Personal Variables of Perception towards Equity Derivative Markets in India

Selvaraj N^*
*Correspondence: Selvaraj N, Assistant Professor of Commerce, Saraswathi Narayanan College, Madurai, India, Tel: + 919843727975, Email:

Keywords

Derivatives • Stock market • Financial • Traders and investment

Introduction

The stock market is a place where buyers and sellers of stocks come together, physically or virtually. Market participants can be small individuals or large fund managers who can be situated anywhere. Traders place their orders to the professionals of a stock exchange who executes these buying and selling orders. The stocks are listed and traded on stock exchanges. Some exchanges are physically located, based on open outcry system where transactions are carried out on trading floor. The other exchanges are virtual exchanges whereas the network of computers is composed to do the transactions electronically. The whole system is order driven; the order placed by a Trader is automatically matched with the best limit order. This system provides the more transparency as it shows all purchase and sale orders. The Indian stock market has mainly functions on two major stock exchanges, the BSE (Bombay Stock Exchange) and NSE (National Stock Exchange). In terms of market capitalization, BSE and NSE have a place in top five stock exchanges of developing economies of the world. Out of total fourteen stock exchanges of emerging economies, BSE placed at fourth position with market capitalization of US$1,101.87 as on June, 2012 and NSE placed at fifth position for market capitalization with $1079.39 as of June, 2012.

Statement of the Problem

In India, Traders want maximum gain with minimum risk, so is the case with derivatives. Derivatives are among the forefront of the innovations in the financial markets and aim to increase returns and reduce risk. A derivative is a financial product which has been derived from another financial product or commodity. The derivatives do not have independent existence without underlying product and market. Derivatives are contracts which are written between two parties for easily marketable assets. It is derived by the means of a mutual agreement, the types of derivative products are limited only by imagination and so there is no definitive list of derivative products. Forward market, future market, option and swaps are the basic types of derivatives. A forward contract is an agreement to buy or sell an asset on a specified date for a specified price. The forward contracts are normally traded outside the exchanges and is present in India from long time back, but future option have emerged in few years in financial market and has brought improvement from the forward market as they are traded on exchange, therefore there is more transparency and less risk. A futures contract is a standardized contract, traded on a futures exchange, to buy or sell a certain underlying instrument at a certain date in the future, at a pre-set price. And a futures contract gives the holder the right and the obligation to buy or sell, which differs from an options contract.

The trading of derivative securities commenced in India after much debate over the introduction of derivatives to hedge the risks posed by the securities and a long waiting period. The National Stock Exchange (NSE) sought permission from the Securities and Exchange Board of India (SEBI) to trade stock index futures in December 1995, but it was only after five years that the first derivative security, i.e., stock index futures, was traded on the exchange. Stock index futures were introduced in June 2000, and thereafter, stock index options in June 2001. The options and futures on individual shares were introduced in July 2001 and November 2001, respectively. Later, more indices and shares were added in this segment. (Table I exhibits chronology of events relating to the development of derivative market in India.) As on December 31, 2009, there were 179 individual shares for which futures and options were traded. They are traded on the Bombay Stock Exchange (BSE) and the National Stock Exchange (NSE) wherein the latter contributes to more than 95 per cent of the total turnover in the derivative market in India. Derivatives are gaining importance due to increased volatility in capital and foreign currency markets. RBI finds ways for healthy development of market and takes steps to popularise the use of derivative instruments, but still awareness about the derivative instruments and its uses are quite low. Hence, it is necessary to find out the level of awareness among investing public and if found low, how to create adequate awareness to encourage the use of derivative products as hedge tools.

Financial derivatives were introduced as a risk management tool; but now they have become the most risky instruments in the markets as the experience in US markets in recent years would corroborate. Though it is widely known that derivatives can be used for hedge, extent of effectiveness has not been systematically and scientifically proved. Moreover, individual Traders are extensively using derivatives for speculation ignoring its use as a hedge tool. Hence, it is necessary to assess how far financial derivatives are effective for hedge from Traders point of view.

