean value of 3.87 for real estates to the maximum of 4.0 for stock futures.
The correlation table - 4.37 presents the relationship among all the factors which are inter linked.
Table – 4.37: Paired Samples Correlations for the Factors of the investment in equity Market
Pair Factors N Correlation Sig. Pair 1 Shares & Debentures 507 .645 .000** Pair 2 Shares & Mutual funds 507 .673 .000** Pair 3 Shares & Stock futures 507 .550 .000**
Pair 4 Shares & Real estates 507 .467 .000** Pair 5 Debentures & Mutual funds 507 .556 .000** Pair 6 Debentures & Stock futures 507 .429 .000**
Pair 7 Debentures & Real estates 507 .533 .000** Pair 8 Mutual funds & Stock 507 .514 .000** futures
Pair 9 Mutual funds & Real estates 507 .449 .000**
Pair 10 Stock futures & Real estates 507 .323 .000**
Source: Primary Data; ** - Significant at 0.01 level
As observed from the above table, the five factors constitute the efficient capital market reforms and the correlation co-efficient are highly significant. So, all reforms are
134 inter linked to accrue benefits to the investors. Paired sample t-test and their consequences are established in table - 4.37.
Table – 4.38: Paired Samples Test Values for the Factors of the Latest Reforms in Capital Market
Sig. (2- Pair Factors t df tailed)
Pair 1 Shares - Debentures 6.707 506 .000**
Pair 2 Shares - Mutual funds -.598 506 .550
Pair 3 Shares - Stock futures -2.364 506 .018*
Pair 4 Shares - Real estates 14.000 506 .000**
Pair 5 Debentures - Mutual funds -6.471 506 .000**
Pair 6 Debentures - Stock futures -7.415 506 .000**
Pair 7 Debentures - Real estates 9.189 506 .000**
Pair 8 Mutual funds - Stock futures -1.769 506 .077
Pair 9 Mutual funds - Real estates 14.140 506 .000**
Pair 10 Stock futures - Real estates 14.390 506 .000**
Source: Primary Data; ** - Significant at 0.01 level; * Significant at 0.05 level
The paired sample statistical table – 4.38 clearly reveals that the investors are very much attracted towards capital market with mean (4.20), followed by mutual funds (mean = 4.17), shares (mean = 4.16), Debentures (mean = 4.04) and finally real estates (mean = 3.87). Though the means are different, paired sample t-test would check the statistically significant differences among them. It is also found that shares and mutual funds are equally treated (t = 0.598) by the investors for their risk and return. The mutual funds and stock futures are also equally popular among the investors (t = 1.769) for both risk and return. So it is inferred that the investors are very much attracted by capital market after understanding the attractive financial sector reforms. The transparency about the performance of the companies issuing the shares and continuous monitoring of central government and the RBI raises the confidence among the investors besides the market
135 risk. It is also found that the investors are willing to invest their hard earned money to have lucrative returns in the short span of time.
4.31 Rate of return
The investors expect different percentage of investment as their returns with safety and security. Both the new companies and the existing ones can raise capital on the new issue market. The prime function of the new issue market is to facilitate the transfer of funds from the willing investors to the entrepreneurs setting up new corporate enterprises or going in for expansion, diversification, growth or modernization. Besides, helping corporate enterprises in securing their funds, the new issue market channelises the savings of individuals and others into investment. In this study four classification have been considered namely below 12%, 12-24%, 24-36%, and 36% and above as the returns.
Table 4.39: Frequency Distribution of Percentage of expected return
Valid Cumulative Percentage of investment Frequency Percent Percent
Valid Below 12% 300 59.2 59.2
12% - 24% 82 16.2 75.4
24% – 36% 28 5.6 81.0
36% above 97 19.0 100.0
Total 507 100.0
Source: Primary data
From the above table 4.39 it is ascertained that a maximum of 59.2% of the investors expect to get return below 12% of their investments followed by 19% of the
136 investors prefer to invest 36% and above of their investments, 16.2% of the investors prefer only 24 – 36% of their investments to be returned only 5.6% of the investors prefer to invest between 12 to 24% of their investments as returns. So the percentage analysis revealed that most of the investors expect below 25% of their total investment from equities market.
4.32 SUMMARY
In this chapter investment pattern, preferences, risk-return perceptions and investment objectives of the retail equity investors have been identified.
137 CHAPTER – V
INVESTMENT SATISFACTION AND PORTFOLIO CHOICE
INTRODUCTION
This chapter examines the various factors that significantly influence equity investors in the evaluation of equity share investments and makes an assessment of the post – investment satisfaction of various classes of investors and investors’ confidence as a whole. The study is based on various socio–economic and investment profile factors.
Investment evaluation and decision has become very crucial for any investor today amidst an array of investment avenues with relative advantages and disadvantages. Investment in equities is considered to be highly risky as compared to others, so investors need to study several factors and information while making equity investment. Success of equity issues is totally dependent on two parameters namely, post - investment satisfaction and investors’ confidence. Post - investment satisfaction creates a lasting impact on the investing habits of the investors and investors’ confidence decides the quantum of investment in equities. The basic factor that generates investment satisfaction and confidence is the high profitability prospects (rate of return) associated with equity investments. If investors perceive high profitability prospects, they tend to invest; if not, they look for other alternatives. The matching of the expected and derived rate of return creates satisfaction and confidence in the minds of the investors. Hence the growth of equity culture may be directly associated with the rate of return that builds investment satisfaction and restores investors’ confidence.
138 5.2 Cluster Analysis of investment evaluation.
In this study investments in the equity shares are classified into 5 elements, viz, general information, primary reform, details of present value. Project details and their changes and financial parameters. Based on these elements the investors are requested to express their opinion about capital investments and the scores are taken to perform cluster analysis by k-means method. By trial and error method it has been identified that 2 clusters are suitable for the study. The cluster classifications based on the investments are presented in table – 5.1.
Table – 5.1: Clusters of Investors Based on Elements of Retail investment
Factors Cluster of Mean Scores
1 2
General information 3.76 4.47
Company management 3.88 4.50
Details of present value 3.74 4.42
Project details and their changes 3.71 4.44
Financial parameters 3.66 4.47
Source: Primary Data
The above table indicates the mean scores of opinion of retail investment. The mean scores are high in the second cluster and low in the first cluster. The frequency of each cluster is presented in table – 5.1.
Table – 5.2: Number of Cases in Each Cluster of Retail investment
Clusters Frequency
1 215.000
2 292.000
139 Valid 507.000
Missing .000
Source: Primary Data
The 507 samples of investors are classified into two clusters. The first cluster has 215 frequencies, in which all investors express the opinion that they moderately agree on all the elements of capital investments. The second cluster has 292 frequencies, in which the investors strongly agree with the investments in equity shares. No one expressed the disagreements on retail investment. So, it is concluded that investors’ awareness ranges from moderate to high.
5.3. Paired sample t-Test Carried out for the Elements of Retail investment
Paired t-test is exploited here to find the significant difference in the means of the different elements of retail investment. The mean scores of the elements’ retail investment for comparison are presented in table - 5.3.
Table - 5.3: Paired Samples Statistics for the Elements of Retail investment Std. Std. Error Pair Variables Mean N Deviation Mean Pair 1 General informations 4.1552 507 .48908 .01704 Company management 4.2266 507 .50512 .01760 Pair 2 General informations 4.1552 507 .48908 .01704 Details of present values 4.1210 507 .58644 .02043 Pair 3 General informations 4.1552 507 .48908 .01704 Project details 4.1141 507 .55972 .01950 Pair 4 General informations 4.1552 507 .48908 .01704 Financial parameters 4.1138 507 .54601 .01902 Pair 5 Company management 4.2266 507 .50512 .01760 Details of present values 4.1210 507 .58644 .02043 Pair 6 Company management 4.2266 507 .50512 .01760 project details 4.1141 507 .55972 .01950 Pair 7 Company management 4.2266 507 .50512 .01760 Financial parameters 4.1138 507 .54601 .01902 Pair 8 Details of present values 4.1210 507 .58644 .02043
140 Change and their project 4.1141 507 .55972 .01950 details Pair 9 Details of present values 4.1210 507 .58644 .02043 Financial parameters 4.1138 507 .54601 .01902 Pair Change and their project 4.1141 507 .55972 .01950 10 details Financial parameters 4.1138 507 .54601 .01902 Source: Primary Data
The above table reveals that the mean scores of elements of retail investment range from 4.11 to 4.23 with their respective standard errors. The relationships among the elements of retail investment are presented in table - 5.3.
Table - 5.4: Paired Samples Correlations for the Elements of Retail investment
Correlat Pair Variable N Sig. ion Pair 1 General informations & Company 507 .587 .000** management Pair 2 General informations & present value 507 .537 .000** Pair 3 General informations & change and 507 .573 .000** their project details Pair 4 General informations & Financial 507 .657 .000** parameters Pair 5 & Details of present values 507 .431 .000** Pair 6 Company management and their 507 .479 .000** project details Pair 7 Company management & financial 507 .528 .000** parameters Pair 8 Present values & changes and their 507 .448 .000** project details Pair 9 Secondary & financial parameters 507 .496 .000** Pair 10 Project details and their changes 507 .519 .000** financial parameters Source: Primary Data; ** - Significant at 0.01 level
141 The above table indicates that all the correlation co-efficient are significant and elements of retail investment are deeply related among themselves in the opinion of the investors. The parametric paired sample significant t-test values are presented in table - 5.4.
Table - 5.5: Paired Samples Test Values for the Elements of Retail investment
Sig. (2- Pair Variables t df tailed) Pair 1 General informations & Company -4.540 506 .000** management Pair 2 General informations & Details of 1.874 506 .061 present values Pair 3 General informations & project 2.414 506 .016* details and their changes Pair 4 General informations & Financial 2.749 506 .006** parameters Pair 5 Company management & Details of 5.176 506 .000** present values Pair 6 Present values& project details and 5.922 506 .000** their changes Pair 7 Primary & financial parameters 6.325 506 .000** Pair 8 present values & project details and .328 506 .743 their changes Pair 9 Present values & financial parameters .359 506 .720 Pair Project details and their changes & .013 506 .990 10 Financial parameters Source: Primary Data; ** - Significant at 0.01 level; * Significant at 0.05 level
The paired sample t-test values clearly indicate that there is a significant difference between general informations and Company management (t=4.54), and the investors are confused with the company management (mean=4.23) and then the general informations (mean=4.16). It is also found that there is no significant difference between general informations and Details of present values (t = 1.874). This implies that the
142 investors have found equal awareness about general capital investments and Details of present values.
It is revealed in the analysis that there is a significant difference between general capital investments and change and their project details (t=2.414) and the investors possess their ideas about general informations (mean=4.15) and more changes and their project details. Similarly, it has been identified that the (mean = 4.11) significant difference between general informations and financial parameters (t = 2.749). In this pair the investors are more aware of general informations (mean = 4.15) than financial parameters (mean = 4.11).
The Company management are significantly different from Details of present values (t = 5.176), because of change in project details (t = 5.922), and financial parameters (t = 6.325). Among these urban investors are very much aware of company management (mean = 4.22), than Details of present values (mean = 4.12), change of project details (mean = 4.114) and financial parameters (mean = 4.113). It is also found that the investors accept equally about the investments in secondary market, project details and their changes, and financial parameters. It is concluded that all the investments are important and they reflect the investments of equity shares.
5.4 Correlation Analysis Carried out for Number of Years Dealing with Equity shares and Elements of Retail investment
Karl Pearson’s co-efficient of correlation is used to find out the relationship between the variables i.e. the number of years dealing with equity shares and different elements of retail investment.
The correlation co-efficient for number of years dealing with equity shares and elements of capital investments is depicted in table - 5.6.
143 Table – 5.6: Correlation Matrix for Number of Year Dealing
Variables Co-efficient Sig. General informations 0.048 0.165
Company management 0.006 0.854
Details of present values 0.018 0.608
Changes and their project details 0.005 0.888
Financial parameters 0.014 0.680
Source: Primary Data
The correlation table clearly shows that there is no significant relationship between the number of years dealing with equity shares and investor’s opinion about capital investments. This shows that the investors’ opinion on investments can not be distinguished on their experiences with equity shares dealings. So the retail investments are totally spread over all the investors equally independent of their number of years of dealings.
5.5 Correlation Analysis carried out for Percentage of Savings in Share Markets and Elements of Retail investment
The relationship between percentage of investment in share markets and different elements of retail investment can be established by applying the statistical tool for Karl Pearson’s co-efficient of correlation. The co-efficient values are presented in table - 5.7.
144 Table – 5.7: Correlation Co-efficient Table for Percentage of Savings in Share Market
Variables Co-efficient Sig. General informations -0.002 0.955 Company management -0.036 0.304 Details of present values 0.002 0.947 Changes and their project details 0.002 0.960 Financial parameters 0.026 0.449 Source: Primary Data
The correlation table clearly illustrates that the percentage of investment in share market does not have any relationship with the investors’ opinion about the capital investments. This also shows that the investors invest their money in share market to accrue maximum benefits before and after investments. So the retail investment just induces the investors to invest in share market, but the investors welcome any type of investments of equity shares if it is really worthy of better returns with absolutely no risk.
5.6 Analysis of Variance Carried out for the Elements of Equity shares Investments with respect to Preference of Investment
The different elements of retail investment are subject to the statistical treatment using analysis of variance with regard to the grouping of variables preference of investors for investment.
(a) Analysis of Variance for the Elements of Equity shares with Respect to Investment in Shares
In this case the analysis of variance is carried out with respect to the investment in shares and the following result is obtained from table - 5.8.
Table - 5.8: ANOVA for the Elements of Capital Investments with respect to Investment in Shares
145 Sum of Mean Variable Source df F Sig. Squares Square General informations Between Groups 2.020 6 .337 1.411 .207 Within Groups 194.839 817 .238 -- -- Total 196.858 506 ------Company Between Groups 2.514 6 .419 1.650 .131 management Within Groups 207.474 817 .254 -- -- Total 209.988 506 ------Details of present Between Groups 4.221 6 .704 2.061 .055 values Within Groups 278.506 817 .341 -- -- Total 283.044 506 ------Changes and their Between Groups 3.108 6 .518 1.661 .128 project details Within Groups 254.729 817 .312 -- -- Total 257.837 506 ------Financial parameters Between Groups 3.375 6 .562 1.899 .078 Within Groups 241.988 817 .296 -- -- Total 245.362 506 ------Source: Primary Data
From the above table, it has been ascertained that the elements of retail investment do not differ significantly with respect to investment in shares. So it is inferred that all the investors are aware of retail investment immaterial by whether they invest in shares or not. This also implies updated information to the investors could be a more effective source of information.
146 (b) Analysis of Variance for Different Elements of Retail investment and Investment in Government Bonds
The variation in group means of elements of retail investment with respect to investments in government bonds are presented in ANOVA table - 5.9.
Table – 5.9: ANOVA for the Elements of Retail investment with respect to Investment in Government Bonds Sum of Mean Variable Source df F Sig. Squares Square General Between Groups 6.185 7 .884 3.781 .000** informations Within Groups 190.674 816 .234 -- -- Total 196.858 506 ------Company Between Groups 5.376 7 .768 3.063 .003** management Within Groups 204.612 816 .251 -- -- Total 209.988 506 ------Details of Between Groups 5.761 7 .506 2.422 .019* present values Within Groups 277.283 816 .340 -- -- Total 283.044 506 ------Change and their Between Groups 11.255 7 1.608 5.321 .000** project details Within Groups 246.582 816 .302 -- -- Total 257.837 506 ------Financial Between Groups 9.231 7 1.319 4.557 .000** parameters Within Groups 236.131 816 .289 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the above table, it is clear that the general informations (F = 3.281), Company management (F = 3.781), Details of present values (F = 2.422) change of project details (F = 5.321), financial parameters (F = 4 .557) exhibit significant variance with respect to investors’ investment in Government Bonds. This also indicates that the investors who differ in their opinion of investing in
147 Government Bonds also differ in identifying the investments in equity shares. The investors are very much attracted by the primary and Details of present values, change of project details investments and investments in financial parameters. So, the investors who have turned their concentration towards government bonds investments are now rapidly returning towards share market investments due to investments in their elements.
(c) Analysis of Variance for Different Elements of Retail investment and Investment in Fixed Deposit
The variations in group means of elements of retail investment with respect to investments in fixed deposits are presented in ANOVA table - 5.10.
Table - 5.10: ANOVA for the Elements of Retail investment with respect to Investment in Fixed Deposits
Sum of Mean Variable Source df F Sig. Squares Square General Between Groups 1.587 7 .227 .947 .469 informations Within Groups 195.271 816 .239 -- -- Total 196.858 506 ------Company Between Groups 1.514 7 .216 .846 .549 management Within Groups 208.474 816 .255 -- -- Total 209.988 506 ------Details of Between Groups 1.436 7 .205 .595 .761 present values Within Groups 281.607 816 .345 -- -- Total 283.044 506 ------Changes and Between Groups 4.821 7 .689 2.221 .031* their project Within Groups 253.015 816 .310 -- -- details Total 257.837 506 -- --
Financial Between Groups 2.507 7 .403 1.357 .220 parameters Within Groups 242.538 816 .297 -- -- Total 245.362 506 -- -- Source: Primary Data; * Significant at 0.05 level
148 From the above table, it is vividly exhibited that the investors who are investing in fixed deposits differ in their opinion about change of project details (F = 2.221). So it is inferred that a part of the investors who deposit their money in banks in the form fixed deposits do not have much knowledge about changes of project details in equity shares. This also shows that the investors are very much attracted towards change of project details investments in equity shares and that in turn induces them to invest more in primary and secondary markets.
(d) Analysis of Variance for Elements of Retail investment with respect to Investment in Gold
The variations in group means of elements of retail investment with respect to investments in gold are presented in ANOVA table - 5.11.
Table - 5.11: ANOVA for the Elements of Retail investment with respect to Investment in Gold
Sum of Mean Variable Source df F Sig. Squares Square
General Between Groups 23.032 8 2.879 13.499 .000** informations Within Groups 173.826 815 .213 -- --
Total 196.858 506 ------
Company Between Groups 11.109 8 1.389 5.691 .000** management Within Groups 198.879 815 .244 -- --
Total 209.988 506 ------
Details of Between Groups 28.119 8 3.515 11.237 .000** present values Within Groups 254.925 815 .313 -- --
Total 283.044 506 ------
Changes and Between Groups 13.231 8 1.654 5.511 .000** their project Within Groups 244.605 815 .300 -- --
149 details Total 257.837 506 ------
Financial Between Groups 14.472 8 1.809 6.386 .000** parameters Within Groups 230.890 815 .283 -- --
Total 245.362 506 ------
Source: Primary Data; ** Significant at 0.01 level
From the above table, it is found that the investors can be distinguished on general informations (F=13.499), Company management (F=5.691), Details of present values (F=11.237), change of project details (F=5.511) and financial parameters (F=6.386) with respect to investment in gold. This shows that when the investors invest their money in gold they do not have more knowledge about retail investment. The investors who are investing in gold are also turning their concentration towards equity shares due to the tremendous developments in primary, details of present values, change of project details and financial parameters.
