“Derivatives are financial weapons of mass destruction.” -Warren Buffett
The financial Derivatives presently have become an integral part of the financial system of India as well as at international level. The study has found the influenced almost every aspect of capital and money markets all over the world extending from investing, raising of funds and managing of the risk.
The financial Derivatives are risk management, which originate their value from an underlying asset. According to the Financial Accounting Standards Board (FASB)'s Statement of Financial Accounting Standards No. 133 (FAS 133) - Accounting for Financial Derivative Instruments and Hedging Activities, an underlying is a particular interest rate, security price, commodity price, foreign exchange rate, and other variable of The underlying asset can be bullion, share currency and index, as well as market interest, the Banks, Securities firms, and investors to hedge risks, to gain access to inexpensive money and to make profit the use of financial derivatives. The financial derivative market instruments that are linked to a specific financial Model and through which specific financial risk can be traded in their own financial aspect. The present value of a financial derivative originates from the price of an underlying assets. Different debt securities and no principal is advanced to be repaid and no investment income accrues (IMF). Derivatives contain the futures, forwards, options and swaps, and these variable can be combined with each other or traditional securities and loans to create hybrid instruments. These instruments are used for risk measurement by hedging i.e. taking opposite position in the futures market.
THEORETICAL FRAMEWORK OF THE RESEARCH STUDY:
The Examine stock market volatility before and after the outline of index futures in 8 countries. The research study has found that the index futures had no significant effect on the spot markets price value of the firm in the selected countries. The research study found that the contribution of option market to price discovery, option market price finding is related to trading volume and spread the both market, and stock volatility. Price finding across the option strike the price is related to leverage, trading volume, and spread. The research results are consistent with theoretical discussion that drawn for the investor1.
The researcher Investigate the impact of Taiwan Index futures Market trading on spot market price volatility using GJR GARCH model and the study has drawn the conclude that the trading of TAIEX futures had a major impact on spot price volatility, although the trading market of MSCI Taiwan did not shown that the insignificance and the effect of Index Futures on stock market is studied. A new model, which is based on the 3-factor model. In the EGARCH-type volatility in Nelson (1991) and non-normal distribution of SSAEPD used. Fama-French 25 portfolios for US stock market (1951-2007) are analysed 2.
The research study is Investigates behaviour of Financial Market volatility after institution of financial derivatives by adopting the GARCH model. Using a sample of 30 stocks taken randomly from the NIFTY and finally the results were shown that the positive impact on the spot price value in the market 3.
The research paper found that the there is a decrease in volatility of market price in the underlying stock market and increased market efficiency then subsequent the launch of NIFTY-linked futures impact of the selected market portfolio4.
The authored he has analysed the impact of financial derivatives market on the volatility of Indian stock market through ARCH/GARCH technique using SandP CNX NIFTY as a proxy for Indian market5.
The research study has examined the impact of financial derivatives trading on the volatility of Indian stock market using Standard Deviation as a measure of volatility is major impact on the market price6.
The present research paper examined the volatility in the Indian stock market after selected the market share value in the futures and option contracts. Numerous volatility forecasting approaches have been used such as ARCH, GARCH and EGARCH models using the data for a sample period of 10 years to determine the market price of the firm7.
Examine stock market volatility before and after the introduction of index futures in 25 countries. They find that index futures had no significant effect on the spot markets in all the countries excluding US and Japan8.
The research study has Investigate the impact of Taiwan Index futures trading market price on spot price volatility using GJR GARCH model and conclude that the trading of TAIEX futures had a major impact on spot price volatility, although the trading of MSCI Taiwan did not and The research Study the impact of the futures trading market price on spot market volatility. Finally the study has found that the used data from both the underlying and non-underlying stocks value in the Malaysian stock exchange9.