Derivative market has shown a great potential in the last few years, but the real issues are yet not been resolved. Instruments traded under derivative market and its volume of trade is also increasing day by day, but the main objective .i.e. setting up of different exchanges yet not achieved. On the other hand future prospects of derivative markets are not sound because of the unresolved issues and they are framed as big challenges in the way.

The percentage of physical settlement under commodity derivatives is very less because of the Forward Contract Act, 1952. In this Act, cash settlement of outstanding contracts at maturity is disallowed. In other words, all outstanding contracts at maturity should be settled in physical delivery. To overcome this huddle participants settle their positions before maturity. This Act, needs to be adjusted which is a big challenge in front of derivative market. Regulators and Supervisory bodies are having an eye on the counter derivative market due to its rapid growth. Some OTC (Over the Counter) derivatives are taken as stress relievers in the tough time of global crisis. But the big challenge is to overcome the assumption of the critics that this market is less transparent, weaker capital requirement and systematic risk.

Derivative market requires a setting up of a regulatory system like security market which is regulated by Security Exchange Board of India which is an independent body. On other side derivative is controlled by FMC (Forward Market Commission) which depends upon the funds of Department of Consumer Affairs for the development of this market a sole powered body is required. Both the regulatory authorities’ i.e. SEBI and FMC are also required to work closely for better results Competition of OTC derivatives with the Exchange traded derivatives. Advisors are having the view that this will increase the transparency, liquidity and on the other side clearing and settlement procedure is better. All the above advices are based on the assumption that the existing method of trading in OTC products is all based on telephone trading and there is no clearing system in place. 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 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 Traders 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 Trader and industry is not sufficient. As a result the Trader 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 present study is aimed to study the traders’ awareness and perception towards equity derivative markets in Madurai District.

Scope of the Study

Derivatives were widely used financial tool in the stock markets. The present study focuses only on Equity derivatives excluding other derivatives like commodity derivatives, weather derivatives, etc. Financial derivative as a hedge tool is a topic with wider scope. The present study limits its scope to measure the traders’ perception and awareness on financial derivatives in Indian stock market. Even though there are different types of financial derivatives that are stock futures, stock options, index futures, index options, currency futures and the like being traded in India. The present study is mainly focuses on traders’ perception and awareness towards equity derivative market in Indian stock market. The present study has adopted both primary and secondary data. Geographically, the study is limited to the Indian stock market, as all the sample respondents are from India.

Objectives of the Study

The following are the objectives of the present study

i. To study the existing literature related to the study area.

ii. To present the origin and growth of Equity Derivative Market in India.

iii. To analyse the demographic profile of the traders in Indian stock market.

iv. To analyse the traders perception towards Equity Derivative Market Indian stock market.

v. To offer suitable suggestions based on the findings of the study area.

Primary Data

The primary data were collected directly from the traders who are trading equity derivatives in the National Stock Exchange and Bombay Stock Exchange in Indian stock market through a well devised interview schedule. For data collection, the researcher has interviewed the respondents at different places including their work place. A pre-test was conducted among thirty traders in the NSE and BSE in Indian stock market. Observations are made on the individual differences in the various components of trading. The interview schedule was prepared for the respondents have been pre-tested by the researcher in person. Comments on the question were noted and after careful analysis necessary modification have been made in the interview schedule. In the course of the time, the researcher had experienced some difficulties in getting answers to some of the questions raised and suitable changes have been incorporated before finalizing the well-structured interview schedule.

Secondary Data

The secondary data for the study were collected from books, journals, research articles, magazines, reports, newspapers and websites that too mainly the official sites that are National Stock Exchange and Bombay Stock Exchange in India and annual reports of SEBI. The researcher also visited various university libraries in Tamilnadu.

Natividad Blasco, et. al. [1] conducted a study to explore herding behaviour to identify relationship between rational and emotional components and test whether past return indirectly drive herding behaviour. Bikhchandani model was used to measure herding intensity in both buyer initiated and seller initiated market and the resulted that the herding intensity depends upon past returns and sentiments and confirm the presence of both rational and emotional factors.