(e) Analysis of Variance for Elements of Retail investment with respect to Debentures
The variations in group means of elements of retail investment with respect to investments in debentures are presented in ANOVA table - 5.12.
Table - 5.12: ANOVA for the Elements of Retail investment with respect to Investment in Debentures Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups 6.238 7 .891 3.815 .000** informations Within Groups 190.621 816 .234 -- -- Total 196.858 506 ------Company Between Groups 3.464 7 .495 1.955 .058 management Within Groups 206.524 816 .253 -- -- Total 209.988 506 ------Details of Between Groups 7.373 7 1.053 3.118 .003** present Within Groups 275.670 816 .338 -- --
150 values Total 283.044 506 ------Changes and Between Groups 3.548 7 .507 1.626 .124 their project Within Groups 254.289 816 .312 -- -- details Total 257.837 506 ------Financial Between Groups 5.491 7 .784 2.668 .010** parameters Within Groups 239.872 816 .294 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level
From the above table it is inferred that the general informations (F=3.815), Details of present values (F=3.118), and financial parameters (F=2.668) differ significantly with respect to the investment in debentures. This shows that the investors’ option of investing in debentures discriminate their ideas about general informations, Details of present values and financial parameters. But they possess the same opinion of company management and change of project details. The investors who concentrate on debentures are very much attracted towards general informations, Details of present values and financial parameters. They profoundly believe that retail investments of above elements are really worthy of better returns. (f) Analysis of Variance for the Elements of Retail investment and Investment in Mutual Funds The variations in group means of elements of retail investment with respect to investments in mutual funds are presented in ANOVA table - 5.13.
Table - 5.13: ANOVA for the Elements of Retail investment with respect to Investment in Mutual Funds Sum of Mean Variable Sources df F Sig. Squares Square General Between 12.446 7 1.778 7.867 .000** informations Groups Within Groups 184.413 816 .226 -- -- Total 196.858 506 ------Company Between 3.032 7 .433 1.708 .104 management Groups Within Groups 206.956 816 .254 -- -- Total 209.988 506 ------
151 Details of Between 5.325 7 .761 2.235 .030* present Groups values Within Groups 277.718 816 .340 -- -- Total 283.044 506 ------Project Between 8.385 7 1.198 3.918 .000** details and Groups their Changes Within Groups 249.452 816 .306 -- -- Total 257.837 506 ------Financial Between 11.364 7 1.623 5.661 .000** parameters Groups Within Groups 233.998 816 .287 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the above table, it is ascertained that the general informations (F=7.867), Details of present values (F=2.235), change of project details (F=3.918), financial parameters (F=5.661) significantly vary with respect to investors option of investing in mutual funds, but in the case of Company management they express the same opinion. So it is inferred that when the investors want to invest their money in mutual funds they should possess thorough knowledge about capital investments. The investors of mutual funds also possess a tendency to shift their investment pattern towards equity shares. They feel that the same amount of risk is involved in mutual funds and equity shares but in the case of returns the equity shares exceeds more than the mutual fund.
(g) Analysis of Variance for the Elements of Retail investment and Investment in Real Estate
The variations in group means of elements of retail investment with respect to investments in real estate are presented in ANOVA table - 5.14.
Table - 5.14 ANOVA for the Elements of Retail investment with respect to Investment in Real Estate Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups 5.330 6 .888 3.790 .001** informations Within Groups 191.528 817 .234 -- --
152 Total 196.858 506 ------Company Between Groups 7.997 6 1.333 5.391 .000** management Within Groups 201.991 817 .247 -- -- Total 209.988 506 ------Details of Between Groups 15.669 6 2.611 7.980 .000** present values Within Groups 267.375 817 .327 -- -- Total 283.044 506 ------Project details Between Groups 10.221 6 1.704 5.621 .000** and their Within Groups 247.615 817 .303 -- -- Changes Total 257.837 506 ------Financial Between Groups 13.146 6 2.191 7.708 .000** parameters Within Groups 232.216 817 .284 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the above table, it is found that the general informations (F=3.790),
Company management (F=5.391), Details of present values (F=7.980) change of project details (F=5.621), financial parameters (F=7.708) differ significantly. This shows that some of the investors who invest in real estate possess the ideas about capital investments but others do not. Even though it is found that investing in real estate would give better returns, the investors are shifting their concentration towards equity shares due to the latest investments. They feel that they are able to get the same type of returns as that of real estate within a short span of time.
5.7 Analysis of Variance for the Elements of Retail investment with
Respect to the Grouping of Variable Reasons for Investments
The elements of capital investments are subject to the analysis of variance treatment to identify the significant variance among them with regard to various reasons for investments return, tax benefits and liquidity.
153 (a) Analysis of Variance for the Elements of Retail investment with
respect to the Reason for Investment – return
The variation in group means of elements of retail investment with respect to reason for investment namely, returns are presented in ANOVA table - 5.15.
Table - 5.15: ANOVA for the Elements of Retail investment with respect to the Reason for Investment – Return
Sum of Mean Variables Sources df F Sig. Squares Square General Between Groups 1.482 2 .741 3.113 .045* informations Within Groups 195.377 821 .238 -- -- Total 196.858 506 ------Company Between Groups .330 2 .165 .646 .524 management Within Groups 209.658 821 .255 -- -- Total 209.988 506 ------Details of Between Groups 2.554 2 1.277 3.737 .024* present values Within Groups 280.490 821 .342 -- -- Total 283.044 506 ------Project details Between Groups 2.655 2 1.328 4.272 .014* and their Within Groups 255.181 821 .311 -- -- Changes Total 257.837 506 ------Financial Between Groups .071 2 .036 .119 .888 parameters Within Groups 245.291 821 .299 -- -- Total 245.362 506 ------Source: Primary Data; * Significant at 0.05 level
It is found from the above table that general informations (F=3.113), Details of present values (F=3.737), and change of project details (F=4.272) differ significantly.
154 This shows that when the investors expect more returns, they differ in their views about general informations, Details of present values and change of project details whereas they have the same view on Company management and financial parameters.
(b) Analysis of Variance for the Elements of Retail investment with Respect to the Reason for Investment - Liquidity
The variations in group means of elements of retail investment with respect to reason for investment – liquidity are presented in ANOVA table - 5.16.
Table - 5.16: ANOVA for the Elements of Retail investment with respect to the Reasons for Investment – Liquidity
Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups 4.145 2 2.072 8.829 .000** informations Within Groups 192.714 821 .235 -- -- Total 196.858 506 ------Company Between Groups 1.812 2 .906 3.574 .028* management Within Groups 208.175 821 .254 -- -- Total 209.988 506 ------Details of Between Groups 5.427 2 2.714 8.025 .000** present Within Groups 277.616 821 .338 -- -- values Total 283.044 506 ------Project Between Groups .506 2 .253 .807 .447 details and Within Groups 257.331 821 .313 -- -- their Total changes 257.837 506 ------Financial Between Groups 2.540 2 1.270 4.294 .014* parameters Within Groups 242.822 821 .296 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the above table it is found that general informations (F=8.829), Company management (F=3.574), Details of present values (F=8.025), and financial parameters (F=4.294) differ significantly. So it is inferred that when the investors expect liquidity
155 from their investment some of them are highly aware of capital investments while some others do not. But they possess the same view about changes of project details. The investors identify liquidity due to investments in primary and secondary market and financial parameters.
(c) Analysis of Variance for the Elements of Retail investment and with respect to Reason for Investment – Tax Benefits
The variation in group means of elements of retail investment with respect to reason for investment, namely tax benefits are presented in ANOVA table – 5.17.
Table - 5.17: ANOVA for the Elements of Retail investment with respect to the Reason for Investment – Tax Benefits
Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups .699 2 .349 1.463 .232 informations Within Groups 196.159 821 .239 -- -- Total 196.858 506 ------Company Between Groups 1.957 2 .979 3.862 .021* management Within Groups 208.031 821 .253 -- -- Total 209.988 506 ------Details of Between Groups 1.708 2 .854 2.492 .083 present values Within Groups 281.336 821 .343 -- -- Total 283.044 506 ------Project details Between Groups .503 2 .251 .802 .449 and their Within Groups 257.334 821 .313 -- -- changes Total 257.837 506 ------Financial Between Groups 1.750 2 .875 2.949 .053 parameters Within Groups 243.612 821 .297 -- -- Total 245.362 506 ------
Source: Primary Data; * Significant at 0.05 level
The analysis of variance table clearly reveals that Company management
(F=3.862) differ significantly with respect to tax benefits. So it is concluded that the
156 investors who invest their money for tax benefits are well aware of general informations,
Details of present values, change of project details and financial parameters.
5.8 Analysis of Variance carried out for Different Elements of retail investments and it’s Influence on Factors of Investment Decision
Analysis of variance is performed on the elements of capital investments, viz., general informations, company management, details of present values, change of project details and financial parameters with respect to different influential factors of investment decision – abridged prospectus, TV channels, consultant, and websites. This analysis helps to identify which influential factor affects the investors in their investment decision process in the light of retail investment.
(a) ANOVA for Elements of Retail investment with regard to abridged prospectus
The variations in group means of elements of retail investment with respect to decision of the abridged prospectus are presented in ANOVA table – 5.18.
Table - 5.18 ANOVA for the Elements of Retail investment with regard to the Investment Decisions Influenced by abridged prospectus Sum of Mean Variables Sources df F Sig. Squares Square General Between 2.533 5 .507 2.133 .060 informations Groups Within Groups 194.325 818 .238 -- -- Total 196.858 506 ------Company Between 6.621 5 1.324 5.326 .000** management Groups Within Groups 203.367 818 .249 -- -- Total 209.988 506 ------
157 Details of Between 1.275 5 .255 .740 .594 present values Groups Within Groups 281.769 818 .344 -- -- Total 283.044 506 ------Project details Between 3.686 5 .737 2.373 .038* and their Groups changes Within Groups 254.150 818 .311 -- -- Total 257.837 506 ------
Financial Between 2.519 5 .504 1.697 .133 parameters Groups Within Groups 242.843 818 .297 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the table, it is ascertained that Company management (F=5.326), and change of project details (F=2.373) differ significantly and other elements do not exhibit any significance by variance. This forces to infer that when the abridged prospectus influences the investment decision, the investors possess good awareness on general informations, Details of present values and financial parameters. In the case of Company management and change of project details the investors significantly vary in their perception of capital investments.
(b) ANOVA for Different Elements of Retail investment with regard to TV channels
The variations in group means of elements of retail investment with respect to TV channels are presented in ANOVA table - 5.19.
Table - 5.19: ANOVA for the Elements of Retail investment with regard to the Investment Decisions Influenced by TV channels Sum of Mean Variables Sources df F Sig. Squares Square General Between Groups 3.546 5 .709 3.001 .011* informations Within Groups 193.312 818 .236 -- -- Total 196.858 506 ------
158 Company Between Groups 5.487 5 1.097 4.390 .001** management Within Groups 204.501 818 .250 -- -- Total 209.988 506 ------
Details of Between Groups 1.319 5 .264 .766 .574 present values Within Groups 281.725 818 .344 -- -- Total 283.044 506 ------Project details Between Groups 7.516 5 1.503 4.913 .000** and their Within Groups 250.320 818 .306 -- -- changes Total 257.837 506 ------Financial Between Groups .953 5 .191 .638 .671 parameters Within Groups 244.410 818 .299 -- -- Total 245.362 506 ------
Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the above table, it is seen that general informations (F=3.001), Company management (F=4.390) and change of project details (F=4.913) differ significantly when the investment decision is influenced by the project details. The investors who are influenced by the TV channels have high awareness on Details of present values and financial parameters.
(c) ANOVA for Different Elements of Retail investment with regard to Consultants
The variations in group means of elements of retail investment with respect to consultants are presented in ANOVA table - 5.20.
Table – 5.20: ANOVA for the Elements of Retail investment with regard to the Investment Decisions Influenced by Consultant Sum of Mean Variables Sources df F Sig. Squares Square General Between Groups 3.037 3 1.012 4.283 .005** informations Within Groups 193.822 820 .236 -- -- Total 196.858 506 ------Company Between Groups 7.856 3 2.619 10.623 .000**
159 management Within Groups 202.132 820 .247 -- -- Total 209.988 506 ------
Details of Between Groups 2.225 3 .742 2.166 .091 present Within Groups 280.818 820 .342 -- -- values Total 283.044 506 ------Project Between Groups 9.043 3 3.014 9.934 .000** details and Within Groups 248.794 820 .303 -- -- their changes Total 257.837 506 ------Financial Between Groups 4.535 3 1.512 5.147 .002** parameters Within Groups 240.827 820 .294 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the analysis of variance table, it is inferred that the investors who approach consultants for investment in equity shares differ significantly in their knowledge about general informations (F=4.283), Company management (F=10.623) change of project details (F=9.934) and financial parameters (F=5.147). It is also found that in the case of Details of present values all the investors are equally well aware and differ significantly in other investments. So consultants are forcing them to have knowledge about details of present values.
(d) ANOVA for Elements of Retail investment with regard to web sites
The variations in group means of elements of retail investment with respect to investment decision by web sites are presented in ANOVA table - 5.21.
Table - 5.21: ANOVA for the Elements of Retail investment with regard to the Investment Decisions Influenced by websites Sum of Mean Variables Sources df F Sig. Squares Square General Between Groups 3.264 2 1.632 6.921 .001** informations Within Groups 193.594 821 .236 -- --
160 Total 196.858 506 ------Company Between Groups 4.036 2 2.018 8.044 .000** management Within Groups 205.952 821 .251 -- --
Total 209.988 506 ------Details of Between Groups .872 2 .436 1.268 .282 present Within Groups 282.172 821 .344 -- -- values Total 283.044 506 ------Project Between Groups 7.130 2 3.565 11.674 .000** details and Within Groups 250.707 821 .305 -- -- their changes Total 257.837 506 ------Financial Between Groups 4.929 2 2.464 8.415 .000** parameters Within Groups 240.433 821 .293 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the above table of analysis of variance, it is ascertained that the investors consult their friends and relatives to invest in equity shares when they do not have much knowledge about general informations (F=6.921), Company management (F=8.044), change of project details (F=11.674), and financial parameters (F=8.415). In the case of Details of present values, the investors cannot be distinguished in terms of their awareness when their investment decision is influenced by web sites.
5.9 Association between Preference of Investment in Equity shares and Clusters of Awareness on Retail investment
The preference of investment in equity shares viz. primary market and secondary market and both are taken for the analysis. Some times the investors want to invest in both the markets, so that option is also considered for the study. To find the association between the above mentioned variables, the non-parametric chi-square test is applied. Table - 5.22 presents the opinion of investment preference of investors in primary and secondary markets.
161 Table - 5.22: Association between Preference of Investment in Equity shares and Clusters of Investors
Preference of Investments Clusters of Investors Total in Equity shares 1 2
Primary market 24 18 42
Secondary market 48 33 81
Both 155 229 384
Total 227 280 507 Source: Primary Data
The above table indicates that the investors want to invest in both the markets and the secondary market is more popular among the investors than the primary market. The chi-square test value is presented in the table - 5.23.
Table - 5.23: Chi-Square for Preference of Investments in Equity shares
Significant Statistical Tool Value Df (2-sided) Pearson Chi-Square 21.256 2 .000**
Likelihood Ratio 21.174 2 .000**
Linear-by-Linear Association 17.377 1 .000**
No. of Valid Cases 507 -- --
Source: Primary Data; ** Significant at 0.01 level
Null Hypothesis
There is no association between preference of investment in equity shares and clusters of awareness on retail investment.
162 From the table of chi-square test it is found that the chi-square value as 21.256, p- value = 0.000 for 2 degrees of freedom. So the null hypothesis is rejected at 5% level of significance and it is concluded that there is a association between preference of investment in equity shares and cluster of awareness on retail investment (i.e.) after knowing the capital investments only the investors decide to invest in primary market and secondary market.
5.10 General Linear Multivariate Model Analysis Carried out for Different Elements of Retail investment and Percentage of Investment in Equity shares
In this analysis, the elements of capital investments are considered as independent co-variants and the percentage of investment options in equity shares are considered as dependent variables. This analysis of multivariate general linear model aims at finding whether the percentage of investment in primary and secondary markets is affected by the investments in equity shares. The individual impact of retail investment on percentage of investment in primary and secondary markets is presented in table - 5.24.
Table - 5.24: Multivariate General Linear Model for Percentage of Investments
Type III Dependent Mean Sources Sum of df F Sig. Variables Square Squares Corrected Percent of Model investment in 45473.254(a) 5 9094.651 12.403 .000** primary market Percent of investment in 21633.333(b) 5 4326.667 5.794 .000** secondary market Intercept Percent of investment in 4028.996 1 4028.996 5.494 .019* primary market Percent of investment in 73508.593 1 73508.593 98.444 .000** secondary market
163 Type III Dependent Mean Sources Sum of df F Sig. Variables Square Squares General Percent of informations investment in 13.266 1 13.266 .018 .893 primary market Percent of investment in 970.030 1 970.030 1.299 .255 secondary market Company Percent of management investment in 4349.727 1 4349.727 5.932 .015* primary market Percent of investment in 761.127 1 761.127 1.019 .313 secondary market Details of Percent of present values investment in 4543.825 1 4543.825 6.197 .013* primary market Percent of investment in 3665.884 1 3665.884 4.909 .027* secondary market Changes and Percent of their Project investment in 1594.629 1 1594.629 2.175 .141 details primary market Percent of investment in 650.103 1 650.103 .871 .351 secondary market Financial Percent of parameters investment in 1079.206 1 1079.206 1.472 .225 primary market Percent of investment in 44.579 1 44.579 .060 .807 secondary market Error Percent of investment in 599825.725 818 733.283 -- -- primary market
164 Type III Dependent Mean Sources Sum of df F Sig. Variables Square Squares Percent of investment in 610801.714 818 746.701 -- -- secondary market Total Percent of investment in 2723037.000 507 ------primary market Percent of investment in 2348437.000 507 ------secondary market Corrected Percent of Total investment in 645298.979 506 ------primary market Percent of investment in 632435.047 506 ------secondary market a. R Squared = .070 (Adjusted R Squared = .065); b. R Squared = .034 (Adjusted R Squared = .028) Source: Primary Data ** Significant at 0.01 level; * Significant at 0.05 level
It is inferred from the above table that the general informations in equity shares do not have any impact on investors to invest certain percentage in primary and secondary markets. Company management induce the investors to invest a considerable percentage of their money in primary market (F=5.932). Details of present values make the investors to invest a good percentage of money in both primary and secondary markets (F=4.909). The change of project details and financial parameters do not have any impact on investors to invest money in primary and secondary markets. So it is concluded that the investments in primary and secondary markets make the investors to allot the required percentage of investment.
