A Study on the Derivatives Market in India

Derivatives are one of the most multifaceted instruments. The word derivative comes from the word to derive. It indicates that it has no independent value. A derivative is a contract whose value is derived from the value of another asset, known as the underlying asset, which could be a share, a stock market index, an interest rate, a commodity, or a currency. The underlying is the identification tag for a derivative contract. When the price of the underlying changes the value of the derivative also changes. Without an underlying asset, derivatives do not have any meaning. For example, the value of a gold futures contract derives from the value of the underlying asset i.e., gold. The prices in the derivatives market are driven by the spot or cash market price of the underlying asset, which is gold in this example.The basic purpose of these instruments is to provide commitments to prices for future dates for giving protection against adverse movements in future prices, in order to reduce the extent of financial risks.

As the initial a step towards the introduction of derivatives trading in India, SEBI set up a 24 member committee under the chairmanship of Dr. L. 17, 1998 recommending that derivatives should be declared as securities so that regulatory framework applicable to the trading of securities could also govern the trading of derivatives. Subsequently, SEBI set up a group in June 1998 under the chairmanship of prof.J.R.Verma, to recommend submitted its report in October 1998. It worked out the operational details of the margining system, a methodology for charging initial margins, membership details and net-worth criterion, deposit requirements and real-time monitoring of positions requirements. The exchange-traded derivatives started in India in June 2000 with SEBI permitting BSE and NSE to introduce the equity derivative segment. To begin with, SEBI approved trading in index futures contracts based on nifty and Senses, which commenced trading in June2000.later, trading in index options commenced in June 2001 and trading in options on individual stocks commenced in July 2001. Future contracts on individual stocks started in November 2001. Metropolitan Stock Exchange of India limited (MESI) started trading in derivative products in February 2013. Derivatives market in India has a history dating back in 1875. The Bombay Cotton Trading Association started future trading in this year. History suggests that by 1900 India became one of the world‘s largest futures trading industry. However after independence, in 1952, the government of India officially put a ban on cash settlement and options trading. This ban on commodities future trading was uplift in the year 2000. The creation of National Electronics Commodity Exchange made it possible.In 1993, the National stocks Exchange, an electronics based trading exchange came into existence. The Bombay stock exchange was already fully functional for over 100 years then.Over the BSE, forward trading was there in the form of Badla trading, but formally derivatives trading kicked started in its present form after 2001 only. The NSE started trading in CNX Nifty index futures on June 12, 2000, based on CNX Nifty 50 index

Commodity derivatives: Commodity derivatives are investment tools that allow investors to profit from certain commodities without possessing them. The buyer of a derivatives contract buys the right to exchange a commodity for a certain price at a future date. The buyer may be buying or selling the commodity.

Forwards: Forwards are over the counter (OTC) derivatives that enable buying or selling an underlyingon a future date, at an agreed upon price. The terms of a forward contract are as agreed between counterparties. Futures: Futures are exchange traded forwards. A future is a contract for buying or selling a specific underlying, on a future date, at a price specified today, and entered through a formal mechanism on an exchange. The terms of the contract are specified by the exchange.

An option is a contract that gives the right, but not an obligation, to buy or sell the underlying on or before a stated date and at a stated price. While buyer of option pays the premium and buys the right, writer/seller of option receives the premium with obligation to sell/buy the underlying asset, if the buyer exercises his right. Swaps: A swap is an agreement made between two parties to exchange cash flow in the future according to a prearranged formula. Swaps are, broadly speaking, series of forward contracts. Swaps help market participants manage risk associated with volatile interest rates, currency exchange rates and commodity prices. Exotic Derivatives: Exotic Derivatives usually refers to more complex, unusual and specific derivative contracts that depend on the value of some underlying asset or defined set of assets. LEAPS: LEAPS (an acronym for Long Term Equity Anticipation Security) are options of longer terms than other more common options. In traditional short-term options, LEAPS are available in two forms, calls and puts.

• It helps the investors to construct a diversified portfolio.

• This study suggests investors about investment in futures, options, and swaps.

• It is used to know the risk management in derivatives.

• To identify and compare the futures, options, and swaps in derivatives in Indian stock market.

• To illustrate the growth and performance of futures and optionsand swaps.