Indu Gautam and PC Kavidayal [2] in their study found out to gather the opinion of NSE/BSE members operating in the State of Uttarakhand, on the implications of derivative trading for Indian Capital Market. In total 110 respondents shared their views through the questionnaire and were classified into three groups according to age namely young group (age<=40) with 23.6% respondents, middle aged group (age>40 &<=55) with 46.4% respondents and old group (age>40) with 30.0% respondents. The respondents are also classified on the basis of risk return profile, namely HRHR profile with 44.6% respondents, MRMR with 33.6% and LRLR with 21.6%. This shows that majority of respondents in first set are middle aged and in the second set are risk takers. All respondents completely agree that volumes have increased exponentially after derivatives. Derivatives facilitate price discovery and the possibility of earning good returns. They promote product innovation. Volatility is related of derivatives and increases during expiry. It was also high during Sub Prime crisis. While analysing the responses of respondents on the basis of risk return profile we found that most of the risk takers (HRHR & MRMR profiles) were young respondents whereas the risk averse (LRLR profile) respondents were comparatively older. There is no consensus on three factors with respect to risk return profile, viz, “Participation”, “Return on Investment”, and “Product Innovation”. The risk takers feel that although it is possible to earn good returns in derivative trading but traders do not participate in the market. These respondents like to take risk themselves; hence they are not satisfied with the current level of product innovation. They want more variety and more complex instruments to maximize their profits. On the other hand, risk adverse respondents feel that traders should participate in a limited way and thus returns cannot be high. These respondents only trade in known products hence are happy with the level of product innovation. The difference in perception of respondents could be due to their own different risk appetites. HRHR respondents want their clients to take risk but due to limited participation clients earn limited returns while LRLR respondents do not force the clients to take risk and hence the clients keep holding the assets for a long time and do not play in the market for fear of losing [3].

Framework of Analysis

Analysis of Variance (ANOVA) – the F-Value

Analysis of variance (ANOVA) developed by R.A. Fisher, is a collection of statistical models used to analyze the differences between group means and their associated procedures such as "variation" among and between groups. It is a useful statistical tool or technique used in several disciplines for instance in Psychology, Economics, Biology, Education, Sociology, Management and the like [4]. It is used when multiple sample cases are involved. It can examine the significant difference between two or more sample measures at the same time. The simplest experiment suitable for ANOVA analysis is the completely randomized experiment with a single factor. ANOVA generalizes to the study of the effects of multiple factors. Factorial experiments are more efficient than a series of single factor experiments and the efficiency grows as the number of factors increases. Using this technique inference can be drawn about on the samples drawn from population. It is important in the context of the situations when one wants to compare the means of all populations simultaneously [5]. It is the measurement of distance between individual distributions on given variables. As F-value increases, P-value goes down (i.e. more significance is there between the two means). In all the statistical analysis, the existing differences are tested for statistical significance level at 0.05 or .01 to tolerate errors, i.e. in each analysis 0.05 and .01 significance levels are considered to indicate statistical significance [6]. Tables for each analysis are used to report the findings

Anova Analysis

Anova between Age of the respondents and Value of investment in derivatives

Ho: Age of the respondents does not significant impact on Value of investment in derivatives.

H1: Age of the respondents does significant impact on Value of investment in derivatives.

As per Table 1 of Anova shows that Age of the respondents have a direct relation with the Value of investment in derivatives. They have positive relation as the ANOVA is 6.229. The significant level is 0.000, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Age of the respondents does impact on Value of investment in derivatives.

ANOVA between Age of the respondents and criteria for selection of securities

Ho: Age of the respondents does not significant impact on criteria for selection of securities.

H1: Age of the respondents does significant impact on criteria for selection of securities.

As per Table 2 of ANOVA shows that Age of the Respondents do not have a direct relation with the criteria for selection of securities. They have negative relation as the ANOVA is 2.056. The significant level is 0.106, which is greater than 0.05, so that Anova is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Age of the Respondents do not have a significant impact on criteria for selection of securities.