5.11 Association between Criteria for Investment and Clusters of Awareness on Retail investment
165 Non-parametric chi-square test is used to find the association between criteria for investments in equity shares and clusters of awareness on equity shares. This helps to know whether the retail investment highlight these criteria and pave the way to investors to decide the prudential consequence of their investments. The opinion of the two groups of equity shares investors about the criteria of investment is presented in table - 5.25.
Table - 5.25: Association Criteria for Investment and Clusters of wareness
Clusters of Investors Total Criteria for investments 1 2
Sector to which the company belongs 89 169 258 to
Financial performance of the 138 111 249 company in recent past
Total 227 280 507 Source: Primary Data
The above table reveals that the criteria of investment are equally popular among the investors. The chi-square test value is presented in table - 5.26.
Table - 5.26: Chi-Square Test and Criteria for Investments
Asymp. Sig. Exact Sig. Exact Sig. Statistical Tools Value Df (2-sided) (2-sided) (1-sided)
Pearson Chi- 36.381 1 .000** -- -- Square
Continuity 35.538 1 .000** -- -- Correction
Likelihood Ratio 36.665 1 .000** -- --
Fisher's Exact ------.000** .000**
166 Test
Linear-by-Linear 36.337 1 .000** -- -- Association
No. of Valid 507 ------Cases Source: Primary Data** Significant at 0.01 level
Null Hypothesis
There is no association between criteria for investments and clusters of awareness of retail investment.
From the chi-square test it is found that the chi-square value is 36.381, when the p-value=0.000. So the null hypothesis is rejected at 5% level of significance and it is inferred that there is an association between criterion for investment and cluster of awareness of capital investments. This also shows that the investors are all well aware that the capital investments giving certain specific criteria for the investment procedure.
5.12 Cluster Analysis carried out for Identifying the Extent of Awareness of Investors on equity investment
Cluster analysis is a statistical tool brought upon the problems of identifying the heterogeneous groups prevailing in the sample. These heterogeneous groups are homogeneous within them. Cluster analysis is carried out with the newly obtained 5 factors of capital market reforms in factor analysis. The formations of new three clusters are shown in table - 5.27.
Table – 5.27: Final Cluster Centres for Awareness of the equity investment
Clusters and Mean Scores Factor 1 2 3 Investment objectives 2.92 3.73 4.48 Investment satisfaction 3.23 3.57 4.35 Facility satisfaction 2.80 3.84 4.45
167 Innovative measures 2.97 3.96 4.44 Problems 3.18 3.51 4.11 Source: Primary Data
The above table revealed the emergence of three groups of investors based on their awareness of capital market reforms. The frequency distribution of each cluster is presented in table - 5.28.
Table – 5.28: Frequency of Clusters for Awareness of the Latest Reforms in Capital Market
Cluster Frequency 1 31.000 2 156.000 3 320.000 Valid 507.000 Missing .000 Source: Primary Data
The cluster analysis transparently reveals that the samples are classified into 3 heterogeneous groups with respect to investment objectives, investment satisfaction, facility satisfaction, innovative measures and problems. The first cluster investors do not possess more awareness with the equity market and the frequency of this cluster is 31. The second cluster has the frequency of 156 and they are moderately aware of the equity investment in capital market. The third clusters with the frequency of 320 are highly aware of the equity investment. So the respondents in the study are classified into 3 groups based on their awareness on the equity investment pattern. This group classification will be further used in the analysis. So it is concluded that the investors of capital market are distributed into three types on the basis of investment pattern prevailing in India
168 5.13 Analysis of Variance carried out for Different Elements of Equity shares Investments and Preference of Investment in Industries
This analysis is aimed at ascertaining whether the capital investments awareness varies with respect to different industries in equity shares. It also helps to find out the relationship between retail investment and the most popular industries attracting the investors.
(a) ANOVA for Different Elements of Retail investment with regard to Preference of Investment in Banking Sector
The variations in group means of elements of retail investment with respect to investment in banking sector are presented in ANOVA table - 5.29.
Table - 5.29: ANOVA for the Elements of Retail investment with regard to Preference of Investment in Banking Sector
Sum of Mean Variables Sources df F Sig. Squares Square
General Between 6.391 8 .799 3.418 .001** informations Groups
Within 190.467 815 .234 -- -- Groups
Total 196.858 506 ------
Company Between 5.492 8 .687 2.736 .006** management Groups
Within 204.495 815 .251 -- -- Groups
Total 209.988 506 ------
Details of Between 11.778 8 1.472 4.423 .000** present values Groups
Within 271.265 815 .333 -- -- Groups
169 Total 283.044 506 ------
Project details Between 10.415 8 1.302 4.288 .000** and their Groups changes Within 247.422 815 .304 -- -- Groups
Total 257.837 506 ------
Financial Between 10.390 8 1.299 4.505 .000** parameters Groups
Within 234.972 815 .288 -- -- Groups
Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the above table, it is found that general informations (F=3.418), Company management (F=2.736), Details of present values (F=4.423) change of project details (F=4.288) and financial parameters (F=4.505) vary significantly with respect to investment in banking sector. This shows that the capital investments have affected the investment in the banking sector. More number of investors are enthusiastic in venturing into equity shares.
(b) Analysis of Variance for Different Elements of Retail investment with regard to Preference of Investment in FMCG Sector
The variations in group means of elements of retail investment with respect to investment in FMCG sector are presented in ANOVA table - 5.30.
Table - 5.30: ANOVA for the Elements of Retail investment with regard to Preference of Investment in FMCG Sector Sum of Mean Variables Sources df F Sig. Squares Square General Between 2.969 7 .424 1.785 .087 informations Groups Within Groups 193.889 816 .238 -- -- Total 196.858 506 ------
170 Company Between 4.861 7 .694 2.763 .008** management Groups Within Groups 205.127 816 .251 -- -- Total 209.988 506 ------Details of Between 3.528 7 .504 1.471 .174 present Groups values Within Groups 279.516 816 .343 -- -- Total 283.044 506 ------Project Between 1.021 7 .146 .463 .861 details and Groups their Within Groups 256.816 816 .315 -- -- changes Total 257.837 506 ------Financial Between 2.818 7 .403 1.354 .222 parameters Groups Within Groups 242.544 816 .297 -- -- Total 245.362 506 ------Source: Primary Data** Significant at 0.01 level
From the above table, it becomes vividly clear that company management (F=2.763) have affected the investments in FMCG sector. Other capital investments do not make any impact on FMCG sector. So it shows that the investors have the knowledge about company management before they invest in FMCG industries.
(c) Analysis of Variance for Different Elements of Retail investment with regard to Preference of Investment in Pharma Sector
The variations in group means of elements of retail investment with respect to investment in pharma sector are presented in ANOVA table - 5.31
Table - 5.31: ANOVA for the Elements of Retail investment with regard to Preference of Investment in Pharma Sector Sum of Mean Variable Sources Square df F Sig. Square s General Between 9.231 7 1.319 5.735 .000** informations Groups
171 Within Groups 187.628 816 .230 -- -- Total 196.858 506 ------Company Between 6.755 7 .965 3.874 .000** management Groups Within Groups 203.233 816 .249 -- -- Total 209.988 506 ------Details of Between 8.561 7 1.223 3.636 .001** present Groups values Within Groups 274.483 816 .336 -- -- Total 283.044 506 ------Project Between 10.396 7 1.485 4.898 .000** details and Groups their changes Within Groups 247.441 816 .303 -- -- Total 257.837 506 ------Financial Between 7.563 7 1.080 3.708 .001** parameters Groups Within Groups 237.799 816 .291 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level
A cursory glance at the above table reveals that the general informations (F=5.735), company management (F=3.874), details of present values (F=3.636), change of project details (F=4.898), and financial parameters (F=3.708) very much affect the investment in pharma sector. So it is inferred that the investors investing more in pharma sector due to retail investment.
(d) Analysis of Variance for Elements of Retail investment with regard to Preference of Investment in PSE Industries
The variations in group means of elements of retail investment with respect to investment in PSE sector are presented in ANOVA table – 5.32.
172 Table - 5.32: ANOVA for the Elements of Retail investment with regard to Preference of Investment in PSE Sector
Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups 12.048 7 1.721 7.599 .000** informations Within Groups 184.367 814 .226 -- -- Total 196.416 821 ------
Company Between Groups 10.982 7 1.569 6.456 .000** management Within Groups 197.806 814 .243 -- -- Total 208.789 821 ------
Details of Between Groups 12.781 7 1.826 5.507 .000** present values Within Groups 269.884 814 .332 -- -- Total 282.665 821 ------Project details Between Groups 9.750 7 1.393 4.611 .000** and their Within Groups 245.889 814 .302 -- -- changes Total 255.639 821 ------Financial Between Groups 13.657 7 1.951 6.859 .000** parameters Within Groups 231.541 814 .284 -- -- Total 245.198 821 ------Source: Primary Data** Significant at 0.01 level
It is inferred from the above table that general informations (F=7.599), company management (F=6.456), details of present values (F=5.507), change of project details (F=4.611), and financial parameters (F=6.859) affecting the investment in PSE sector. Hence it is clear that the capital investments direct the investors to invest more in PSE sector.
(e) Analysis of Variance for Elements of Retail investment with regard to Preference of Investment in MNC Sector
The variations in group means of elements of retail investment with respect to investment in MNC sector are presented in ANOVA table - 5.33.
173 Table - 5.33: ANOVA for the Elements of Retail investment with regard to Preference of Investment in MNC Sector
Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups 6.557 7 .937 4.016 .000** informations Within Groups 190.302 816 .233 -- -- Total 196.858 506 ------Company Between Groups 9.248 7 1.321 5.371 .000** management Within Groups 200.739 816 .246 -- -- Total 209.988 506 ------Details of Between Groups 7.999 7 1.143 3.390 .001** present values Within Groups 275.045 816 .337 -- -- Total 283.044 506 ------Project details Between Groups 13.871 7 1.982 6.628 .000** and their Within Groups 243.965 816 .299 -- -- changes Total 257.837 506 ------Financial Between Groups 12.474 7 1.782 6.244 .000** parameters Within Groups 232.889 816 .285 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level
It is deduced from the above table that the general informations (F=4.016), Company management (F=5.371), Details of present values (F=3.390), change of project details (F=6.628), and financial parameters (F=6.244) affect the investment in MNC sector. The degrees of awareness and knowledge about retail investment have enabled the investors for making meaningful investment decisions in MNC sector.
(f) Analysis of Variance for Different Elements of Retail investment with regard to Preference of Investment in IT Sector
The variations in group means of elements of retail investment with respect to investment in IT sector are presented in ANOVA table - 5.34.
174 Table - 5.34: ANOVA for the Elements of Retail investment with regard to Preference of Investment in IT Sector
Sum of Mean Variable Sources df F Sig. Squares Square
General Between Groups 4.792 7 .685 2.908 .005** informations Within Groups 192.067 816 .235 -- --
Total 196.858 506 ------
Company Between Groups 3.949 7 .564 2.234 .030* management Within Groups 206.039 816 .252 -- --
Total 209.988 506 ------
Details of Between Groups 13.207 7 1.887 5.705 .000** present values Within Groups 269.837 816 .331 -- --
Total 283.044 506 ------
Project details Between Groups 3.452 7 .493 1.582 .137 and their changes Within Groups 254.384 816 .312 -- -- Total 257.837 506 ------
Financial Between Groups 5.187 7 .741 2.518 .014* parameters Within Groups 240.175 816 .294 -- --
Total 245.362 506 ------
Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the above table, it is inferred that general informations (F=2.908), Company management (F=2.234), Details of present values (F=5.705), and financial parameters have affected the investment in IT sector. The above mentioned investments induce the investors to invest in IT sector. It is also found that change of project details does not have any impact on investment in IT sector.
175 (g) Analysis of Variance for Different Elements of Retail investment with regard to Preference of Investment in Manufacturing Sector
The variations in group means of elements of retail investment with respect to investment in manufacturing sector are presented in ANOVA table - 5.35.
Table - 5.35: ANOVA for the Elements of Retail investment with regard to Preference of Investment in Manufacturing Sector Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups 4.620 7 .660 2.801 .007** informations Within Groups 192.239 816 .236 -- -- Total 196.858 506 ------
Company Between Groups 1.680 7 .240 .940 .474 management Within Groups 208.307 816 .255 -- -- Total 209.988 506 ------Details of Between Groups 3.116 7 .445 1.297 .248 present values Within Groups 279.928 816 .343 -- -- Total 283.044 506 ------Project details Between Groups 3.869 7 .553 1.776 .089 and their Within Groups 253.968 816 .311 -- -- changes Total 257.837 506 ------Financial Between Groups 3.894 7 .556 1.880 .070 parameters Within Groups 241.468 816 .296 -- -- Total 245.362 506 ------
Source: Primary Data; ** Significant at 0.01 level
The above table is useful in deciding that the general informations (F=2.801) affect the investment in manufacturing sector. This also shows that the investors find a scope for their investment in manufacturing sector after general capital investments. Other investments do not have any role to play with manufacturing sector.
(h) Analysis of Variance for Different Elements of Retail investment with regard to Preference of Investment in Service Sector
176 The variations in group means of elements of retail investment with respect to investment in service sector are presented in ANOVA table - 5.36.
Table - 5.36: ANOVA for the Elements of Retail investment with regard to Preference of Investment in Service Sector Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups 6.951 7 .993 4.267 .000** informations Within Groups 189.907 816 .233 -- -- Total 196.858 506 ------Company Between Groups 8.400 7 1.200 4.857 .000** management Within Groups 201.588 816 .247 -- -- Total 209.988 506 ------Details of Between Groups 13.342 7 1.906 5.767 .000** present values Within Groups 269.702 816 .331 -- -- Total 283.044 506 ------Project details Between Groups 6.085 7 .869 2.818 .007** and their Within Groups 251.752 816 .309 -- -- changes Total 257.837 506 ------Financial Between Groups 8.541 7 1.220 4.204 .000** parameters Within Groups 236.821 816 .290 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level
The above table clearly reveals that the general informations (F=4.267), Company management (F=4.857), Details of present values (F=5.767), change of project details (F=2.818) and financial parameters (F=4.204) affect the investment in service sector. This also shows that the investors are drifting towards service sector after capital investments.
5.14 Association between Investment in Equity shares with Higher Risk and Clusters of Awareness on Retail investment
This analysis is aimed at verifying the retail investment made every procedure of investment transparent and free from risks. The non- parametric chi-square test is applied
177 to achieve this objective. The opinion of the group of investors about the risk involved in retail investment is presented in the table - 5.37.
Table - 5.37: Investment in Equity shares is Higher Risk and Clusters of Awareness on Retail investment
Investment in Clusters of Equity shares is Investors Total Higher Risk 1 2
Yes 318 415 733
No 48 43 91
Total 366 458 824 Source: Primary Data
The above table indicates that a maximum number of both the clusters confessed that the risk in equity shares investments is higher. The chi-square test value is presented in the table - 5.38.
Table – 5.38: Chi-square Test Statistics for Investment in Equity shares is Higher Risk
Asymp. Sig. Exact Sig. Exact Sig. Statistical Tool Value df (2-sided) (2-sided) (1-sided) Pearson Chi- 2.875 1 .090 -- -- Square Continuity 2.508 1 .113 -- -- Correction Likelihood Ratio 2.856 1 .091 -- -- Fisher's Exact ------.094 .057 Test Linear-by-Linear 2.872 1 .090 -- -- Association N of Valid Cases 507 ------Source: Primary Data
178 Null Hypothesis
There is no association between extension of risk in equity shares and awareness on retail investment.
From the chi-square table, it is inferred that the null hypothesis is accepted at 5% level of significance and that there is no association between extensive of risk and awareness of retail investment. It clearly shows that the investors are very much aware of risks involved in investing in equity shares, because it depends upon the performance of firms upon which their money is invested.
5.15 Analysis of Variance Carried out for Different Elements of Capital Market Investments with regard to Preference of Stock Exchange
The analysis of variance is applied on the elements of capital investments with respect to different stock exchanges like NSE, BSE and MSE. This would help the researcher to analyse the impact of retail investment in different stock exchanges.
(a) Analysis of Variance for Elements of Retail investment with regard to Preference of sensex
The variations in group means of elements of retail investment with respect to preference to sensex are presented in ANOVA table - 5.39.
Table - 5.39: ANOVA for the Elements of Retail investment with regard to Preference of stock exchanges - sensex
Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups 14.540 3 4.847 21.798 .000** informations Within Groups 182.319 820 .222 -- -- Total 196.858 506 ------Company Between Groups 8.217 3 2.739 11.131 .000** management Within Groups 201.771 820 .246 -- --
179 Total 209.988 506 ------Details of Between Groups 7.227 3 2.409 7.162 .000** present values Within Groups 275.817 820 .336 -- -- Total 283.044 506 ------Project details Between Groups 12.219 3 4.073 13.598 .000** and their Within Groups 245.618 820 .300 -- -- changes Total 257.837 506 ------Financial Between Groups 16.471 3 5.490 19.669 .000** parameters Within Groups 228.892 820 .279 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level
It is deduced from the above table that the general informations (F=21.798), Company management (F=11.131), Details of present values (F=7.162), change of project details (F=13.598) and financial parameters (F=19.669) significantly differ with respect to rules assigned to sensex. So it is inferred that preference of sensex depends upon the retail investment.
(b) Analysis of Variance for Elements of Retail investment with regard to Preference of Stock Exchanges - Nifty
The variations in group means of elements of retail investment with respect to preference to Nifty are presented in ANOVA table - 5.40.
Table - 5.40 ANOVA for the Elements of Retail investment with regard to Preference of nifty
Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups 14.336 3 4.779 21.468 .000** informations Within Groups 182.523 820 .223 -- -- Total 196.858 506 ------Company Between Groups 9.595 3 3.198 13.087 .000** management Within Groups 200.393 820 .244 -- -- Total 209.988 506 ------
180 Details of Between Groups 11.305 3 3.768 11.371 .000** present values Within Groups 271.739 820 .331 -- -- Total 283.044 506 ------Project details Between Groups 7.793 3 2.598 8.519 .000** and their Within Groups 250.043 820 .305 -- -- changes Total 257.837 506 ------Financial Between Groups 15.892 3 5.297 18.930 .000** parameters Within Groups 229.470 820 .280 -- -- Total 245.362 506 ------Source: Primary Data; ** Significant at 0.01 level
From the above table it is noted that the general informations (F=21.468), Company management (F=13.087), Details of present values (F=11.371), change of project details (F=8.519) and financial parameters (F=18.930) differ significantly with respect to Nifty. This shows that the investors are able to set information about Nifty through the investments of elements of equity shares.