This research paper studies the volatility inferences of the summary of derivatives on stock market volatility in India expending the SandP CNX Nifty Index as a standard. To account for non-constant error alteration in the return series, a GARCH model is fitted by integrating futures and options dummy variables in the provisional variance equation. The paper find gathering and determination of volatility before and after derivatives, while listing seems to have no balance effects on market volatility. The post derivatives period shows that the understanding of the index returns to market returns and any day-of-the-week effects have vanished. That is, the nature of the volatility patterns has altered during the post-derivatives period10.
The study has explained the ARCH, GARCH, and EGARCH models and the estimation of their parameters using maximum likelihood technique in the financial derivative market, to determine the market price and risk of market portfolio. His article aims at studying the stock price behaviour modelling the volatility of the Indian Stock Market using SandP CNX Nifty to proxy the Indian Stock Market over the twelve years period starting from October 1st, 2000- September 30th, 2012 11.
The authored research study has examined the Single Stock Futures ‘contracts trading on the Karachi Stock Exchange. The main purpose to do the Research the changes in the return volatility of the underlying stocks using an augmented GJR-GARCH model as well the more traditional measures of return volatility12.
Theoretically examined the impact of index futures on volatility and noise trading. She has analysed contrasting theoretical approaches and empirical evidence relating to the issue and the authored explored index futures had no significant effect on the spot markets in all the countries excluding US and Japan13.
The introduction of the TAIEX futures trading improves the efficiency of information transmission from futures to spot markets. The authored the build the relationship of the study to find a reduction in spot market volatility after the introduction of index futures in the present market value and determine the risk of share market14.
The study illustrate about the ARCH, GARCH, and EGARCH models and the estimation of their parameters using maximum likelihood technique in the financial derivative market to evaluate the performance of market financial statement. In his research paper concluded that about the GARCH best explains the performance of stock prices and EGARCH best explains the returns series15.
STATEMENT OF THE PROBLEM:
1. The Present Research Paper perception that financial derivative market can prime to deterioration in volatility in financial derivative. The impact of interchange derivatives on the volatility of spot market price is widely debated and the role of financial derivatives has been the focus of sufficient current attention of the research paper market value price.
2. The research paper has found that the Increased on financial derivatives market has been place into practice, not making an allowance for the lack of reliable statistical evidence in the financial derivatives trading is associated with change in volatility and risk of the Indian stock market.
3. The Nevertheless the research study cannot indifference the benefits of financial derivatives market as it plays an important role in price finding, portfolio diversification and hedging in the Indian capital market from the last 5 years.
4. The present research study is to examine the role of Index and Stock futures trading on the volatility and systematic risk of the Indian spot markets. The aim of this study is to bring the perspectives to the ongoing debate about the role of derivatives in capital markets.
5. The study find the further observation from the literature review there are still dissimilarities on what role financial derivatives trading play about the stock market volatility and financial risk system. Huge number of studies has been previously made to address this issue but they produce contradictory results has declared.
NEED OF THE STUDY:
1. The research paper has consider the Instructions on interest rate risk taken by financial derivative market in the Indian context apply to measure and control interest rate risk that occurs in both assets and liabilities and off-balance sheet.
2. The study has consider the Interest rate risk analysis is performed on maturity bands consisting of an IR Gap type report, technique based on the gap between assets and liabilities sensitive at interest rate.
3. Assets and liabilities are grouped in assets and liabilities with floating interest rate. The gap is calculated as difference between assets and liabilities in each maturity band.
4. The financial Derivatives are continuously fabricated with prevailing market rates. Contracting a swap receiving the fixed rate will suggest receiving the current fixed rate for the selected maturity. Contracting a swap getting the variable rate will infer receiving the current rate for the selected short maturity of the variable rate.
5. The impact of financial derivatives on the volatility of spot market is widely debated and the role of financial derivatives trading has been the focus of plenty recent attention. the research study found the lack of significant statistical evidence that financial derivatives trading is connected with alteration in volatility in the Indian stock market.
OBJECTIVE OF THE STUDY:
1. To study the financial risk Management in Indian equity market with focus on the derivatives Market.
2. To study the role and impact of Risk Management on Indian capital market in the context of Financial Derivatives Market.