Anova between Gender of the respondents and Contract maturity period of Trading

Ho: Gender of the respondents does not significant impact Contract maturity period of Trading.

H1: Gender of the respondents does significant impact Contract maturity period of Trading.

Table 3 of ANOVA shows that Gender of the respondents do not have a direct relation with the Contract maturity period of Trading. They have negative relation as the ANOVA is 2.456. The significant level is .118, which is greater than 0.05, so that Anova is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Gender of the respondents do not have a significant impact on Contract maturity period of Trading

Anova between Gender of the respondents and Stock trade option of the respondents

Ho: Gender of the respondents does not significant impact the Stock trade option of the respondents.

H1: Gender of the respondents does significant impact the Stock trade option of the respondents.

As per Table 4 of Anova shows that Gender of the respondents have a direct relation with the Stock trade option of the respondents. They have positive relation as the ANOVA is 9.365. The significant level is 0.002, which is less than 0.05, so that Anova is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Gender of the respondents do have a significant impact the Stock trade option of the respondents.

Anova between Gender of the respondents and criteria for selection of securities.

Ho: Gender of the respondents does not significant of criteria for selection of securities.

H1: Gender of the respondents does significant impact of criteria for selection of securities.

As per Table 5 of ANOVA shows that Gender of the respondents do not have a criteria for selection of securities. They have negative relation as the ANOVA is 0.438. The significant level is .508, which is greater than 0.05, so that ANOVA is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Gender of the respondents do not have a significant impact on criteria for selection of securities.

Anova between Gender of the respondents and Stock Exchange Preference

Ho: Gender of the respondents does not significant impact on Stock Exchange Preference.

H1: Gender of the respondents does significant impact on Stock Exchange Preference.

As per Table 6 of ANOVA shows that Gender of the respondents have a direct relation with the Stock Exchange Preference. They have positive relation as the ANOVA is 167.744. The significant level is 0.000, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Gender of the respondents have a significant impact on Stock Exchange Preference.

Anova between Educational Qualifications and Value of investment in derivatives

Ho: Educational Qualifications does not significant impact on value of investment in derivatives.

H1: Educational Qualifications does significant impact on value of investment in derivatives.

As per Table 7 of ANOVA shows the Educational Qualifications of trader have a direct relation with value of investment in derivatives. They have positive relation as the ANOVA is 3.208. The significant level is 0.023, which is less than 0.05, so that Anova is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Educational Qualifications have a significant impact on Value of investment in derivatives.

Anova between Educational Qualifications and purpose of Investment

Ho: Educational Qualifications does not significant impact on purpose of Investment

H1: Educational Qualifications does significant impact on purpose of Investment

As per Table 8 of Anova shows that educational qualification of the respondents are does not significant impact with the purpose of Investment. They have negative relation as the Anova is 0.879. The significant level is 0.452, which is greater than 0.05, so that Anova is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Gender of the respondents does not significant impact on purpose of Investment.

Anova between Occupational Status and Contract maturity period of Trading

Ho: Occupational Status does not significant impact on contract maturity period of Trading.

H1: Occupational Status does significant impact on contract maturity period of Trading.

As per Table 9 of ANOVA shows that Occupational Status has a direct relation with Contract maturity period of Trading. They have positive relation as the ANOVA is 5.499. The significant level is .000, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Occupational Status does have significant impact on contract maturity period of Trading.

Anova between Occupational Status and criteria for selection of securities

Ho: Occupational Status does not significant impact on criteria for selection of securities.

H1: Occupational Status does significant impact on criteria for selection of securities.

As per Table 10 of Anova shows that Occupational Status has a direct relation with criteria for selection of securities. They have positive relation as the Anova is 2.313. The significant level is 0.058, which is less than 0.05, so that ANOVA is statistically significant. Therefore we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Occupational Status towards criteria for selection of securities do have a significant impact.

Anova between Annual Income and Value of investment in derivatives Ho: Annual Income does not significant impact on value of investment in derivatives.

H1: Annual Income does significant impact on value of investment in derivatives.