(c) Analysis of Variance for Elements of Retail investment with regard to Preference of Stock Exchanges - MSE
The variations in group means of elements of retail investment with respect to preference to CNX 100 are presented in ANOVA table - 5.41
Table - 5.41: ANOVA for the Elements of Capital Investments with regard to Preference of CNX 100
Sum of Mean Variable Sources df F Sig. Squares Square General Between Groups 2.279 3 .760 3.201 .023* informations Within Groups 194.580 820 .237 -- -- Total 196.858 506 ------Company Between Groups .560 3 .187 .731 .534 management Within Groups 209.428 820 .255 -- -- Total 209.988 506 ------Details of Between Groups 2.344 3 .781 2.282 .078 present values Within Groups 280.700 820 .342 -- -- Total 283.044 506 ------
181 Project details Between Groups 2.659 3 .886 2.848 .037* and their Within Groups 255.178 820 .311 -- -- changes Total 257.837 506 ------Financial Between Groups 1.586 3 .529 1.779 .150 parameters Within Groups 243.776 820 .297 -- -- Total 245.362 506 ------
Source: Primary Data; * Significant at 0.05 level It is ascertained from the above table that general informations (F=3.201), and change of project details (F=2.848) induce the investors to give preference to CNX 100. Other elements of equity shares do not have any impact on investors to choose CNX 100. So the investors in CNX 100possess the same opinion about primary and secondary markets as well as financial parameters.
5.16 Association between Reason for Preference Given to Stock Exchange Dealings and Clusters of Awareness of retail investment
The non-parametric chi-square test is applied between the two variables-reason for stock exchange dealings and clusters of awareness of capital investments. This also helps to ascertain the retail investment and its relationship with different stock exchanges in India. The different groups of investors possess different opinion about reasons for stock exchange dealings and they are presented in table - 5.42
Table - 5.42: Reason for Preference Given to Stock Exchange Dealing and Clusters of Awareness on Retail investment
Reasons for Preference given to Stock Clusters of Investors Total Exchange Dealing 1 2 Reputation 120 213 333 No. of stocks listed 130 93 223 Transparency and updated information 116 152 268 Total 366 458 824
Source: Primary Data
182 The above table clearly expresses that the reputation of stock exchanges plays a very important role for the groups of investors followed by number of stocks and transparency in the proceedings. Table - 5.43 presents the chi-square test value.
Table - 5.43: Chi-Square Tests for Reason of Preference Given to Stock Exchanges
Asymp. Sig. (2- Statistical Tool Value df sided)
Pearson Chi-Square 27.146 2 .000**
Likelihood Ratio 27.163 2 .000**
Linear-by-Linear Association 3.821 1 .051
No. of Valid Cases 507 -- -- Source: Primary Data; ** Significant at 0.01 level
Null Hypothesis
There is no association between reasons for preference of stock exchange and clusters of awareness of equity shares.
From the table of chi-square it is found that the null hypothesis is rejected, because the chi-square value = 27.146 and p = 0.000. It is further inferred that different reasons for preference of stock exchange arise due to retail investment.
5.17 Association between Experience in Dealing with Shares in Electronic Mode (demat) and Elements of Retail investment
A non-parametric test is brought upon the problem of finding the association between retail investment and investors dealing with electronic shares. The different groups of investors possess different opinions about dealing with electronic shares are presented in table - 5.44.
183 Table - 5.44: Experience in Dealing Shares through Electronic Mode (demat) and Cluster of Awareness on Elements of Retail investment
Clusters of Investors Experience in Dealing Shares through Total Electronic Mode (demat) 1 2
Yes 313 394 707
No 53 64 117
Total 366 458 824 Source: Primary Data
The above table indicates the maximum number investors are dealing shares through electronic mode and only a few investors do not deal shares through this mode. Table - 5.45 indicates the chi-square test value.
Table - 5.45: Chi-Square Tests Statistic Showing Experience in Dealing Shares with Electronic Mode (demat) and Cluster of Awareness on Elements of Retail investment
Asymp. Sig. Exact Sig. Exact Sig. Statistical Tool Value df (2-sided) (2-sided) (1-sided) Pearson Chi- .043 1 .836 -- -- Square Continuity of .011 1 .915 -- -- Correction Likelihood Ratio .043 1 .836 -- -- Fisher's Exact ------.841 .456 Test Linear-by-Linear .043 1 .836 -- -- Association No. of Valid 507 ------Cases Source: Primary Data
184 Null Hypothesis
There is no association between dealing with electronic shares and elements of retail investment.
From the table of chi-square test it is found that the chi-square value = 0.043 and p-value = -0.836. So the null hypothesis is accepted and it is concluded that there is no association between dealing with electronic shares and elements of retail investment. This shows that the investors feel that the electronic share is a convenient mode because it is introduced in equity shares by electronic advertisement in the scientific world and the economic use of the investments in equity shares which do not have any role to play with technological electronic advancement.
5.18 Sources of Information Available to Know about Retail investment
The different sources of information are useful to the investors to obtain updated information about retail investment and stock exchanges. They are able to set the information through newspapers, journals, TV channels, stock brokers, consultants, websites and friends and relatives. This analysis is aimed at finding which the most useful source of information is. The percentage of different sources information useful for the investors to deal with equity shares is presented in table - 5.46.
Table – 5.46 Percentage of Different Sources of Information to Know About Retail investment Preferred by Not preferred by Source investors investors (in %) (in %) 1. News papers 77.5 22.5
185 2. Journals 56.6 43.4 3. TV channels 66.5 33.5 4. Stock brokers 50.8 49.2 5. Consultants 39.4 60.6 6. Websites 35.3 64.7 7.company announcements 40.0 60.0 Source: Primary Data
The above table clearly ascertains that the investors are able to get proper information through newspapers (77.5%). So it is the most preferred source of information to know about retail investment. The next source of information is TV through which 66.5% investors are able to get more information about equity shares, followed by journals 56.6% and stock brokers 50.8%. Other sources are not that much significant. So it is concluded that the investors are able to get perfect information about equity shares through newspapers and TV.
5.19 Paired sample t-Test Carried out for the Factors of the equity investment.
Paired sample t-test is to identify the significant difference in the means among the five factors of the equity investment. This tool is also useful to identify the most popular factors of capital market reforms. The mean scores of each factor is presented in the table - 5.47, which is useful to identify the popular factor among the investors
Table – 5.47: Paired Samples Statistics for the Factors of the equity investment Std. Std. Error Pair Factors Mean N Deviation Mean Pair 1 Investment 4.1576 824 .58216 .02028 objectives Investment 4.0445 824 .56689 .01975 satisfaction Pair 2 Investment 4.1576 824 .58216 .02028 objectives Facility satisfaction 4.1675 824 .58990 .02055
186 Pair 3 Investment 4.1576 824 .58216 .02028 objectives Innovative 4.2031 824 .58191 .02027 measures Pair 4 Investment 4.1576 824 .58216 .02028 objectives Problems 3.8706 824 .55730 .01941 Pair 5 Investment 4.0445 824 .56689 .01975 satisfaction Facility satisfaction 4.1675 824 .58990 .02055 Pair 6 Investment 4.0445 824 .56689 .01975 satisfaction Innovative 4.2031 824 .58191 .02027 measures Pair 7 Investment 4.0445 824 .56689 .01975 satisfaction Problems 3.8706 824 .55730 .01941 Pair 8 Facility satisfaction 4.1675 824 .58990 .02055 Innovative 4.2031 824 .58191 .02027 measures Pair 9 Facility satisfaction 4.1675 824 .58990 .02055 Problems 3.8706 824 .55730 .01941 Pair 10 Innovative 4.2031 824 .58191 .02027 measures Problems 3.8706 824 .55730 .01941 Source: Primary Data
The above table indicates the mean values of the factors of capital market reforms. It ranges from the minimum mean value of 3.87 for problems to the maximum of 4.0 for innovative measures. The correlation table - 5.48 presents the relationship among all the factors which are inter linked.
Table – 5.48: Paired Samples Correlations for the Factors of the equity investment
Pair Factors N Correlation Sig. Pair 1 Investment objectives & 824 .645 .000**
187 Investment satisfaction Pair 2 Investment objectives & 824 .673 .000** Facility satisfaction Pair 3 Investment objectives & 824 .550 .000** Innovative measures Pair 4 Investment objectives & 824 .467 .000** Problems Pair 5 Investment satisfaction & 824 .556 .000** Facility satisfaction Pair 6 Investment satisfaction & 824 .429 .000** Innovative measures Pair 7 Investment satisfaction & 824 .533 .000** Problems Pair 8 Facility satisfaction & 824 .514 .000** Innovative measures Pair 9 Facility satisfaction & 824 .449 .000** Problems Pair 10 Innovative measures & 824 .323 .000** Problems Source: Primary Data; ** - Significant at 0.01 level
As observed from the above table, the five factors constitute the efficient capital market reforms and the correlation co-efficient are highly significant. So, all reforms are inter linked to accrue benefits to the investors. Paired sample t-test and their consequences are established in table - 5.49.
Table – 5.49: Paired Samples Test Values for the Factors of the equity investment
Pair Factors t df Sig. (2-tailed)
Pair 1 Investment objectives - 6.707 823 .000** Investment satisfaction
Pair 2 Investment objectives - -.598 823 .550 Facility satisfaction
188 Pair 3 Investment objectives - -2.364 823 .018* Innovative measures
Pair 4 Investment objectives - 14.000 823 .000** Problems
Pair 5 Investment satisfaction - -6.471 823 .000** Facility satisfaction
Pair 6 Investment satisfaction - -7.415 823 .000** Innovative measures
Pair 7 Investment satisfaction - 9.189 823 .000** Problems
Pair 8 Facility satisfaction - -1.769 823 .077 Innovative measures
Pair 9 Facility satisfaction - Problems 14.140 823 .000**
Pair 10 Innovative measures - 14.390 823 .000** Problems Source: Primary Data; ** - Significant at 0.01 level; * Significant at 0.05 level
The paired sample statistical table – 4.99 clearly reveals that the investors are very much attracted towards capital market with mean (4.20), followed by facility satisfaction (mean = 4.17), investment objectives (mean = 4.16), investment satisfaction (mean = 4.04) and finally problems (mean = 3.87). Though the means are different, paired sample t-test would check the statistically significant differences among them. It is also found that investment objectives and facility satisfaction are equally treated (t = 0.598) by the investors for their awareness. The educative and innovative measures are also equally popular among the investors (t = 1.769). So it is inferred that the investors are very much attracted by capital market after understanding the attractive financial sector reforms. The transparency about the performance of the companies issuing the shares and continuous monitoring of central government and the RBI raises the confidence among the investors besides the market risk. It is also found that the investors are willing to invest their hard earned money to have lucrative returns in the short span of time.
189 5.20 General Linear Multivariate Model Utilized to find out the Impact of the Equity investment and Various Elements of Capital Market Reforms
The general linear multivariate model provides a regression analysis and analysis of variance for multiple dependent variables. The independent variables are considerable as co-variants. In this study, the various elements of capital market reforms, general information in capital market, primary market reforms, secondary market reforms, reforms in instruments and their changes and finally reforms in financial parameters are considered as multiple dependent variables and the equity investments are considered as independent variables. The effect of independent variables on the dependent variables is depicted in table - 5.50.
Table – 5.50: Multivariate Tests (b) for the Impact of the Latest Reforms in Capital Market Hypothesis Factor Source Value F Error df Sig. df Intercept Pillai's Trace .224 46.864(a) 5.000 814.000 .000** Wilks' Lambda .776 46.864(a) 5.000 814.000 .000** Hotelling's Trace .288 46.864(a) 5.000 814.000 .000** Roy's Largest .288 46.864(a) 5.000 814.000 .000** Root Investment Pillai's Trace .151 28.889(a) 5.000 814.000 .000** objectives Wilks' Lambda .849 28.889(a) 5.000 814.000 .000** Hotelling's Trace .177 28.889(a) 5.000 814.000 .000** Roy's Largest .177 28.889(a) 5.000 814.000 .000** Root Investment Pillai's Trace .179 35.537(a) 5.000 814.000 .000** satisfaction Wilks' Lambda .821 35.537(a) 5.000 814.000 .000** Hotelling's Trace .218 35.537(a) 5.000 814.000 .000** Roy's Largest .218 35.537(a) 5.000 814.000 .000** Root Facility Pillai's Trace .051 8.823(a) 5.000 814.000 .000** satisfaction Wilks' Lambda .949 8.823(a) 5.000 814.000 .000**
190 Hotelling's Trace .054 8.823(a) 5.000 814.000 .000** Roy's Largest .054 8.823(a) 5.000 814.000 .000** Root Innovative Pillai's Trace .063 10.938(a) 5.000 814.000 .000** measures Wilks' Lambda .937 10.938(a) 5.000 814.000 .000** Hotelling's Trace .067 10.938(a) 5.000 814.000 .000** Roy's Largest .067 10.938(a) 5.000 814.000 .000** Root Problems Pillai's Trace .042 7.210(a) 5.000 814.000 .000** Wilks' Lambda .958 7.210(a) 5.000 814.000 .000** Hotelling's Trace .044 7.210(a) 5.000 814.000 .000** Roy's Largest .044 7.210(a) 5.000 814.000 .000** Root a Exact statistics b Design: Intercept+ Investment objectives+ Investment satisfaction+ Facility satisfaction+ Innovative measures + Problems Source: Primary Data; ** - Significant at 0.01 level; * Significant at 0.05 level
The above table reveals the existence of significant multivariate test for the dependent variables and the factors of capital market reforms. It is clear from the table that the F-values are significant in identifying the impact of independent variables.
The individual impact of five factors of capital market reforms on the dependent variables and probable significance are presented in the table - 5.51.
Table – 5.51: Impact of the equity investment objectives on the Element of investment decision Tests of Between-Subjects Effects Type III Independent Dependent Mean Sum of df F Sig. Variable Variable Square Squares Corrected General 107.477(a) 5 21.495 196.723 .000** Model information Company 82.097(b) 5 16.419 105.020 .000** management Details of the 111.103(c) 5 22.221 105.713 .000** present value Project details 111.547(d) 5 22.309 124.745 .000**
191 Type III Independent Dependent Mean Sum of df F Sig. Variable Variable Square Squares Financial 109.080(e) 5 21.816 130.945 .000** parameters Intercept General 11.698 1 11.698 107.056 .000** information Company 21.894 1 21.894 140.037 .000** management Details of the 7.009 1 7.009 33.344 .000** present value Project details 9.421 1 9.421 52.681 .000** Financial 11.025 1 11.025 66.176 .000** parameters Investment General 5.641 1 5.641 51.629 .000** objectives information Company 8.786 1 8.786 56.194 .000** management Details of the 2.395 1 2.395 11.393 .001** present value Project details 14.654 1 14.654 81.942 .000** Financial 5.840 1 5.840 35.053 .000** parameters Investment General 9.418 1 9.418 86.192 .000** satisfaction information Company .617 1 .617 3.944 .047* management Details of the 11.218 1 11.218 53.371 .000** present value Project details 5.703 1 5.703 31.888 .000** Financial 16.841 1 16.841 101.083 .000** parameters Facility General 2.812 1 2.812 25.733 .000** satisfaction information Company 3.612 1 3.612 23.104 .000** management Details of the 2.368 1 2.368 11.266 .001** present value Project details .216 1 .216 1.206 .272
192 Type III Independent Dependent Mean Sum of df F Sig. Variable Variable Square Squares Financial 1.016 1 1.016 6.101 .014* parameters Innovative General 4.709 1 4.709 43.097 .000** measures information Company .913 1 .913 5.837 .016* management Details of the 3.618 1 3.618 17.212 .000** present value Project details .598 1 .598 3.344 .068 Financial .372 1 .372 2.236 .135 parameters Problems General .574 1 .574 5.257 .022* information Company 1.123 1 1.123 7.185 .008** management Details of the 1.403 1 1.403 6.675 .010** present value Project details 1.683 1 1.683 9.411 .002** Financial .135 1 .135 .809 .369 parameters Error General 89.381 818 .109 -- -- information Company 127.891 818 .156 -- -- management Details of the 171.941 818 .210 -- -- present value Project details 146.290 818 .179 -- -- Financial 136.282 818 .167 -- -- parameters Total General 14423.703 824 ------information Company 14930.313 824 ------management Details of the 14276.432 824 ------present value Project details 14204.560 824 ------
193 Type III Independent Dependent Mean Sum of df F Sig. Variable Variable Square Squares Financial 14190.440 824 ------parameters Corrected General 196.858 823 ------Total information Company 209.988 823 ------management Details of the 283.044 823 ------present value Project details 257.837 823 ------Financial 245.362 823 ------parameters a R Squared = .546 (Adjusted R Squared = .543) b R Squared = .391 (Adjusted R Squared = .387) c R Squared = .393 (Adjusted R Squared = .389) d R Squared = .433 (Adjusted R Squared = .429) e R Squared = .445 (Adjusted R Squared = .441) Source: Primary Data; ** - Significant at 0.01 level; * Significant at 0.05 level
The following observations have been made from the above table. The independent variables of the equity investment explain the total variance of 54.6%, 39.1%, 39.3%, 43.3% and 44.5% respectively. These variances are statistically significant to state that the equity investment increases the number of investors in primary market and secondary market.
The table of tests of between – subtest effects clearly reveals that the investment objectives and the latest developments have impact on general information (F = 51.629), company management (F = 56.194), details of the present value (F = 11.393), project details (F = 81.942) and financial parameters (F = 35.053). Similarly the investment satisfaction has an impact on all the elements of reforms in capital market.
Facility satisfaction does not create an impact on instruments and their changes. Innovative measures have good impact on all elements of capital reforms, except financial parameters. Problems create deep impact on capital market reforms, primary
194 market reforms secondary market reforms, instruments and their changes, but it does not predict financial parameters. So, it is summarised that the equity investment have predicted good impact on reforms in capital market. Collectively the equity investments aim at reforming primary and secondary market. Positive changes in the instrument and better returns to the investors prevail in the equity market.
5.21 Analysis of Variance carried out for Investors Preference of Investment when better return is received
Analysis of variance is a useful tool to identify the variance among the variables. In this study, the preference to investments, shares, real estate, gold, deposit in bank, government bonds and purchasing of agricultural lands are considered for their significant difference in variance and the grouping variables for the analysis in the cluster of investors. Table - 5.52 presents the variance in group means of factors of capital market reforms with respect to clusters of investors and exhibits the significant variance in group means of various investment options.