The relationship between risk and return from derivative trading calls for consideration of investor‗s satisfaction level in relation to different variables. The present study was conducted in Ernakulam district of the Kerala state. The level of satisfaction and attitude of the investors were analysed with the help of different statistical tools and methods. The method used in the study is exploratory as it utilizes scoring of the variables. The collected data contains both the qualitative and quantitative data. Accordingly, the study uses both qualitative and quantitative techniques for the analysis of data. The statistical analysis comprised of two stages. The first stage examined the descriptive statistics of the measurement items and assessed the reliability and validity of the measure applied in this study. The second stage tested the proposed research model and this involves assessing the contributions and significance of the manifest variables path coefficients. The data were analyzed via SPSS 20.0 for Windows. Descriptive statistics were used to describe and summarize the properties of the mass of data collected from the respondents. Parametric statistics like independent sample Z test and the one-way analysis of variance were used for comparison of the factors considered between different level of the demographic variables. A level of 0.05 was established a priori for determining statistical significance. The main objective of the study is to evaluate various problems faced by the F&O trading to an investor in Ernakulam District and their satisfaction level with F&O trading. In the present study, we converted opinion into a score for some variables. So, the answer may be subjected to random variation and is influenced by psychological factors. Hence it is better to use psychometric scale development approaches to evaluate the relationship. The best model for testing the convergent validity and for modeling the best method is Structural Equation Model or confirmatory factor analysis. For the analysis initially an input model was developed by using AMOS-18 graphics. An assessment of the statistical reliability is necessary before any further validation analysis. Reliability refers to degree of dependability or consistency of a scale. Unreliable scale will lack consistency of measuring the same item to the extent. Now a day, particularly for field survey, internal Consistency is estimated by using Cronbach‗s alpha. An alpha value of 0.70 or above is criterion for demonstrating strong internal consistency, alpha value of 0.60 or above is significant. and final Cronbach‗s alpha for each of the construct considered. Result shows that all of the constructs has reliability greater than 0.6 so we proceed for further analysis.

The survey was conducted among the 175 investors in Ernakulam District. The investors were categorized on the basis of age, sex, education, occupation and monthly income. The influences of demographic control variables, that is, gender, age, education, income levels, and occupation towards the various accepts of financial literacy. The analyses were conducted using independent sample Z test and one way ANOVA.

Table 4.2 states that gender wise classification of the respondents in Ernakulam district. 84 percent of the respondent constitute male respondents and 16 per cent are female respondents.

Source: Primary data Sex wise classification of investors are presented in the Figure 1. Of the total sample (175 investors) of investors in Ernakulam district, 147 respondents are male investors and rest of the respondents (28 investors) are female respondents Source: Primary data H0a: There is no significant difference in satisfaction level of male and female investors. H1a: There is significant difference in satisfaction level of male and female investors. An independent sample Z test are often used to compare the satisfaction level of variables for two different groups of participants, that is, male and female investors. Hence a Z test was conducted, and the results were shown in the Table 3

Source: Primary data The result shows that no significant difference in the satisfaction level exist between the male and female investors as the p value in these cases is greater than 0.05. So we accept the H0a hypothesis.

Age wise classification of respondents are presented in the Table4. The table reveals that majority (41.7 percent) of the respondents are included in the 31–40 category. 30.3 percent of the respondents are 20-30 years‗ category. 16 percent of the respondents are 41-50 category and only 12 percent of the respondents were above 50 age category.

Source: Primary data. Figure2 shows that investors are categorized into different age groups. Majority of the investors belonged to 31-40 age category and the next majority comes to 20-30 category. Source: Primary data

H0b: The level of satisfaction does not differ with age. H1b: The level of satisfaction differs with age. A one sample analysis of variance (ANOVA) is used to test hypotheses about means when there are three or more groups ofone independent variable. The result of the analysis is exhibited in Table 5

The results of the ANOVA reveals that assumed significance value( p) is less than 0.05. The results proved that the level of satisfaction differ with age. We reject the hypothesis H0b.Since the ANOVA test indicate that the significant difference exists among the different Age group for the Satisfaction. The present study was also conducted a post hoc test (multiple comparison test) for identify which among the age group differs significantly. This was presented in the Table 6.

The result of the analysis indicates that differences exist between all the groups except 40-50 years and above 50 years.

The level of education of the respondents are shown in the Table 7. It is clearly evident from the table that majority of the respondents (60 percent) are professionals and remaining of them (40 percent) are qualified up to a graduate level.

Source: Primary data Figure 3 presents the education wise classification of the investors in Ernakulam district. The study reveals that majority of the investors (60 percent) are professionally qualified while others (40 percent) have completedtheir graduate degree. Source: Primary data H0b: There is no significant difference in the satisfaction level of investors in relation to education. H1b: There is significant difference in the satisfaction level of investors in relation to education. One way ANOVAis used to test hypotheses about means when there are three or more groups of one independent variable. The result of the analysis is exhibited in Table 8.

The results of the ANOVA shows that assumed significance value, (p) is less than 0.05. The results proved that the level of satisfaction differ with education of the respondent. We reject the hypothesis H0b.Since the ANOVA test indicate that there is significant difference in level ofsatisfaction in respect of education. Therefore, we accept H1b hypothesis.

Occupation wise classificationreveals that 60 percent of the respondents are private sector employees, 16.6 percent are professionals, 9.1 percent are businessmen and rest of the respondents are government servants, retired employees and others engaged in daily wage activities and unemployed persons. This was exhibited in the Table 4.

Source: Primary data Figure 4 showedthe occupation wise classification of investors. Majority of the respondents are private sector employees (60 percent), followed by professionals (16.6 percent), businessmen (9.1percent) andothers (including daily wage earners and unemployed persons) which constitute 7.4 percent.