As per Table 11 of Anova shows that Occupational Status has a direct relation with value of investment in derivatives. They have positive relation as the Anova is 26.804. The significant level is .000, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Annual Income of the respondents does have significant impact on value of investment in derivatives.

Anova between Annual Income and Type of Derivative are trading

Ho: Annual Income does not significant impacts of type of derivatives are trading.

H1: Annual Income does significant impacts of type of derivatives are trading.

As per Table 12 of Anova shows that Annual Income has not direct relation with Type of Derivative are trading. They have negative relation as the Anova is 0.060. The significant level is 0.942, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Annual Income of the respondents does not have significant impact on Type of Derivative are trading.

Anova between Annual Income and Contract maturity period of Trading

Ho: Annual Income does not significant impact on Contract maturity period of Trading.

H1: Annual Income does significant impact on Contract maturity period of Trading.

As per Table 13 of Anova shows that Annual Income has a direct relation with Contract maturity period of Trading. They have positive relation as the Anova is 16.551. The significant level is .000, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Annual Income of the respondents does have significant impact on contract maturity period of Trading.

Anova between Marital Status of the respondents and Value of investment in derivatives

Ho: There is no significant impact on Marital Status of the respondents and value of investment in derivatives.

H1: There is significant impact on Marital Status of the respondents and value of investment in derivatives.

As per Table 14 of Anova shows that Marital Status of the respondents does not have a direct relation with the value of investment in derivatives. They have negative relation as the ANOVA is 0.175. The significant level is 0.676, which is greater than 0.05, so that Anova is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Marital Status of the respondents does not have a significant impact on value of investment in derivatives.

Anova between Marital Status of the respondents and criteria for selection of securities

Ho: There is no significant impact on Marital Status of the respondents and criteria for selection of securities.

H1: There is significant impact on Marital Status of the respondents and criteria for selection of securities.

As per Table 15 of Anova shows that Marital Status of the respondents does have a direct relation with the criteria for selection of securities. They have positive relation as the Anova is 3.602. The significant level is 0.059, which is less than 0.05, so that Anova is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Marital Status of the respondents does have a significant impact on criteria for selection of securities.

Anova between Marital Status of the respondents and Stock Exchange Preference

Ho: There is no significant impact on Marital Status of the respondents and Stock Exchange Preference.

H1: There is significant impact on Marital Status of the respondents and Stock Exchange Preference.

As per Table 16 of Anova shows that Marital Status of the respondents does not have a direct relation with the Stock Exchange Preference. They have negative relation as the Anova is 1.551. The significant level is 0.214, which is greater than 0.05, so that Anova is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Marital Status of the respondents does not have a significant impact on Stock Exchange Preference.

Findings

i. The significant level is 0.000, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Age of the respondents does impact on Value of investment in derivatives.

ii. The significant level is 0.106, which is greater than 0.05, so that ANOVA is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Age of the Respondents do not have a significant impact on criteria for selection of securities.

iii. The significant level is 0.118, which is greater than 0.05, so that ANOVA is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Gender of the respondents do not have a significant impact on Contract maturity period of Trading.

iv. The significant level is 0.002, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Gender of the respondents do have a significant impact the Stock trade option of the respondents.

v. The significant level is 0.508, which is greater than 0.05, so that ANOVA is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Gender of the respondents do not have a significant impact on criteria for selection of securities.

vi. The significant level is 0.000, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Gender of the respondents have a significant impact on Stock Exchange Preference.

vii. The significant level is 0.023, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Educational Qualifications have a significant impact on Value of investment in derivatives.

viii. The significant level is 0.452, which is greater than 0.05, so that ANOVA is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Gender of the respondents does not significant impact on purpose of Investment.

ix. The significant level is .000, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Occupational Status does have significant impact on contract maturity period of Trading.

x. The significant level is 0.058, which is less than 0.05, so that ANOVA is statistically significant. Therefore we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Occupational Status towards criteria for selection of securities do have a significant impact.