Table – 5.52: ANOVA for Group Means of Investment Options
Dependent Sum of Mean Group df F Sig. Variable Squares Square Investment in Between Share and Groups 374.254 2 187.127 .699 .497 Debentures Within 219775.397 821 267.692 -- -- Groups Total 220149.650 823 ------Investment in Between 2441.163 2 1220.582 5.845 .003** Real Estate Groups Within 171434.196 821 208.811 -- -- Groups Total 173875.359 823 ------Investment in Between 2461.048 2 1230.524 8.558 .000** Gold Groups
195 Within 118043.568 821 143.780 -- -- Groups Total 120504.617 823 ------Investment in Between 111.702 2 55.851 .325 .723 Bank Groups Within 141021.793 821 171.768 -- -- Groups Total 141133.495 823 ------Investment in Between Government Groups 5596.028 2 2798.014 20.266 .000** Bonds Within 113350.058 821 138.063 -- -- Groups Total 118946.086 823 ------Investment in Between Purchasing of Groups 989.789 2 494.894 8.894 .000** Agricultural Lands Within 45682.366 821 55.642 -- -- Groups Total 46672.154 823 ------Source: Primary Data; ** - Significant at 0.01 level; * Significant at 0.05 level
It is found from the above table that there is a significant variance in investment in real estate (F = 5.845), investment in gold (F = 8.558), investment in Government bonds (F = 20.27), and finally investment in of agricultural lands (F = 8.894).
On the whole it is concluded that the investors’ behaviour changes with regard to clusters of equity investment. As the clusters of investors are based on their interest and awareness of capital market, it can be profoundly stated that the investors are also explore the avenues like real estate, gold investment and government bonds to get more returns with less risk.
5.22 Correlation Analysis Carried out for the Number of Years in Dealing with equity market investment
196 Karl Pearson’s co-efficient of correlation is a statistical tool used to establish the relationship between the two variables. There are two types of correlations, one is positive correlation and the other one is negative correlation.
Table – 5.53 establishes the co-efficient of correlation between the factors of the equity investment and the number of years in dealing with capital market.
Table - 5.53: Coefficient of Correlations for Number of Years Dealing in Capital Market Variables Co-efficient Significance 1. Investment objectives .008 0.816 2. Investment satisfaction -.004 0.911 3. Facility satisfaction -.064 0.068 4. Innovative measures -.027 0.439 5. Problems -.050 0.153 Source: Primary Data
After a close scrutiny of the above table, it is concluded that there is no significant relationship between the number of years in dealing with capital market and variably of the equity investment, i.e., some investors are continuously investing in capital markets with their perception about the developments in capital market. They feel it is an advantage for their investment.
5.23 Percentage of Savings in Capital Market with regard to equity investment
The group means and their significant difference between them with respect to percentage of savings is presented in table - 5.54.
Table – 5.54: ANOVA for the Latest Reforms Based on Percentage of Savings Independent Sum of Mean Group Df F Sig. Variable Squares Square Investment Between Groups 11.380 3 3.793 11.627 .000** objectives Within Groups 267.540 820 .326 -- -- Total 278.920 823 ------Investment Between Groups .464 3 .155 .481 .696
197 satisfaction Within Groups 264.015 820 .322 -- -- Total 264.480 823 ------Facility Between Groups 7.836 3 2.612 7.689 .000** satisfaction Within Groups 278.552 820 .340 -- -- Total 286.388 823 ------Innovative Between Groups 1.545 3 .515 1.523 .207 measures Within Groups 277.141 820 .338 -- -- Total 278.686 823 ------Problems Between Groups 1.860 3 .620 2.003 .112 Within Groups 253.749 820 .309 -- -- Total 255.609 823 ------Source: Primary Data; ** - Significant at 0.01 level; *Significant at 0.05level The above table clearly reveals that the latest investment objectives (F=11.627) and facility satisfaction (F=7.689) differ in their means significantly. So, it can be inferred that investment objectives and facility satisfaction severely affect the investor’s decision to decide the percentage of investment in share market.
5.24 Linear Multiple Regression Analysis carried out on Elements of Retail investment
Linear multiple regression analysis is a multivariate statistical tool used to identify the impact of independent variables on dependent variables. It also explores the percentage of variance of independent variables on dependent variable. The ANOVA table exhibited in this analysis explains fitness of regression using independent variables and the co-efficient table elaborates about the individual impact on every independent variable in the study. The demographic variables of investors’ viz. Age, Gender, Marital Status, Education, Occupation, Income, Nature of Family, Number of Dependents, House Ownership and percentage of investment are considered as independent variables. Each element of capital investments is taken as a dependent variable. This analysis is going to be performed cluster wise, using the clusters of awareness on retail investment.
198 (a) Cluster wise Linear Multiple Regression Analysis for General informations
In cluster, 1 the explanation of independent demographic variables about dependent variable general informations is presented in table - 5.55.
Table - 5.55: Variance of Independent Variable on General informations and Cluster 1 (b)
Adjusted R Std. Error of Model R R Square Square the Estimate
1 .341(a) .116 .091 .38026 a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Clusters of investments 1 Source: Primary Data
As seen in the above table in the case of moderate cluster the independent variables explain 11.6% variance of dependent variables.
The significance of the regression model is presented in the table - 5.56.
Table – 5.56: ANOVA (b, c) for General informations and Cluster 1
Sum of Mean Model Source df F Sig. Squares Square
1 Regression 6.588 10 .659 4.556 .000(a)**
Residual 50.176 347 .145 -- --
Total 56.763 357 ------a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Dependent Variable: General informations c. Clusters of investments 1
199 Source: Primary Data; ** Significant at 0.01 level
From the above table it is found that the regression significantly fits (F=4.556).The individual explanations of each demographic variable and its respective t- values are presented in table - 5.57.
Table - 5.57: Coefficients (a, b) of General informations and Cluster 1
Un- Standardized Independent standardized Model Coefficients t Sig. Variables Coefficients
Std. B Beta Error 1 (Constant) 3.240 .190 -- 17.037 .000** Age .124 .032 .234 3.927 .000** Gender .307 .082 .193 3.720 .000** Martial Status .036 .047 .042 .765 .445 Educational .022 .020 .063 1.098 .273 Qualification Occupation -.025 .020 -.074 -1.249 .213 Annual .069 .026 .155 2.654 .008** Income Family -.030 .045 -.037 -.669 .504 Dependents -.008 .011 -.038 -.704 .482 House -.065 .054 -.064 -1.192 .234 Ownership Percentage of -.109 .045 -.135 -2.440 .015* investment a. Dependent Variable: General informations; b . Clusters of investments 1 Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
In this moderate awareness cluster age (t=3.927), gender (t=3.720), annual income (t=2.654), and vehicle ownership (t=2.440) of investors pave the way to know about general capital investments. So on the whole it is concluded that the demographic variables of investors are useful for them to identify the general retail investment.
200 Table - 5.58: Variance of Independent Variable on General informations and Cluster 2 (b)
Adjusted Std. Error of Model R R. Square R. Square the Estimate
1 .298(a) .089 .068 .26307 a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Clusters of investments 2 Source: Primary Data
In the case of high awareness cluster the independent variables explain 8.9% variation of dependent variable. It is found in the above table. The significant fit of the regression model is presented in the table - 5.58.
Table - 5.59: ANOVA (b, c) for General informations and Cluster 2
Sum of Mean Model Sources df F Sig. Squares Square
1 Regression 3.000 10 .300 4.335 .000(a)**
Residual 30.796 445 .069 -- --
Total 33.796 455 ------a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Dependent Variable: General informations c. Clusters of investments 2
Source: Primary Data; ** Significant at 0.01 level
From the table – 5.59 it is identified that the regression fits significantly (F=4.335). The individual explanations of each demographic variable and their respective t- values are presented in table - 4.67.
In cluster 2 the explanation of independent demographic variables about dependent variable general informations is presented in the table - 5.60.
201 Table – 5.60: Coefficients (a, b) of General informations and Cluster 2
Un-standardized Standardized Independent Coefficients Coefficients Model t Sig. Variable Std. B Beta Error 1 (Constant) 4.606 .142 -- 32.518 .000** Age .079 .024 .183 3.360 .001** Gender -.054 .047 -.054 -1.166 .244 Martial Status .084 .034 .125 2.463 .014* Educational -.022 .014 -.076 -1.577 .116 Qualification Occupation -.038 .013 -.137 -2.830 .005** Annual -.001 .016 -.004 -.082 .935 Income Family .016 .027 .028 .574 .566
Dependents -.028 .007 -.181 -3.507 .000** House -.073 .041 -.083 -1.763 .079 Ownership Percentage of -.052 .025 -.106 -2.071 .039* investment a. Dependent Variable: General informations b. Clusters of investments 2 Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the co-efficient table it is found that the high awareness of investors is achieved through their age (t=3.360) marital status (t=2.463) occupation (t=2.83) no. of dependents and percentage of investment. In cluster 2 the demographic variables distinguish the investors from high awareness on retail investment.
202 (b) Cluster-wise Linear Multiple Regression Analysis for Company management
In cluster 1, the explanation of independent demographic variables about dependent variable Company management is presented in table - 5.61.
Table - 5.61: Variance of Independent Variable for Company management and Cluster 1 (b)
Adjusted R Std. Error of the Model R R Square Square Estimate
1 .252(a) .064 .037 .41747 a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family, Annual Income, Age. b Clusters of investments 1 Source: Primary Data
As seen from the above table the demographic variables of investors with moderate awareness on equity shares explains 6.4% variance of the dependent variable. The significant fit of the regression model is presented in table - 5.62.
Table - 5.62: ANOVA (b, c) for Company management and Cluster 1
Sum of Mean Model Source df F Sig. Squares Square
1 Regression 4.118 10 .412 2.363 .010(a)*
Residual 60.475 347 .174 -- --
Total 64.594 357 ------a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Dependent Variable: Company management c. Clusters of investments 1 Source: Primary Data; * Significant at 0.05 level
203 From the above table, the significant regression fit is evident (F=2.363). The individual impact of each variable is presented in table - 5.63.
Table - 5.63: Coefficients (a, b) of Company management and Cluster 1
Unstandardized Standardized Independent Coefficients Coefficients Model t Sig. Variable Std. B Beta Error 1 (Constant) 3.356 .209 -- 16.075 .000** Age -.013 .035 -.022 -.366 .715 Gender .086 .091 .051 .950 .343 Martial Status .025 .052 .028 .488 .626 Educational -.005 .022 -.012 -.211 .833 Qualification
Occupation -.016 .022 -.043 -.707 .480
Annual Income .052 .029 .109 1.809 .071
Family .097 .049 .113 1.979 .049*
Dependents .009 .012 .042 .757 .450 House .038 .059 .035 .633 .527 Ownership Percentage of .127 .049 .149 2.602 .010** investment a. Dependent Variable: Company management; b. Clusters of investments 1 Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
As observed from the above table the demographic variables of investors with moderate awareness on equity shares explain 6.4% variance of the dependent variable with good regression fit (F=2.363). In this moderate awareness group of investors, nature of family (t=1.979) and vehicle ownership help them to acquire knowledge about company management. It is concluded that the nature of family decides the investor’s awareness on the company management in cluster 1.
In cluster 2 the explanation of independent demographic variables about dependent variable company management is presented in table - 5.64.
204 Table - 5.64: Variance of Independent Variable for Company management and Cluster 2 (b)
Adjusted Std. Error of Model R R Square R Square the Estimate
1 .269(a) .072 .051 .36060 a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b Clusters of investments 2 Source: Primary Data
It is clear from the above table that in the high awareness on equity shares reform clusters, the demographic variables of investors explain 7.2% of total variation on company management. The significant fit of the regression model is presented in the table - 5.65.
Table - 5.65: ANOVA (b, c) for Company management and Cluster 2
Sum of Mean Model Source df F Sig. Squares Square 1 Regression 4.498 10 .450 3.460 .000(a)** Residual 57.863 445 .130 -- -- Total 62.361 455 ------a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Dependent Variable: Company management; c Clusters of investments 2 Source: Primary Data; ** Significant at 0.01 level
From the above table, it is found that the regression fits significantly with F=3.460. The individual explanations of each demographic variable and its respective t- value are indicated in table - 5.66.
205 Table - 5.66: Coefficients (a, b) for Company management and Cluster 2 Un- Standardized standardized Independent Coefficients t Sig. Model Coefficients Variable Std. B Beta Error 1 (Constant) 4.757 .194 -- 24.500 .000** Age .021 .032 .036 .663 .508 Gender -.032 .064 -.024 -.502 .616 Martial Status .034 .047 .037 .724 .469 Educational -.001 .019 -.004 -.073 .942 Qualification Occupation -.035 .018 -.094 -1.912 .057 Annual Income .055 .021 .138 2.556 .011* Family -.045 .038 -.058 -1.191 .234 Dependents -.033 .010 -.157 -3.290 .001** House .017 .057 .014 .301 .764 Ownership Percentage of -.143 .034 -.215 -4.159 .000** investment a. Dependent Variable: Company management; b. Clusters of investments2; Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05level
It is understood from the above table that annual income (t=2.556), no of dependents (t=3.290), and vehicle ownership (t=4.159) are useful for the investors to know the company management. In cluster 2, it is concluded that income, vehicle ownership and number of dependents explain the awareness of investors on company management. c) Cluster-wise Linear Multiple Regression Analysis for Details of present values
In cluster 1, the explanation of independent demographic variables about dependent variable Details of present values is presented in table - 5.67.
206 Table - 5.67: Variance of Independent Variable on Details of present values Cluster 1 (b)
Adjusted Std. Error of Model R R Square R Square the Estimate
1 .297(a) .088 .062 .53165 a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b Clusters of investments 1 Source: Primary Data
It is deduced from the above table that in the case of moderate awareness on capital reform clusters, the independent variables explain 8.8% variance of details of present values. The significant fit of the regression model is presented in table - 5.68.
Table - 5.68: ANOVA (b, c) for Details of present values and Cluster 1
Sum of Mean Model Source df F Sig. Squares Square 1 Regression 9.505 10 .951 3.363 .000(a)** Residual 98.081 347 .283 -- --
Total 107.587 357 ------a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Dependent Variable: Details of present values; c. Clusters of investments 1
Source: Primary Data; ** Significant at 0.01 level
From the above table, it is found that the regression fits significantly with F=3.363. The individual explanations of each demographic variable and its respective t- value are presented in table - 5.69.
207 Table - 5.69: Coefficients (a, b) of Details of present values and Cluster 1
Un-standardized Standardized Independent Coefficients Coefficients Model t Sig. Variable Std. B Beta Error
1 (Constant) 3.476 .266 -- 13.070 .000**
Age -.088 .044 -.121 -1.994 .047*
Gender .177 .115 .081 1.539 .125
Martial Status .090 .066 .077 1.375 .170
Educational .033 .028 .067 1.155 .249 Qualification Occupation -.033 .029 -.069 -1.141 .255 Annual .041 .036 .067 1.124 .262 Income Family .192 .063 .173 3.071 .002**
Dependents .010 .016 .034 .627 .531
House -.195 .076 -.139 -2.576 .010** Ownership
Percentage of -.029 .062 -.026 -.463 .644 investment a. Dependent Variable: Details of present values; b. Clusters of investments 1; Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
It is inferred from the above table that in this cluster, age (t=1.994), nature of family (t=3.071), and house ownership (t=2.576) create a good impact on details of present values. So it is concluded that in moderate awareness, clusters, the secondary market awareness can be observed by the investors using their age, nature of family and house ownership.
In cluster 2 the explanation of independent demographic variables about dependent variable Details of present values is given in the table - 5.70.
208 Table - 5.70: Variance of Independent Variable on Details of present values and Cluster 2 (b)
Adjusted R Std. Error of the Model R R Square Square Estimate
1 .157(a) .025 .003 .41696 a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Clusters of investments 2
Source: Primary Data
As per the above table the demographic variables explain 2.5% of the total variance. The significant fit of the regression model is presented in table - 5.71.
Table - 5.71: ANOVA (b, c) for Details of present values and Cluster 2
Sum of Mean Model Source df F Sig. Squares Square 1 Regression 1.956 10 .196 1.125 .341(a)
Residual 77.365 445 .174 -- --
Total 79.321 455 ------a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Dependent Variable: Details of present values; c. Clusters of investments 2 Source: Primary Data
The above table clearly reveals that the regression is not significant. The individual explanations of each demographic variable and its respective t-value are presented in table - 5.72.
Table - 5.72: Coefficients (a, b) for Details of present values and Cluster 2 Un-standardized Standardized Independent Model Coefficients Coefficients t Sig. Variable Std. B Beta Error
209 1 (Constant) 4.219 .224 -- 18.793 .000** Age .076 .037 .114 2.017 .044* Gender -.029 .074 -.019 -.390 .697 Martial Status .017 .054 .017 .320 .749 Educational .007 .022 .017 .340 .734 Qualification
Occupation -.003 .021 -.007 -.130 .897
Annual Income -.013 .025 -.028 -.506 .613
Family .056 .043 .064 1.282 .201
Dependents -.008 .012 -.034 -.691 .490 House -.069 .066 -.051 -1.045 .296 Ownership Percentage of .030 .040 .040 .757 .449 investment a Dependent Variable: Details of present values b Clusters of investments 2 Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
The investors with high awareness on retail investment are able to initiate more ideas of details of present values through age (t=2.017), alone. The regression does not fit significantly and the variance percentage is 2.5 only. It is found that in order to have high awareness age alone helps the investors. All these have been observed from table - 5.72.
(d) Cluster-wise Linear Multiple Regression Analysis for Project details and their Changes
In cluster 1 the explanation of independent demographic variables about dependent variable change of project details is presented in table - 5.73.
210 Table - 5.73 Variance of Independent Variable on Project details and their Changes and Cluster 1 (b)
Adjusted Std. Error of Model R R Square R Square the Estimate
1 .268(a) .072 .045 .47031
a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b Clusters of investments 1 Source: Primary Data
According to the above table in moderate awareness cluster, the demographic variables of investors explain 7.2% variance on dependent variables. The significant fit of the regression model is presented in table - 5.74.
Table - 5.74: ANOVA (b, c) for Project details and their Changes and Cluster 1 Sum of Mean Model Source Df F Sig. Squares Square
1 Regression .004(a)* 5.933 10 .593 2.682 *
Residual 76.753 347 .221 -- --
Total 82.686 357 ------a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Dependent Variable: Change of project details c. Clusters of investments 1
Source: Primary Data; ** Significant at 0.01 level
From the above table it is found that the regression fits significantly with F=2.682.The individual explanations of each demographic variable and its respective t- value are presented in table - 5.75.
211 Table – 5.75: Coefficients (a, b) for Project details and their Changes and Cluster 1 Standardize Un-standardized Independent d Model Coefficients t Sig. Variable Coefficients
Std. B Beta Error
1 (Constant) 3.658 .235 -- 15.549 .000**
Age -.072 .039 -.113 -1.849 .065
Gender .269 .102 .140 2.641 .009**
Martial Status -.022 .058 -.021 -.375 .708
Educational -.027 .025 -.064 -1.083 .279 Qualification
Occupation -.004 .025 -.009 -.151 .880
Annual Income .097 .032 .179 2.998 .003**
Family .062 .055 .064 1.127 .260
Dependents -.007 .014 -.028 -.504 .615
House -.133 .067 -.108 -1.981 .048* Ownership
Percentage of -.036 .055 -.037 -.658 .511 investment a Dependent Variable: Change of project details b Clusters of investments 1 Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
It is understood from the table that in this cluster, gender (t=2.641), income (t=2.998) ownership of the house (t=1.981) explain the awareness of investors on
212 changes of project details. So it is concluded that gender, income and ownership of the house decide their high awareness on details of present values.