H0b: The level of satisfaction does not differ with occupation. H1b: The level of satisfaction differs with occupation. A one sample analysis of variance(ANOVA) is used to test hypotheses that there is significant difference in the satisfaction level of investors in derivative trading. The result of analysis is exhibited in the Table 10.

The results of ANOVA proved that significance level, P< 0.05. The results of analysis reveal that the level of satisfaction differ with occupation of the investors. Hence we reject the hypothesis H0b.Since the ANOVA test indicate that there is significant difference in the satisfaction level of investors. Therefore, we accept H1b hypothesis, the level of satisfaction differs with occupation. The present study also conducted a post hoc test for identifying the investors level of satisfaction in relation to occupation revealed that their satisfaction level in derivative trading is significantly different. This was presented in the Table 11.

The result of analysis indicates thatthere is no significant difference in the opinion of investors. These investors are engaged in government service, semi- government service, professional service and other services.

The income wise classification of investors are presented in the table 12. The results shows that majority of the respondents (37.7 percent) earn Rs. 41,000 to Rs. 50,000 per month. Around 30.3 percent of the respondents earn more than Rs.

Source: Primary data Figure 5 illustrate the monthly income of the investors in Ernakulam district. Out of the 175 respondents, 37.7 percent earn a monthly income of Rs. 41,000 to Rs. 50,000, followed by 30.3 percent of the respondents‗ earnings was above Rs. 50,000. 20.6 percent of respondent earns monthly income of Rs. 31,000 to Rs. 40,000. Source: Primary data

H0b: The level of satisfaction does not differ with income. H1b: The level of satisfaction does differ with income. A one sample analysis of variance (ANOVA) is used to test the hypotheses that there is no significant difference in the satisfaction level of investors. The result of the analysis is shown in the Table 13.

Source: Primary data The results of the ANOVA proved that assumed significance valueis less than 0.05. The results satisfaction level of investors in Futures and Options trading activity. A post hoc test was also conducted to identify whetherthe income groups differs significantly. This was presented in the Table 14.

The result of the analysis indicates there is significant variations between all the income groups except Rs. 20000 to Rs. 30000 income category and Rs.40, 000 to Rs 50,000 category.

Derivatives trading is dominating the commodity and financial market all over the world. Trading in derivative instruments require familiarization with basics, its purpose, trading practices,type of instrument, level of risk involved, experience and frequency in trading, amount of risk covered, and sources influenced in trade.

An insight into the derivative trading showed that the experience of respondents in the stock market has a significant role in derivative trading. Majority of the respondents (51.9 percent) has an experience of 5 years and below, followed by respondents (38.9 percent) with 6 to 10 years. Hardly 2.9 percent of respondents has an experience ranging from 15 years and above.

Source : Primary Data Figure 6 shows that experience of investors in the stock market. Out of the 175 respondents 51.4 percent has an experience of 5 years and below. Investors (38.9 percent) had an experience ranging from 6 to 10 years. The remaining respondents (6.9 and 2.9 percent) had an experience of more than 10 years. Source: Primary data

In Table 16 the experience wise classification of the investors engaged in derivative trading shows that most of the investors(34.3 percent) trading in derivatives has an experience of 3 to 4 years, followed by investors (30.9 percent) with an experience of 1 year or less. Out of the 175 investors, 29.7 percent of the investors had an experience ranging from 1 to 2 years.

Source: Primary data percent of the investorshad year exposure of 3 to 4 years in the trading,30.9 percent with less than 1 year experience,29.7 percent with 1 to 2 years of experience and a minority (5.1 year) with 5 or more than 5 years of experience. Source: Primary data

The frequency in derivative trading in among investors in Ernakulam district is shown in the Table 17. Majority of the investors in Ernakulam (39.4 percent) trade in derivatives frequently. Investors doing occasional trading constitute 34.9 percent. Only 14.3 percent of the investors always trade in derivatives.

Source: Primary data Figure 8, shows the frequency of derivative trading among 175 respondents. The figure shows that almost every investor in Ernakulam is trading in derivatives frequently (39.4 percent), followed by investors doing occasional trading (34.9 percent). Only 14.3 percent of investors are always engaged in Future and Options trading. Source: Primary data

Table 18 shows the level of risk tolerance among the investors engaged in Futures and Options trading in Ernakulam District. Among the 175 investors, 48.6 percent are ready to accept a medium level of risk in their investment.26.3 percent of the investors are willing to face high level of risk in their investment meanwhile only 16 and 9.1 percent of the investors ready to take very low risk on their investment.

Source: Primary Data The investor‗s level of risk endurance in their investment is shown in the figure 9. Majority of the respondents (48.6 percent) are ready to accept medium investment risk, followed by 26.3 percent with high investment risk, 16 percent with low investment risk and 9.1 percent with very low investment risk. Source: Primary Data

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Assistant Professor, Jain Deemed To Be University, Bangalore