xi. The significant level is .000, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Annual Income of the respondents does have significant impact on value of investment in derivatives.

xii. The significant level is 0.942, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Annual Income of the respondents does not have significant impact on Type of Derivative are trading.

xiii. The significant level is .000, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Annual Income of the respondents does have significant impact on contract maturity period of Trading.

xiv. The significant level is 0.676, which is greater than 0.05, so that ANOVA is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Marital Status of the respondents does not have a significant impact on value of investment in derivatives.

xv. The significant level is 0.059, which is less than 0.05, so that ANOVA is statistically significant. So that we reject null hypothesis Ho, and accept alternate hypothesis H1 that is Marital Status of the respondents does have a significant impact on criteria for selection of securities.

xvi. The significant level is 0.214, which is greater than 0.05, so that ANOVA is statistically not significant. So that we accept null hypothesis Ho, and reject alternate hypothesis H1 that is Marital Status of the respondents does not have a significant impact on Stock Exchange Preference.

Suggestions

Following are the consolidated list of suggestions for the purpose.

i. Since people don‘t prefer to invest in Indian Stock Market owing to lack of their knowledge on the Market and prospects of this mode of investment, it is necessary to drive awareness campaigns by the regulatory bodies and brokerage houses with the backing of the government.

ii. In order to counter negative word of mouth, successful traders are to be encouraged and motivated to air their success stories at different forums.

iii. Since people have fear of being cheated, workshops to train the potential traders to have knowledge on how to trade by own.

iv. A mechanism may be developed to ensure the traders that the investment could be channelized by the brokerage houses with some sort of assurance of a considerable percentage of principal amounts so that people having no time to trade by their own could depend on the brokerage houses with confidence.

v. The concept of General Insurance may be extended to the amount invested in Indian Stock Market for which the premium may be collected from the traders.

vi. To keep the interest of the traders in mutual fund the companies will play a vital role to attract the traders to invest in mutual fund so for that companies should bring such plans which is having very low risk

vii. As per the study the traders wants safe returns on their investment and all traders know the risk in share market and which is the main reason traders avoid to invest in shares and equities or mutual fund because of the fear of losing the money

viii. The Market should maintain a good relationship in reality and should render of quick services according to the customers, in case of necessity.

ix. The Capital market should go for doorstep services, which would help the customers to get educated regarding the services and be the prospective customers.

x. The Capital market should have a separate customer’s care department so that they keep in touch with customers which make them feel they are cared loved needed.

xi. Public awareness can be through any media, but we see that the awareness is through the customers of the Capital market through advertisement which would more the company feel great and even it can reduce its promotional costs and time.

xii. The brokers of the stock broking company should be profit centered than brokerage centered for their customers.

xiii. There is a need to spread more awareness among the existing and potential traders.

xiv. Findings of the study suggest that more efforts are needed to spread awareness, especially among the women. This is because of their lower participation compared to the equity assets under their ownership.

xv. These finding provide a great opportunity for intermediaries and asset management companies to target and market equity asset instruments to enhance participation and exposure.

xvi. Asset management companies should design more products with capital protection element as the most retail traders perceive ‘capital erosion’ as the top risk while investing in equity assets. Based on the given finding, regulators can also think of some insurance scheme that protects capital of the beginners or small traders to boost participation.

xvii. It has been established that traders’ risk to return perceptions are vastly different and depend on demographic variables. Market players should leverage the findings of this study and help traders in fulfilling their investment objectives and goals.

xviii. Investment experience of the traders in the market is a crucial variable that has a significant impact on investment decisions. Intermediaries and brokers should take cognizance of this finding and leverage it to customize their offerings appropriately for traders.

xix. Among several mutual fund schemes, retail traders’ top choice is to invest in ‘growth funds’. On the other hand ‘index funds’ are the least preferred. Asset management companies should consider these preferences for designing and selling mutual fund products.

xx. Two leading stock exchanges have introduced 75 different meaningful indices. However, still SENSEX and NIFTY are the most preferred indices for retail traders. More awareness needs to be spread for the newer indices as they are useful indicators of sectorial performance.