In cluster 2 the explanation of independent demographic variables about dependent variable change of project details is presented in the table - 5.76.
Table - 5.76: Variance of Independent Variable on Project details and their Changes and Cluster 2 (b)
Adjusted R Std. Error of the Model R R Square Square Estimate
1 .191(a) .037 .015 .37355 a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b Clusters of investments 2
Source: Primary Data
As exhibited in the above table for high awareness cluster, the regression does not fit significantly (f=1.690) and very poor 3.7% variance is explained by independent variables on dependent variables The significant fit of the regression model is presented in table - 5.77.
Table - 5.77: ANOVA (b, c) for Project details and their Changes and Cluster 2 Sum of Mean Model Source df F Sig. Squares Square
1 Regression 2.358 10 .236 1.690 .080(a)
Residual 62.095 445 .140 -- --
Total 64.453 455 ------a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b Dependent Variable: Change of project details c Clusters of investments 2
Source: Primary Data
213
The above table clearly reveals that the regression is not significant. The individual explanations of each demographic variable and its respective t-value are presented in table - 5.78.
Table - 5.78 Coefficients (a, b) for Project details and their Changes Cluster 2 Un- Standardized standardized Independent Coefficients Model Coefficients t Sig. Variable Std. B Beta Error 1 (Constant) 4.100 .201 -- 20.388 .000**
Age .054 .034 .090 1.599 .111
Gender .028 .066 .020 .421 .674
Martial Status .099 .048 .106 2.037 .042*
Educational -.020 .020 -.052 -1.044 .297 Qualification
Occupation -.024 .019 -.063 -1.257 .209
Annual Income .047 .022 .116 2.110 .035*
Family .071 .039 .091 1.836 .067
Dependents -.013 .010 -.061 -1.248 .213
House Ownership .052 .059 .043 .893 .372
Percentage of -.052 .036 -.077 -1.450 .148 investment a Dependent Variable: Change of project details b Clusters of investments 2
214 Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
It is inferred from the above table that in this cluster, the marital status (t=2.037) and income (t=2.110) create an impact of dependent variables. The marital status and income of the investors decide them to possess moderate awareness on change of project details
(e) Cluster-wise Linear Multiple Regression Analysis for Financial parameters
In cluster 1 the explanation of independent demographic variables about dependent variable financial parameters is presented in the table – 5.79.
Table - 5.79: Variance of Independent Variable on Financial parameters and Cluster 1 (b) Adjusted R Std. Error of the Model R R Square Square Estimate 1 .412(a) .170 .146 .39757 a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Clusters of investments 1 Source: Primary Data
It is clear from the above table that in the case of moderate awareness on capital reform with 17% variance in financial parameters. The significant fit of the regression model is presented in table - 5.80.
Table - 5.80: ANOVA (b, c) for Financial parameters for Cluster 1 Sum of Mean Model Source Df F Sig. Squares Square 1 Regression 11.241 10 1.124 7.112 .000(a)** Residual 54.847 347 .158 -- -- Total 66.088 357 ------a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Dependent Variable: financial parameters c. Clusters of investments 1 Source: Primary Data; ** Significant at 0.01 level
215 From the above table it is found that the regression fits significantly with F=7.112. The individual explanation of each demographic variable and its respective t- value are presented in table - 5.81.
Table - 5.81: Coefficients (a, b) for Financial parameters and Cluster 1
Unstandardized Standardized Model Independent Coefficients Coefficients t Sig. Variable Std. B Beta Error 1 (Constant) 3.995 .199 -- 20.091 .000** Age .039 .033 .068 1.177 .240 Gender -.025 .086 -.015 -.295 .768 Martial Status .202 .049 .219 4.106 .000** Educational .032 .021 .085 1.532 .126 Qualification Occupation -.063 .021 -.171 -2.965 .003** Annual -.078 .027 -.161 -2.846 .005** Income Family -.085 .047 -.097 -1.810 .071
Dependents -.015 .012 -.069 -1.311 .191 House -.262 .057 -.239 -4.624 .000** Ownership Percentage of .038 .047 .044 .822 .412 investment a Dependent Variable: financial parameters b Clusters of investments 1 Source: Primary Data; ** Significant at 0.01 level
It is found from the above table that in this cluster the marital status (t=4.106), occupation (t=2.965), income (t=2.846) and house ownership (t=4.624) of investors pave the way for them to understand the financial parameters. The moderate awareness on financial parameters can be obtained through the marital status, occupation, income and house ownership of the investors.
In cluster 2, the explanation of independent demographic variables about dependent variable financial parameters is presented in table - 5.82.
216 Table - 5.82: Variance of Independent Variable on Financial parameters and Cluster 2 (b)
Adjusted Std. Error of Model R R Square R Square the Estimate
1 .200(a) .040 .018 .30988 a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Clusters of investments 2 Source: Primary Data
The significant fit of the regression model is presented in table - 5.83.
Table - 5.83: ANOVA (b, c) for Financial parameters for Cluster 2
Sum of Mean Model Source df F Sig. Squares Square
1 Regression 1.783 10 .178 1.856 .049(a)*
Residual 42.732 445 .096 -- --
Total 44.515 455 ------a. Predictors: (Constant), Vehicle Ownership, Occupation, House Ownership Gender, Marital Status, Dependents, Qualification, Nature of the Family Annual Income, Age. b. Dependent Variable: financial parameters c. Clusters of investments 2 Source: Primary Data; * Significant at 0.05 level
Tables 5.82 and 5.83 clearly reveals that in the highly awareness on capital reform cluster, 4% of the variance of dependent variables is explained by the independent variables. The individual explanation of each demographic variable and its respective t- value are presented in table - 5.84.
217 Table - 5.84: Coefficients (a, b) for Financial parameters and Cluster 2
Un-standardized Standardized Independent Coefficients Coefficients Model t Sig. Variables Std. B Beta Error
1 (Constant) 4.487 .167 -- 26.896 .000**
Age -.002 .028 -.003 -.057 .955
Gender .087 .055 .076 1.586 .113
Martial Status .003 .040 .004 .083 .934
Educational -.017 .016 -.052 -1.057 .291 Qualification Occupation -.032 .016 -.101 -2.020 .044* Annual Income .031 .018 .091 1.660 .098
Family .009 .032 .013 .274 .785
Dependents -.023 .009 -.131 -2.693 .007**
House .005 .049 .005 .099 .922 Ownership
Percentage of -.005 .030 -.009 -.176 .860 investment a. Dependent Variable: return in investment b. Clusters of investments 2 Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
It is found from the above table that the occupation (t=2.020), and no of dependents (t=2.693) are the two demographic variables of investors creating a good impact on return in investment. The high awareness on financial parameters of investors is decided by their occupation and the number of dependents in the family.
218 5.25 The Multivariate General Linear Analysis for returns Received and
Preference of Investment
In this analysis the retail investment and its impact on different avenues of investment are explored using multivariate general linear model. The elements of retail investment are taken as independent variables and the percentage of investment in different avenues are considered as dependent variables. The individual impact of retail investment on the investment options is explained in the table - 5.85.
Table - 5.85: Impact of Retail investment Preference of returns Amount Received and Tests of Between-Subjects Effects
Type III Dependent Mean Source Sum of df F Sig. Variable Square Squares Corrected Investment in 5735.221(a) 5 1147.044 4.376 .001** Model shares Investment in 5598.794(b) 5 1119.759 5.443 .000** real estate Investment in 6797.038(c) 5 1359.408 9.779 .000** Gold Investment in 3116.403(d) 5 623.281 3.694 .003** bank Investment in 2023.126(e) 5 404.625 2.831 .015* Govt bonds Investment in 2741.143(f) 5 548.229 10.208 .000** lands Intercept Investment in 1241.456 1 1241.456 4.736 .030* shares Investment in 2.489 1 2.489 .012 .912 real estate Investment in 10447.977 1 10447.977 75.162 .000** Gold
219 Type III Dependent Mean Source Sum of df F Sig. Variable Square Squares Investment in 10893.213 1 10893.213 64.562 .000** bank Investment in 21.241 1 21.241 .149 .700 Govt bonds Investment in 1514.569 1 1514.569 28.201 .000** lands General Investment in 2322.564 1 2322.564 8.861 .003** informations shares Investment in 2844.654 1 2844.654 13.828 .000** real estate Investment in 2342.439 1 2342.439 16.851 .000** Gold Investment in 1011.898 1 1011.898 5.997 .015* bank Investment in 107.061 1 107.061 .749 .387 Govt bonds Investment in 293.177 1 293.177 5.459 .020* lands Company Investment in 13.601 1 13.601 .052 .820 management shares Investment in 101.959 1 101.959 .496 .482 real estate Investment in 291.202 1 291.202 2.095 .148 Gold Investment in 337.034 1 337.034 1.998 .158 bank Investment in 692.267 1 692.267 4.843 .028* Govt bonds Investment in 26.321 1 26.321 .490 .484 lands
220 Type III Dependent Mean Source Sum of df F Sig. Variable Square Squares Details of Investment in 77.867 1 77.867 .297 .586 present values shares Investment in 158.547 1 158.547 .771 .380 real estate Investment in 864.583 1 864.583 6.220 .013* Gold Investment in 8.884 1 8.884 .053 .819 bank Investment in 180.865 1 180.865 1.265 .261 Govt bonds Investment in 1047.146 1 1047.146 19.498 .000** lands Project details Investment in and their shares 1.543 1 1.543 .006 .939 Changes Investment in 492.994 1 492.994 2.396 .122 real estate Investment in 28.536 1 28.536 .205 .651 Gold Investment in 7.476 1 7.476 .044 .833 bank Investment in 261.607 1 261.607 1.830 .176 Govt bonds Investment in 403.619 1 403.619 7.515 .006** lands Financial Investment in 89.543 1 89.543 .342 .559 parameters shares Investment in 16.320 1 16.320 .079 .778 real estate Investment in 1.353 1 1.353 .010 .921 Gold
221 Type III Dependent Mean Source Sum of df F Sig. Variable Square Squares Investment in 43.005 1 43.005 .255 .614 bank Investment in 114.515 1 114.515 .801 .371 Govt bonds Investment in 383.380 1 383.380 7.139 .008** lands Error Investment in 214414.429 818 262.120 -- -- shares Investment in 168276.565 818 205.717 -- -- real estate Investment in 113707.579 818 139.007 -- -- Gold Investment in 138017.093 818 168.725 -- -- bank Investment in 116922.960 818 142.938 -- -- Govt bonds Investment in 43931.011 818 53.705 -- -- lands Total Investment in 1169704.000 507 ------shares Investment in 434980.000 507 ------real estate Investment in 268580.000 507 ------Gold Investment in 446400.000 507 ------bank Investment in 206525.000 507 ------Govt bonds Investment in 57969.000 507 ------lands
222 Type III Dependent Mean Source Sum of df F Sig. Variable Square Squares Corrected Investment in 220149.650 506 ------Total shares Investment in 173875.359 506 ------real estate Investment in 120504.617 506 ------Gold Investment in 141133.495 506 ------bank Investment in 118946.086 506 ------Govt bonds Investment in 46672.154 506 ------lands a. R Squared = .026 (Adjusted R Squared = .020); b. R Squared = .032 (Adjusted R Squared = .026) c. R Squared = .056 (Adjusted R Squared = .051); d. R Squared = .022 (Adjusted R Squared = .016) e. R Squared = .017 (Adjusted R Squared = .011); f. R Squared = .059 (Adjusted R Squared = .053) Source: Primary Data; ** Significant at 0.01 level; * Significant at 0.05 level
From the above table, it is clear that general capital investments include the investors’ investment in shares (F=8.861), real estate (F=13.828), gold (F=16.851), bank deposits (F=5.997) and in agricultural lands (F=5.459). It is also ascertained that the retail investment explain the investment options as 2.6%, 3.2%, 5.6%, 2.2%, 1.7% and 5.9% respectively which is not statistically significant. So due to general capital investments investors show good enthusiasm for various investment avenues. Company management make the investors to go for investing in Government bonds (F=4.843). Details of present values compel the investors to invest in gold (F=6.220) and in lands (F=19.498). Change in project details forces the investors to go in for own lands (F=7.515) and similarly financial parameters directs the investors to invest in lands (F=7.139). On the whole, it is concluded that the capital investments open fascinating vistas for investment of investors.
223 The demographic variables of investors in some way affect their awareness of retail investment.
5.26 Impact of Demographic Variables on the investment objectives, decision and satisfaction.
The general multivariate linear model is used to find the impact of independent demographic variables such as age, gender, marital status, educational qualification, occupation, annual income, family members, dependents, house ownership and vehicle ownership on the dependent variables factors of latest developments in capital market. The individual impacts of all type of the demographic variables are presented in table - 5.86.
Table – 5.86: Impact of Demographic Variables on the investment objectives, decision and satisfaction-Tests of Between-Subjects Effects
Type III Independent Dependent Mean Sum of df F Sig. Variable Variable Square Squares Corrected Investment 2703.389(a) 10 270.339 14.383 .000** Model objectives Investment 688.234(b) 10 68.823 6.372 .000** satisfaction Facility 559.123(c) 10 55.912 11.229 .000** satisfaction Innovative 208.500(d) 10 20.850 7.377 .000** measures Problems 411.062(e) 10 41.106 5.610 .000** Intercept Investment 5784.901 1 5784.901 307.774 .000** objectives Investment 3855.162 1 3855.162 356.921 .000** satisfaction Facility 1572.120 1 1572.120 315.737 .000** satisfaction Innovative 900.553 1 900.553 318.632 .000** measures
224 Type III Independent Dependent Mean Sum of df F Sig. Variable Variable Square Squares Problems 2404.229 1 2404.229 328.118 .000** Age Investment 89.200 1 89.200 4.746 .030* objectives Investment 11.592 1 11.592 1.073 .301 satisfaction Facility 34.923 1 34.923 7.014 .008** satisfaction Innovative 14.130 1 14.130 5.000 .026* measures Problems 7.022 1 7.022 .958 .328 Gender Investment 22.322 1 22.322 1.188 .276 objectives Investment 33.234 1 33.234 3.077 .080 satisfaction Facility .762 1 .762 .153 .696 satisfaction Innovative 7.843 1 7.843 2.775 .096 measures Problems 35.445 1 35.445 4.837 .028* Martial Status Investment 28.386 1 28.386 1.510 .219 objectives Investment .045 1 .045 .004 .949 satisfaction Facility 26.692 1 26.692 5.361 .021* satisfaction Innovative .364 1 .364 .129 .720 measures Problems 18.983 1 18.983 2.591 .108 Educational Investment 23.534 1 23.534 1.252 .263 Qualifications objectives Investment 3.125 1 3.125 .289 .591 satisfaction Facility 5.357 1 5.357 1.076 .300 satisfaction
225 Type III Independent Dependent Mean Sum of df F Sig. Variable Variable Square Squares Innovative 4.891 1 4.891 1.730 .189 measures Problems 84.528 1 84.528 11.536 .001** Occupation Investment 116.999 1 116.999 6.225 .013* objectives Investment 25.933 1 25.933 2.401 .122 satisfaction Facility 29.747 1 29.747 5.974 .015* satisfaction Innovative .362 1 .362 .128 .720 measures Problems 2.946 1 2.946 .402 .526 Annual Investment 1014.005 1 1014.005 53.948 .000** Income objectives Investment 82.041 1 82.041 7.596 .006** satisfaction Facility 257.483 1 257.483 51.712 .000** satisfaction Innovative 25.697 1 25.697 9.092 .003** measures Problems 38.907 1 38.907 5.310 .021* Nature of Investment 168.022 1 168.022 8.939 .003** Family objectives Investment 160.850 1 160.850 14.892 .000** satisfaction Facility 52.974 1 52.974 10.639 .001** satisfaction Innovative .301 1 .301 .107 .744 measures Problems 170.968 1 170.968 23.333 .000** No. of Investment 191.904 1 191.904 10.210 .001** dependents objectives Investment 52.536 1 52.536 4.864 .028* satisfaction
226 Type III Independent Dependent Mean Sum of df F Sig. Variable Variable Square Squares Facility 27.323 1 27.323 5.488 .019* satisfaction Innovative 13.845 1 13.845 4.899 .027* measures Problems 26.191 1 26.191 3.574 .059 House Investment 16.594 1 16.594 .883 .348 Ownership objectives Investment 139.010 1 139.010 12.870 .000** satisfaction Facility 26.083 1 26.083 5.238 .022* satisfaction Innovative 1.338 1 1.338 .473 .492 measures Problems 61.304 1 61.304 8.367 .004** Vehicle Investment 173.975 1 173.975 9.256 .002** Ownership objectives Investment 26.966 1 26.966 2.497 .114 satisfaction Facility .108 1 .108 .022 .883 satisfaction Innovative 35.237 1 35.237 12.468 .000** measures Problems 12.569 1 12.569 1.715 .191 Error Investment 15093.152 803 18.796 objectives Investment 8673.343 803 10.801 satisfaction Facility 3998.298 803 4.979 satisfaction Innovative 2269.526 803 2.826 measures Problems 5883.842 803 7.327
227 Type III Independent Dependent Mean Sum of df F Sig. Variable Variable Square Squares Total Investment 918822.000 814 objectives Investment 489622.000 814 satisfaction Facility 230813.000 814 satisfaction Innovative 131623.000 814 measures Problems 311582.000 814 Corrected Investment 17796.541 813 Total objectives Investment 9361.577 813 satisfaction Facility 4557.421 813 satisfaction Innovative 2478.026 813 measures Problems 6294.904 813 a. R Squared = .152 (Adjusted R Squared = .141); b. R Squared = .074 (Adjusted R Squared = .062) c. R Squared = .123 (Adjusted R Squared = .112); d R Squared = .084 (Adjusted R Squared = .073) e R Squared = .065 (Adjusted R Squared = .054); Source: Primary Data
** - Significant at 0.01 level; * Significant at 0.05 level
The demographic variables of investors explain the dependent variables investment objectives, investment satisfaction, facility satisfaction, innovative measures and problems with the total variance of 15.2%, 7.4%, 12.3%, 8.4% and 6.5% respectively.
It is found that the age of the investors predicts investment objectives (F = 4.746), Facility satisfaction, (F = 7.014) and Innovative measures (F = 5.00). In
228 investment objectives the investors in the age group of 41-60 years (mean = 4.295) are highly aware of investment objectives. Similarly the age group 41-60 are aware of facility satisfaction and innovative measures.
Gender has its impact on problems (F = 4.837), especially the female investors are aware of problems in capital market (mean = 4.03) than male investors (mean = 3.86). The marital status of the investors explains facility satisfaction (F = 5.361). It is found that the separated investors status concentrate more on facility satisfaction (mean = 4.23) followed by married (mean = 4 .17) and unmarried (mean = 4.15).
Educational qualification predicts problems (F = 6.225). The graduate investors (mean = 3.90) and diploma investors (mean = 3.92) are aware of innovative developments in capital market.
Occupation of investors predicts investment objectives (F = 6.225) and facility satisfaction (F = 5.974). Among these, occupation of the investors who are working as government employees (mean = 4.28) followed by private employees (mean = 4.17) concentrate more on these reforms. Income predicts all the latest development investment objectives (F = 53.948), investment satisfaction (F = 7.596) and innovative measures (F = 9.092). In the case of investment objectives, the income group of 3 lakhs and above investors alone (mean = 4.40) are aware of it. The investors with the annual income 2-3 lakhs (mean = 4.16) are aware of investment satisfaction; those with annual income of above 3 lakhs are very much aware of facility satisfaction (mean = 4.39), innovative measures (mean = 4.43) and finally the income group of 2-3 lakhs are aware of problems (mean = 3.91).
The nature of family predicts investment objectives (F = 8.939), investment satisfaction (F = 14.892) facility satisfaction (F = 10.639) and problems (F = 10.639). It is also found that the investors in the nuclear family are aware of investment objectives (mean = 4.20) than joint families. Similarly, the nuclear family investors are aware of investment satisfaction (mean = 4.10), facility satisfaction (mean = 4.21) and problems (mean = 3.93).
229 It is inferred that the number of dependents is considered as a very important factor for investors to deal with the capital market the ownership of the house explains the investors’ interest on investment satisfaction (F = 12.87) facility satisfaction (F = 5.238) and problems (F = 8.367). The investors with own house are showing special enthusiasm on investment satisfaction (mean = 4.07), facility satisfaction (mean = 4.19), and problems (mean = 3.89).
The ownership of vehicles predicts investment objectives (F = 9.26), and innovative measures (F = 12.47). The investors with four wheelers are aware of investment objectives (mean = 4.38) and those who do not possess the vehicles are drawn by innovative measures (mean = 4.47). So, it is concluded that that all the demographic variables of investors are related to investors in understanding the latest developments of capital market. All the above observations have been explored in table - 5.86.
5.27 A MODEL OF INVESTMENT PATTERN IN STOCK MARKET
The present research ventured in identifying investment pattern of investors in stock market. It ascertained through analysis of primary data of investors and under pinned the exact the pattern of investment in stock market with regard to Chennai geographical base. The primary data is analysed through the various statistical tools factor analysis, cluster analysis, multiple regression analysis, analysis of variances, Karl Pearson’s co-efficient of correlation and non-parametric chi-square analysis.
The analysis revealed socio-economic profile of investors is a basis for ascertaining the investment profile. The multiple regression analysis is followed by analysis of variance significantly identified that the investor’s socio-economic profile desires their type, category, and type of market they invest.
The sequential analysis further revealed the investment profile reveals a characteristics feature of investors through their investment preferences and objectives. The analysis of variance with suitable ‘F’ value clearly proved the relationship between investment profile, investment preferences and investment objectives. The inter
230 correlation between investment preferences and investment objectives identified their existence of positive relationship between preferences and objectives.
The factor analysis found that investment decision is a composition of five pre- dominant factors general information, company management, details of present issue, project details and financial parameters. The overall relationship between the factors of investment decision with preferences and objectives are established through significant correlation co-efficient.
The factors of investment decision act as a basis for the formation of heterogeneous groups of investors, similarly investment satisfaction and problems of investors classify them into various heterogeneous groups. The mutual association among investment decision, investment satisfaction and problems are significantly associated through non-parametric chi-square analysis. This model profoundly concludes that the research instrument used in the study is highly reliable is ascertained through this model. This investment pattern of Chennai investors is identified through this model.
5.28 SUMMARY
In this chapter, factors influencing equity investors, investment satisfaction and investors’ confidence of the retail equity investors have been assessed.
231 CHAPTER – VI
SUMMARY OF FINDINGS SUGGESTION AND CONCLUSION
INTRODUCTION
This chapter is intended to present the findings of the research and suitable suggestions, profound conclusions and scope for further research.
The microscopic cross examinations of the primary and secondary data reveal the following results. Primary and secondary data are explored completely to ascertain the important factors of the study, to identify the reasons of investors for investing in retail investment, impact of investment decision, relationship between financial sector reforms and equity retail investment. The changes in the attitude of investors were noticed after the latest developments in capital market in 1991. Now the investors possess greater awareness through TV, newspaper and other sources of information. The transparency in capital market is considered as one of the vital reforms that magnetically attracted the investors and increased their number in retail investment. The classification of markets paved way to the investors to select their own lucrative choice and make them to employ various strategies to overcome the impediments in investment procedures.
6.2 MAJOR FINDINGS OF THE STUDY
6.2.1 OBJECTIVE ONE
To study the investment pattern of retail equity investors in Chennai.
A maximum percentage of 54.9% of investors are in the age group of 26 to 40 followed by the investors in the age group 41 to 60 which is 33.3%. Male investors are more enthusiastic than females in equity shares investment.
It is identified that most of the investors are working in private concerns or running their own business, that is 43% and 32.7% of investors are employed in private or in their business concerns. The Government employees are not enthusiastic more in equity shares.
It is found that 39.1% investors belong to the income groups of Rs. 1 - 2 lakhs and 26.6% investors have the income less then Rs. 1 lakh, 22.9% are in the income of groups of Rs. 2 - 3 lakhs. The number of dependents and investment are inversely proportional to
232 each other. When the number of dependents is more in the family, they do not have ample money for investment in this present economic situation.
It is found that 72% of the respondents establish themselves as both long term investors and daily traders and 12.6%of them operate equity investment daily. Most of the investors are having the experience in the securities market just below 5 years. The young investors and educated persons now enter into the securities markets.
It is found that 74.1% of the respondents in Chennai invested in less than 10 companies and remaining 25.9% of them are attracted towards more than 10 companies share market investment. 10.7 % of the respondents have an investment of less than Rs. 1, 00,000. The investment level of 35.4 % of the respondents is between Rs. 1, 00,000 and Rs. 2, 00,000. 23.5 % of them have an investment size which ranges from Rs.2, 00,000 to Rs. 3, 00,000.
The maximum number of investors invest own funds to obtain better returns. A maximum of 64% of sample size are investing their fund out of their savings below 25%, most of the investor are invest their money out of their saving below 25% of the surplus money that they had.
6.2.2 OBJECTIVE TWO
To analyse the information search and investment option of retail investors.
A maximum of 77.6% of investors get the information about the securities market through news papers followed by 66.4% of investors get the information through television media, 56.5% of investors receive the information through the stock brokers.
A major percentage of the investors are getting the information through news papers television and stock brokers. 49.6 percent of investors are investing their money after analyzing the financial performance of the companies and only 0.5 percent of investors are considering some other factors like present market condition and new production strategies.
233 A maximum of 85.8 percent of investor are possessing experience in dealing their investment forums followed by 14.2 percent of investor doesn’t have any experience with the forum of investors. Most of the investors in Indian securities market are having the knowledge about the malpractices done by the intermediaries and share brokers.
It is ascertained that a maximum of 82.1 percent of investors in securities market are aware of the online trading and they buy and sell their equities followed by 17.9 percent of investors deal with offline trading. Majority of the investors in Indian securities market are aware of the financial sector reforms made by the Government of India.
42.9% of the investment decisions are taken based on sensex index and 31.9% of the investors’ decisions are influenced by the index of Nifty. Most of the investor’s decisions are influenced and taken by the observations of sensex index.
Newspaper plays a crucial role in identifying all the industries except IT industry. It is found that the information through Journals and magazines is useful for investors to invest in banking, manufacturing, textile and automobile industries. Banking, steel and cement industry are concentrated by the investors with the help of information through TV channels.
The stockbrokers give more information to the investors in selecting the industry. The investment consultants significantly guide the investors to invest in banking, steel, IT, manufacturing, textile and automobile industries. Web sites give profuse source of information for investors about the performance of banking, cement, IT, pharma, manufacturing, and automobile industries
6.2.3 OBJECTIVE THREE
To identify the various investment preferences and investors perception on risk and return.
The most preferred investments are well established and the investors strongly agree that the investment in capital market alone gives more returns with minimum
234 market risk. The investors prefer share market as most preferred investment followed by fixed deposit, real estate, mutual funds, government bonds, gold and debentures in order
The investors invest their money safely in banks in the form of deposits and give second preference to IT industry followed by cement and pharma industry. The investors also concentrate more on the safety of their investments in banking sector.
All type of investors demand more returns with no risk. So they prefer share market fabricated with minimal risk. It is found that the investors adopt the modes of calculative, conservative, risk taking, impulsive and intuitive in the respective order.
The investors investing in secondary market give their first preference to NSE followed by BSE and MSE respectively. The transparency about the performance of the companies issuing the shares and continuous monitoring of central government and the RBI raises the confidence among the investors besides the market risk. It is also found that the investors are willing to invest their hard earned money to have lucrative returns in the short span of time.
It is ascertained that a maximum of 59.2% of the investors expect to get return below 12% of their investments followed by 19% of the investors prefer to invest 36 % and above of their investments in equities.
6.2.4 OBJECTIVE FOUR
To examine factors influencing investment evaluation and decision of investors.
The cluster analysis revealed that 42.16 percent investors express the opinion that they moderately agree on all the elements of capital investments and remaining 57.54 percent investors strongly agree with the investments in equity shares
235 The investors accept equally about the investments in secondary market, project details and their changes, and financial parameters. It is concluded that all the investments are important and they reflect the investments of equity shares Investors’ opinion on investments can not be distinguished on their experiences with equity shares dealings. The retail investments are totally spread over all the investors equally independent of their number of years of dealings.
The investors invest their money in share market to accrue maximum benefits before and after investments. The retail investment just induces the investors to invest in share market, but the investors welcome any type of investments of equity shares with better returns and absolutely no risk.
All the investors are aware of retail investment immaterial whether they invest in shares or not. The updated information to the investors could be a more effective source of information.
The investors who differ in their opinion of investing in Government Bonds also differ in identifying the investments in equity shares. The investors are very much attracted towards the primary and Details of present values, change of project details investments and investments in financial parameters.
The investors are very much attracted towards change of project details investments in equity shares and that in turn induces them to invest more in primary and secondary markets. When the investors invest their money in gold they do not have more knowledge about retail investment. The investors who are investing in gold are also turning their concentration towards equity shares
Investors who concentrate on debentures are very much attracted towards general information, Details of present values and financial parameters. They profoundly believe that retail investments of above elements are really worthy of better returns.
The investors of mutual funds also possess a tendency to shift their investment pattern towards equity shares. They feel that the same amount of risk is involved in
236 mutual funds and equity shares but in the case of returns the equity shares exceeds more than the mutual fund.
The investors shift their concentration towards equity shares due to the latest developments in Indian equity shares. They feel that they are able to get the same type of returns as that of real estate within a short span of time.
The investors expect more returns, they differ in their views about general informations, Details of present values and change of project details whereas they have the same view on Company management and financial parameters.
It is inferred that when the investors expect liquidity from their investment, some of them are highly aware of capital investments while some others do not. The investors who invest their money for tax benefits are well aware of general information, Details of present values, change of project details and financial parameters.
Company management and change of project details differ the investors significantly in their perception of capital investments. The investors who are influenced by the TV channels have high awareness on Details of present values and financial parameters.
The investors want to invest in both the markets and the secondary market is more popular among the investors than the primary market. There is a association between preference of investment in equity shares and cluster of awareness on retail investment. The investors decide to invest in primary market and secondary market after knowing the capital investments only the investors
The general information in equity shares does not have any impact on investors to invest certain percentage in primary and secondary markets. Company management induce the investors to invest a considerable percentage of their money in share market. The change of project details and financial parameters do not have any impact on investors to invest funds in share market.
237 It is inferred that there is an association between criterion for investment and cluster of awareness of capital investments. The investors are all well aware that the capital investments giving certain specific criteria for the investment procedure.
6.2.5 OBJECTIVE FIVE
To evaluate investors level of satisfaction and their futuristic perceptions towards retail equity investment.
It is found that the investors of equity market are distributed into three groups on the basis of investment pattern prevailing in India. The first group consists of 6.11 percent investors with minimum awareness on equities and 63.12 percent with high awareness on equity investments.
Equity investments have affected the investment in the banking sector. More number of investors is enthusiastic in venturing into equity shares pertaining to banking sector. The investors have the knowledge about company management before they invest in FMCG sector.
General information, company management, and details of present values, change of project details and financial parameters significantly affect the investment in pharma sector and PSE sector retail investment.
The degree of awareness and knowledge about retail investment has enabled the investors for making meaningful investment decisions in MNC sector. It is also found that change of project details does not have any impact on investment in IT sector
The general information affects the investment in manufacturing sector. The investors find a scope for their investment in manufacturing sector after general capital investments. Other details do not have any role to play with manufacturing sector.
General information, Company management, Details of present values, change of project details and financial parameters affect the investment in service sector. The investors are drifting towards service sector after obtaining the details of investment.
238 There is no association between extensive of risk and awareness of retail investment. The investors are very much aware of risks involved in investing in equity shares, because it depends upon the performance of firms.
It is inferred that different reasons for preference of stock exchange arise due to retail investment. There is no association between dealing with electronic shares and elements of retail investment.
The investors are very much attracted by share market after understanding the attractive financial sector reforms. The transparency about the performance of the companies issuing the shares.
Facility satisfaction does not create an impact on instruments and their changes. Innovative measures have good impact on all elements of capital reforms, except financial parameters. Problems create deep impact on capital market reforms, primary market reforms secondary market reforms, instruments and their changes, but it does not predict financial parameters.
The equity investment has predicted good impact on reforms in capital market. Collectively the equity investments aim at reforming primary and secondary market. Positive changes in the instrument and better returns to the investors prevail in the equity market.
The investors are also exploring the avenues like real estate, gold investment and government bonds to get more returns with less risk. There is no significant relationship between the number of years in dealing with capital market and equity investment, some investors are continuously investing in capital markets with their perception about the developments in capital market. They feel it is an advantage for their investment. Investment objectives and facility satisfaction severely affect the investor’s decision to decide the percentage of investment in share market.
239 6.2.6 OBJECTIVE SIX
To find the relationship between demographic variables of investors and their investment objectives, decision and satisfaction.
In this moderate awareness cluster age, gender, annual income and vehicle ownership of investors pave the way to know about general capital investments. The high awareness of investors is achieved through their age, marital status occupation, no. of dependents and percentage of investment.
In this moderate awareness group of investors, nature of family and vehicle ownership help them to acquire knowledge about company management. It is concluded that the nature of family decides the investor’s awareness on the company management.
The annual income, no of dependents and vehicle ownership are useful for the investors to know the company management. It is concluded that income, vehicle ownership and number of dependents explain the awareness of investors on company management.
Age, nature of family, and house ownership create a good impact on details of present values. In moderate awareness, clusters, the equity market awareness can be observed by the investors using their age, nature of family and house ownership.
The investors with high awareness on retail investment are able to initiate more ideas of details of present values through age alone. Genders, income, ownership of the house explain the awareness of investors on changes of project details. The gender, income and ownership of the house decide their high awareness on details of present values.
The marital status and income of the investors decide them to possess moderate awareness on change of project details. The marital status, occupation, income and house ownership of investors pave the way for them to understand the financial parameters. The moderate awareness on financial parameters can be obtained through the marital status, occupation, income and house ownership of the investors.
240 The high awareness on financial parameters of investors is decided by their occupation and the number of dependents in the family. The investors show good enthusiasm for various investment avenues. Company management makes the investors to go for investing in Government bonds. Details of present values compel the investors to invest in gold and in lands. Change in project details forces the investors to go in for own lands and similarly financial parameters direct the investors to invest in lands.
It is found that the age of the investors predicts investment objectives, Facility satisfaction, and Innovative measures. In investment objectives the investors in the age group of 41-60 years are highly aware of investment objectives. Similarly the age group 41-60 are aware of facility satisfaction and innovative measures.
Gender has its impact on problems, especially the female investors are aware of problems in capital market than male investors. The marital status of the investors explains facility satisfaction. It is found that the separated investors status concentrate more on facility satisfaction followed by married and unmarried.
Educational qualification predicts problems. The graduate investors and diploma investors are aware of innovative developments in capital market.
Occupation of investors predicts investment objectives and facility satisfaction. Among these, occupations of the investors who are working as government employees followed by private employees concentrate more on these reforms. In the case of investment objectives, the income group of 3 lakhs and above investors alone are aware of it. The investors with the annual income 2-3 lakhs are aware of investment satisfaction; those with annual income of above 3 lakhs are very much aware of facility satisfaction, innovative measures and finally the income group of 2-3 lakhs are aware of problems.
The investors in the nuclear family are aware of investment objectives than joint families. Similarly, the nuclear family investors are aware of investment satisfaction, facility satisfaction and problems.
241 It is inferred that the number of dependents is considered as a very important factor for investors to deal with the capital market. The investors with own house are showing special enthusiasm on investment satisfaction, facility satisfaction, and problems. The investors with four wheelers are aware of investment objectives and those who do not possess the vehicles are drawn by innovative measures.
6.3 SUGGESTIONS
Based on the study, the following suggestions have been made.
The transparency must be made about the companies and their performance so that the investors can decide their investment on suitable shares.
Corporate governance has to be implemented in all stock exchanges.
Innovative technologies like integration of stock exchanges, demat, online trading, creation of development of web pages must be brought in capital markets for its growth and to attract the educated investors.
Strategies like hedging, index futures must emerge in capital market to reduce the market risk, provisions must be made to return at least the principal amount of investors.
Strategies must be employed to encourage women investors. Awareness programmes has to conduct in all places.
The competitions of capital market have come from instructional investors like mutual funds and real estate. So the companies must be careful enough in issuing their shares.
Transparency must be made both in primary market and secondary market equally to help the investors to get their capital.
242 Shares, Debentures and bonds are familiar to urban investors. But their counterparts in rural areas do not know anything about them.
Investors are the hub of the capital market. Their satisfaction is the most important. So it should be done by providing safety, return and liquidity for their investments.
Capital market should create a higher level critical factors involved for making investment decisions.
Companies should provide information/education to investors at large with detailed data including the role of SEBI to make them smart.
Regarding capital market more journals, newspapers and TV media have to reach the investors.
The investors should be allowed an opportunity to trade in International Stock Exchanges.
As far as the capital market is concerned research carried out is very less. So, SEBI and other agencies should provide assistance to carryout advance research in this area.
Credit rating agencies should rate the equities and mutual funds for the benefit of the investors.