xxi. More traders prefer corporate and online over traditional brokers/ intermediaries. Traditional brokers should adopt technology and modern ways, not only to grow but sustain their share in the market.

xxii. It is found that majority of the traders still prefer newspapers and business channels on TV as a medium to access investment information. Hence it is essential for the market players to continue using these mediums for spreading awareness. India is not yet ready to bypass these traditional mediums for websites and Apps.

xxiii. The Technological up gradation such as online trading, online consultation of stockbrokers and online availability of audited annual reports should be introduced in capital market for its growth and to attract traders.

xxiv. Risk minimizing strategies like hedging, stock index futures and stock index options should be introduced in capital market so as to attract rational traders

xxv. The study suggests that Government should look forward to setting up a super regulator who can take care of these various regulatory arbitrage/risk issues or there should be joint committee of all the regulatory bodies to look into such concerns of the market from overall perspective.

xxvi. This study can be used by the regulating authorities and broker houses to increase awareness among the traders about derivatives.

xxvii. One should invest in secured and risk-free investments rather than high-risk, highly profitable investments.

xxviii. Tracking the market environment better with sound knowledge about a particular stock would result in better returns.

xxix. Since many of the entities in this study are independent of each other, there is need to analyse on a buying decision specifically for respective stocks

xxx. People with less experience can also be high profit makers when decisions are based on intricate fundamental and technical analyses. xxxi. The Awareness programmes should be conducted at various places in order to attract women traders.

xxxii. The Awareness regarding equity derivatives should be spread in rural areas because those people are financially stable but they have no knowledge to invest their surplus funds.

xxxiii. Traders are the life blood of the capital market, so safety, profitability and liquidity of their funds should be ensured.

Conclusion

The success of a country’s economy largely depends upon the growth of the capital market to and the growth of the capital market depends upon the proper understanding of the small individual traders (Household) and attracting them towards the capital market, the reason is that all the individual traders have got the major chunk to invest as they have got more than what the spent and this holds quite opposite in case of all corporate entities. The Derivatives are financial contracts whose value is derived from some underlying asset. These assets can include equities and equity indices, bonds, loans, interest rates, exchange rates, commodities. The contracts come in many forms, but the more common ones include options, forwards/futures and swaps. This study has been to trader compare among different types of derivatives for reducing risk and increase the return. This is important if one wants to understand the determinants of use of each type of derivatives, due to the fact that traders of derivatives often use more than one type of derivatives. Modern traders are rapidly informed than their predecessors. Modern traders want future security while investing. So, every stockbrokerage agency should make their strategies for the benefit of the traders on a long term basis. This study would be of great use for traders and financial intermediaries who make decisions regarding investment. This study will help the traders and investment consultants in identifying profitable investment avenues. Trader’s preference for equity will help the policymakers in formulating strategies and will also help the credit rating agencies in rating the investment instruments. Stock exchanges can introduce technological advancement in trading. In short, this piece of research is of immense use for all the three group of players in the capital market viz. the traders, issuers and the intermediaries.

References

1. Blasco N, Corredor P, Ferreruela S, “Market sentiment: a key factor of traders imitative behaviour.” Account Finan 52 (2012): 663-689.
2. Gautam I, Kavidayal PC. “Perception of Market Participants towards Derivative Trading: A study of Uttarakhand.“ Int J Manag IT Eng 6 (2016): 191-207.
3. Kavitha C. “Traders Attitudes towards Stock Market Investment.” Int J Scientific Res manag 3 (2015): 3356-3362.
4. De Weaver MA, Shannon R. “Waning vigilance and the disposition effect: Evidence from Thailand on individual trader decision making.” J Socio Econ 39 (2010): 18-23.
5. Grinblatt M, Matti Keloharju M. “The investment behaviour and performances of various trader types: A study of Finlands unique data set.” J Finan Econ 55 (2007): 43-67.
6. Barberis N, Thaler R. “Chapter 18 A survey of behavioral finance.” Handbook Econ Finan 1 (2003): 1053-1128.