SEBI and other intermediaries should tap the rural investors by conducting awareness programme exclusively for them.
6.4 IMPLICATION OF THE STUDY
This study would be of immense help to managers, particularly, financial managers who take decisions regarding investment and investors’ attitude towards share market. The study will help investment consultants in identifying the investment avenues. The credit rating agencies can use the information for their investment rating. Investor’s
243 preference for equity retail investment will help policy makers in formulating strategies. The study helps for timing and type of instruments for new issues in retail investment. Stock exchanges can introduce technological advancement in trading. In short, this piece of research work has become quite friendly to all the three groups of players in the capital market viz. the investors, issuers and the intermediaries.
6.5 SCOPE FOR FURTHER RESEARCH
Based on the study done by the researcher, the following suggestions are identified for further research.
Since the present study is at a regional level, it could be extended to state and national level.
The impact of retail investment in capital market may be studied in view of rural investors.
The study may further be carried out to analyse the impact of reforms on the functioning of stock exchanges.
A study on the awareness of women investors about retail investment pattern could be attempted.
Implications of internet stock trading in India can be taken up for study.
Impact of technological innovation in capital markets can be studied.
6.6 CONCLUSION
Indian retail investment in share market has now grown into a great material market with a lot of qualitative inputs and emphasis on investors’ protections and disclosure norms laid down. The market has become automated, transparent and self- driven. It has integrated with global markets with Indian companies seeking listing on foreign stock exchange, off shore investments coming to India and foreign mutual funds floating their schemes and thus bringing expertise in to our markets. India has achieved the distinction of possessing the largest population of investors next to the U.K. Perhaps ours is the country to have the largest number of listed companies with around 19 Regional Stock Exchanges and National Stock Exchanges most of them automated. India
244 now has world class regulatory system in place. Thus at the dawn of the new millennium, stock market increased the wealth of Indian companies and investors. No doubt strong economic recovery, upturn in demand, improved market structure, etc. have been the driving forces.
Further, financial services sector is considered to be the nuclear of the growth model designed for the economic development of our vast country. Financial services and markets constitute significant components of the financial system. Development and reforms in this field are inevitable for the growth of our developing economy. Accordingly, a lot of financial reforms have been made as and when required for the welfare of the investors and the institutions.
The investors of to-day are more rapidly informed than their predecessors of yesterday. So they are better informed and better treated. They want to be secure when they aspire to become rich, wanted to save while they are tempted to spend, want to feel the joy of pride and avoid the pain of regret. However every agency in the capital market should plan their strategies for profit to investors on a long term basis. The potential investor must be properly educated and guided in a manner that more idle resources or invested in other avenues will be diverted to capital market. Increase in GDP (9%) raising of sensex around 20,000 more participation of MNCS with their FDI results in the progress of Indian economy and awareness of the prudent Indian investors. If and when all financial reforms are inflated, the Indian capital market will not only be on par with developed capital markets of the world, but also will become the paradise for investors. Conclusively the quantum of retail investment increased rapidly as well as enormously, liberalization continues to blow retail market investment by adapting itself to new procedures practices and patterns with the entry of various players in the market; it is poised to achieve unprecedented levels of growth in the near future.
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251 II. JOURNALS AND PERIODICALS
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256 48. Kuntluru S. and Md. Akbar Ali khan, “Financing pattern of foreign and Domestic owned Pharmaceutical companies in India”, The management Accountant ICWAI Journal Vol. 44 No.12 December 2009 PP: 984 – 991.
49. Larry D. Wall, “On investing in the Equity of small firms”, Journal of small Business management 2007 45 (1) PP: 89-93.
50. Levine, Ross and S. Zervos, “Stock Market Development and Economic Growth”, The World Bank Economic Review, Vol.1012, PP.323-339, 2008.
51. Lieven Baele,” Olivier De Jonghe and Rudi vander Vennet, “Does the Stock Market value bank diversification? “ Federal public planning service science policy, inter university Attraction 2005 PP: 1-27.
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53. Mahabaleswara Bhatta H.S. “Behavioral Finance- A discussion his individual investor biases”, The Management Accountant ICWAI Journal Vol.44, No. 2, February2009, PP: 138-141.
54. Malcolm Baker and Jeffrey Wurgler, “A Catering Theory of Dividends,” The ICFAI Journal of Behavioral Finance, Vol.59, Issue 3, 2008 PP: 32-60.
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56. Manish Mittal and R K Vyas, “personality type and investment choice: An empirical study”, The ICFAI University Journal of Behavioral Finance, Vol. V, No. 3, 2008, PP: 6-22.
257 57. Marcela Meirelles Aurelio, “Going Global: The changing pattern of U.S. Investment Abroad,” Economic – Federal Reserve Bank of Kansas city Vol.93 No.3, Third quarter 2006 PP: 5-33.
58. Maria May seitanidi, “Intangible economy: how can investors deliver change in business? Lessons from non profit business partnerships”, Management Decision Journal, Emerald Group publishing limited Vol.45 No.5 2007 PP: 853-865.
59. Mark Grinblatt, Matti Keloharju, “The Investment Behaviour and Performance of Various Investor Types: Study of Finland’s unique Data set”, Journal of Financial Economics, Vol. 55, 2010, pp: 43-67.
60. Maruthu Pandian P, Benjamin Christopher S, “A study on Equity Investor Awareness”, Doctoral Dissertation at Bharathiar University, 2011.
61. Masashi Toshino and Megumi suto,” Cognitive biases of Japanese institutional investor’s consistency with behavioral finance,’ The ICFAI Journal of Behavioral Finance, March 2008 PP: 7-18.
62. Meenu Verma, “Wealth management and behavioral finance: The effect of demographics and personality on investment choice among Indian investors”, The ICFAI University Journal of Behavioral Finance, Vol. V, No. 4, 2008, PP: 31-57.
63. Meir Statman, Steven Thorley and Keith Vorkink, “Investor overconfidence and Trading volume,” The Review of Financial studies Vol.19, No. 4 , 2006, PP: 1531- 1565.
64. Michael J. Robinson and Thomas J. Cottrell, “Investment patterns of informal investors in the Alberta private Equity Market,” Journal of small Business Management Vol. 45, No. 1 PP: 47-67.
65. Michael Kaestner, “investors’ Misreaction to unexpected earnings: evidence of simultaneous overreaction and under reaction,” The ICFAI Journal of Behavioral Finance, March 2008, PP: 32-42.
258 66. Ming Dong, Chris Robinson and Chris veld, “Why individual investors want dividends,” The ICFAI Journal of Behavioral Finance, Vol. III, No. 2, 2007, PP: 27-62.
67. Minh Quang Dao, “The impact of investment climate indicators on Gross capital formation in developing countries,” Eastern Illinois university, USA, working paper, 2007, PP: 1-10.
68. Mohammad Salahuddin and Md. Rabiul Islam,” Factors affecting investment in developing countries: A panel data study,” South east university Bangladesh, working paper, 2009, PP: 21-37.
69. Mohanty B.K. “Market capitalization: A suitable growth approach for share holders’ value creation”, The Management Accountant ICWAI Journal Vol.43, No. 8, August 2008, PP: 398-401.
70. Nagarajan R.“Green shoe option in IPO”, The Management Accountant ICWAI Journal Vol.40, No. 5, May 2008, PP: 398-401.
71. Narendra Jadhav, “Development of Securities Market – The Indian Experience”, Association for Financial Professionals (AFP), Annual conference, session: 30 2009, PP: 1-34.
72. Nissim Ben David, “An indicator for internalization of analyst’s recommendations by investors, “The ICFAI University Journal of Behavioral Finance Vol. V, No. 3, 2008, PP: 23-35.
73. NSE-Fact book: 2006, www.nseindia.com,p.1, PP.85.
74. Panda K, Tapan N.P and Tripathi, “Recent Trends in Marketing of Public Issues: An Empirical Study of Investors Perception”, Journal of Applied Finance, Vol. 7, No.1, 2010, pp: 1-6.
75. Qiang Cheng and Terry D. Warfield,” Equity incentives and earnings management,” The Accounting Review Vol.80, No. 2, PP: 441-476.
259 76. Rajarajan V, “Investors Life Styles and Investment Characteristics”, Finance India, Vol. XIV, No. 2, 2010, pp: 465-478.
77. Ramesh Gupta, “Retail Investor – A lost Species”, IIM Working paper series, E 15378, p:1.
78. Retail Investments into Equity”, IIM Working paper series, E27119, p:4.
79. Roopam Kothari and Narendra Sharma,” Testing the Beta Stability of Banking Sector over various Phases in Indian Stock market,” The Management Accountant ICWAI Journal Vol.45 No.7 July 2010 PP: 591-595.
80. Sachdeva, “Emerging Securities Market – Challenges and Prospects”, Chartered Financial Analyst, Feb 2005, PP.53-56.
81. Sadhan Kumar Chattopadhyay and Samir Ranjan Behera, “Financial Integration for Indian Stock Market”, Department of Economic Analysis and policy of the RBI, Working paper, 2006, PP: 1-29.
82. Sakthivel N. “EVA – MVA: Shareholders’ value measure”, The Management Accountant ICWAI Journal Vol.45, No. 1, January 2010, PP: 10-14 &18.
83. Santi Swarup K, “Measures for Improving Common Investor Confidence in Indian Primary Market: A Survey”, Research Publication, 2008, nseindia.com.
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86. Securities and Exchange Board of India-National council of Applied Economic Research (SEBI – NCAER), “Survey of Indian investors”, Chartered Secretary, Vol. XXX, No.9, 2009, pp: 1201-1207.
260 87. Security Regulations, Guidelines, Schemes in Force, SEBI bulletin, Vol.3, No.11, Nov 2005, PP.13
88. Selvam M, Rajagopalan V, Vanitha S, Babu M, “Equity culture in Indian Capital Market”, Sajosps, Vol. 4, No. 1, July-Dec 2003, pp: 66-78.
89. Sen S.S. and S.K. Ghosh, “Stock Market Liquidity of BSE and NSE: A comparative study (1999-2005),” Management Accountant ICWAI Journal Vol.43 No.2 February 2008 PP: 55-60.
90. Sen S.S. B.K. Ghosh and Santanu Kumar Ghosh, “ Stock market liquidity and Exchange Rate –A case study on BSE & NSE”, The Management Accountant ICWAI Journal Vol.42, No.10 October 2007 PP: 820-821 & 830.
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262
III. REPORTS
Annual Reports of RBI (2000 – 2010)
Annual Reports of SEBI (2000 – 2011)
Gupta L.C, “Indian share owner–A survey”, Society for Capital Market Research and Development, (2011), New Delhi.
Gupta L.C, Naveen Jain and Team, “Indian Household Investors Survey-2004”, Society for Capital Market Research and Development”, (2006), Delhi.
Hong Kong Exchanges and clearing Ltd (HKEx), (2001-02), Derivatives Retail Investor Survey (DRIS).
Santi Swarup K, “Measures for Improving Common Investor Confidence in Indian Primary Market: A Survey”, Research Publication, 2008, nseindia.com.
Securities and Exchange Board of India-National council of Applied Economic Research (SEBI – NCAER), “Survey of Indian investors”, Chartered Secretary, Vol. XXX, No.9, 2010, pp: 1201-1207.
IV. WEBSITES www.nse-india.com www.bseindia.com www.sebi.gov.in www.moneycontrol.com www.watchoutinvestors.com
263 www.rbi.org.in www.nyse.com www.nsadag.com www.epwrf.res.in
INTERVIEW SCHEDULE PART 1: SOCIO ECONOMIC PROFILE
1. Age : Below 25 years 25 - 35 years
: 35 - 45 years 45 - 55 years
: 55 & above
2. Gender : Male Female
3. Marital Status : Married Unmarried
4. Educational Level : School Education
: College Education
: Professional
: Others, Specify______
5. Occupation : Salaried
: Professional
264 : Business
: Retired
: Others, specify ______
6. No. of Members in the Family :
7. No of Earning Members
in the Family :
8. Monthly Family Income : Below Rs. 10,000
: Rs. 10,000 – Rs. 20,000
: Rs. 20,000 – Rs. 30,000
: Rs. 30,000 – Rs. 40,000
: Rs. 40,000 & above
265 PART 2: INVESTMENT PROFILE AND PATTERN
2.1 Type of investor
Hereditary investor New generation investor
2.2 Category of investor Long term investor Day trader both
2.3 Type of market Operated Primary market Secondary market both
2.4 Experience in the market Less than 1 year 1-3 years 3 years & above
2.5 Number of companies in which investment is made Less than 10 10-20 20 & above
2.6 State the approximate size of investment in shares as on date Below Rs. 1 Lakh
Rs. 1 lakh – Rs. 2 lakhs
Rs. 2 lakhs & above
2.7 State the source of investment
Own savings Borrowings Both
266
2.8 State the Percentage of your savings invested in shares Less than 15 % 15% - 30 % 30% and above
2.9 Rank the following sources of investment information based on usage and reliability (1 to 10)
S. No Sources of Investment Information Rank
a Abridged Prospectus
b Newspaper Journals & Magazines
c TV Channels
d Investments Related Websites
e Brokers / Analysts Forecast
f Investor Forum
g Technical Analysis
h Company Announcements
i Stock Exchange Announcements
j Others (Friends , Relatives etc)
2.10 Mode of trading Online Offline Both
2.11 State the trading volume per month a. Long-term investor Less than Rs. 1 lakh
Rs. 1 Lakh – Rs. 2 lakhs
Rs. 2 lakhs & above
267
b. Day trader Less than Rs. 50 Lakhs
Rs. 50 Lakhs – Rs 1 Crore
Rs. 1 Crore & above
2.12 State the indices you frequently refer
S. No Indices Tick ( )
a Sensex
b S&P CNX Nifty
c CNX Nifty Junior
d CNX 100
e S& CNX 500
f CNX Mid-cap
g CNX Mid-cap 200
2.13 Are you a member of any investor forum? Yes No
If yes, specify the period
Less than 1 year 1- 3 years 3 years & above
268 PART 3: INVESTMENT PREFERENCES & RISK RETURN PERCEPTIONS
3.1 Rank your Investment preferences (1 to 10)
S. No Investments Ranks
a Shares
b Debentures / Bonds
c Stock Futures and Options
d Mutual Funds
e *NSC/PPF/PF
f Fixed Deposits
g Insurance Policies
h Real Estate
i Gold / Silver
j Others
*NSC – National Saving Certificate, PPF – Public Provident Fund, PF – Provident Fund
3.2 Rank your Sectoral preferences for stocks (1 to 10)
S. No Sectoral Stocks Ranks
a IT Sector
b Bank Sector
c *FMCG sector
d *PSE Sector
269 e *MNC Sector
f Service Sector
g Energy Sector
h Pharma Sector
Infrastructure & Capital Goods i Sector
*FMCG – Fast Moving Consumer Goods, PSE – Public Sector Enterprises MNC – Multinational Company.
3.3 State the level of risk and return associated with the following investments.
Level of risk Level of Return
Very Mode Very Very Mode Very High rate Low Investments High rate Low High Low High Low Shares Debentures / Bonds Stock Futures and Options Mutual Funds NSC/PPF/PF Fixed Deposits Insurance Policies Real Estate Gold / Silver Others *NSC – National Saving Certificate, PPF – Public Provident Fund, PF – Provident Fund
270 Kindly answer the following questions with regard to Equity Shares (Part 4, 5 &6)
PART 4: INVESTMENT OBJECTIVES
4.1 State the level of importance of the following investment objectives
Very High Moderate Low Very S. Investment Objectives High low No
a Dividends
b Capital Appreciation
c Quick Gain
d Safety
e Liquidity
f Tax Benefits
g Diversification of Asset Holding
h Rights / Bonus issues & Stock splits
i Hedge against Inflation
4.2 State the expected rate of return (ROR) per annum.
Less than 12%
12% - 24%
24% - 36%
36% & above
271
PART 5: FACTORS INVOLVED IN INVESTMENT EVALUATION AND
DECISION
5.1 State the level of influence of the following factors in investment evaluation and decision
Level of importance S. Investment Factors Very Moderate Very No High Low high Low 5.1.1 General Information a. Stock Exchange information b Risk factors c Lead managers image d Credit rating e Brokers advice/ Analysts forecast/Advertisement impact 5.1.2 Company Management a Company history b Promoters background & contribution c Board of directors d Company’s present policies e Companies under the same management & their performance 5.1.3 Details of Present issue a Authorized and Paid up capital b Size of present issue c Objectives of present issue d Terms of issue e Minimum & Maximum subscription f Institutional investments 5.1.4 Project Details a Cost of the project & Means of financing b Location /Process/ Infrastructure c Product strength d Existing & Future demand e Future prospects & Profitability 5.1.5 Financial parameters a EPS/PE Ratio b Dividend payment trend
272 c Book value, Market value per share & Price trends d Market volume traded e Bonus/ Rights issues & Stock splits f Performance of related companies
PART 6: INVESTMENT SATISFACTION
6.1 State the level of satisfaction achieved, in the following investment objectives
Level of importance Neutral / S. Investment Highly Highly No objectives Satisfied undecided Dissatisfied Satisfied Dissatisfied
a Dividends
b Capital Appreciation
c Quick Gain
d Safety
e Liquidity
f Tax Benefits
g Diversification of Asset holding
h Rights / Bonus issues & Stock splits
i Hedge Against Inflation
6.2 State the derived rate of return
Less than 12% 12% - 24%
24% - 36% 36% & above
273 6.3 State the level of satisfaction with respect to the following other aspects of share investment Level of importance S. Others Neutral / Highly Highly No Aspects Satisfied Dissatisfied Satisfied undecided Dissatisfied
Nation wide a trading facility Equal access b to all investors Fairness, efficiency and c transparency of security trading Settlement d cycle Prompt service from company e Such as transfers, subdivision etc Functioning f of Stock Exchange Functioning g of SEBI Quality of advice and h services of brokers Information i availability & reliability Market j regulation
274 Transparency k & disclosure norms Share holders rights & l equitable treatment Investor awareness & m education measures Investor n protection measures Speedy o redressal of grievances Functioning p of investor forum
6.4 State your level of agreeability regarding enhancing or introduction of the following measures, to increase investor confidence and to attract more investments in shares.
Level of Agreeability S. Agree Neutral / Measures Strongly Strongly No undecided Disagree agree Disagree
Information related a measures Scandal control b measures Investor awareness c and education Measures
275 Grievance handling d and Investor protection measures Regulating e intermediary and rating measures Market regulation f measures Return related g measures Government h measures Transparency in i Promoter’s activities Rating of equity j scripts Insurance coverage k for stock losses
If any other, Please specify______
______
276 6.5 How much you are affected by the following problems
S. Very High Moderate Low Very Problems Faced No High low
a No proper advise by Brokers
b Too many channel giving too many opinion about the market
c Difficulty in operating online trading
d Change of transaction password frequently
e Unauthorized transaction by brokers
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