3. To determine the investor’s perceptions regarding effect of future contract on stock expected return in the Indian stock market.
4. To study comparative effect of future contract on stock Market expected return in the Indian financial derivative market.
HYPOTHESIS:
1. There is no significant difference between Financial Derivatives as an effective risk management Model
2. There is a significant difference between mean values for Derivatives associated Indian financial market by increasing spot price volatility.
3. The Derivatives help the investors to adjust the financial risk and return to create and manage portfolio carefully in stock market.
4. There is an effect of financial derivative on expected stock return in the stock market.
5. There is an effect of future contract on expected stock price volatility on stock
METHODOLOGY:
This research paper has adopted the systematic method consisting of articulating the problem, framing a hypothesis, collecting the facts or data, analyzing the facts and reaching positive conclusions either in the form of solution(s) towards the concerned problem or in certain generalizations for some theoretical formulation. The present study utilizes. Descriptive research design is a scientific method which contains observing and describing the behavior of a subject without influencing it in any way.
DATA COLLECTION:
The research study has used the technique to collect the data source purpose the previous stock price time series data and the data on catalogs have been collected from the authorized website of National Stock Exchange of India and capital line. Other hand data collection include various Reports, journals, and internet. The data set contains of time series data on 75 separate stocks and 2 indices from National Stock Exchange (NSE). The NSE is leading stock exchange and records highest trading volume in the financial derivatives segment. The stock value of present future price in stock and 75 stocks is not present in future price.
DATA ANALYSIS AND INTERPRETATION:
The Black-Scholes Models determining the risk, efficiency of market option and price in the Indian financial derivative market:-
According Black and Scholes (1973) are pioneers in pricing option theory. They started from the Premise that if options are properly evaluated, there can be certainly no gain from the sale and purchase of options and underlying assets. Using this principle, the Research study presented a method for formative the theoretical value of an option. Black-Scholes model for influential the price of a European option is widely used in practice because it requires knowledge of observable parameters. The present research paper has estimate of early exercise premium (EEP) is difficult because simultaneous liquid markets for Indian capital market with reference to NSEandBSE identical options do not exist in the present available data. In this Research study have used American put options model to evaluate the financial derivative risk with futures contracts on as underlying asset, these being the most liquid options. The analysed period from 2010 to 2016.
The research paper is try to investigate if the exercise premium EEP of an Indianputoption. The needy on the degree in which the option of the derivative market is in the money, the time to maturity, the risk free rate and the volatility. The following model was used in this sense:
EEPpit = C1+ C2 Mt +C3 Tt+C4 Yft+C5 σt+ εI,t
EEPpit= the exercise premium before maturity for the Indian put option;
M = the degree in which the option is in the money;
T = the time to maturity of the portfolio
r.f = risk free rate of the individual portfolio
σ = volatility in the present market value consideration
ε – Residual variable of the research paper.
In the same sequence of the above equation the research paper has predictable EEPp the Research study have subtracted the premium, calculated with the aid of the PCP relationship for Indian options market value, from the market price of the NSE andBSE.
EEPp = P-P
Where:
P - The price of the Indian put option;
After discussion of the above equation the Presents Research paper declare the results obtained when volatility is used. Using volatility leads to a surprising result opposite to investors’ expectations. Yet, other financial studies using the same type of volatility have identified the same negative impact of the volatility on the exercise premium.
Table 1. Modelling EEP for Indian put options using moneyness, time to maturity, risk free rate and volatility as exogenous variables.
|
EEPp =C1+C2M+C3T+C4Yf+C5σist |
|
|
R2 |
0.650132 |
|
Adjusted R2 |
0.72647 |
|
C1 |
-0.25638** (-0.68032) |
|
C2 |
0.362015*** (9.03215) |
|
C3 |
0.56820 (2.369850) |
|
C4 |
-0.35980** (-3.02563) |
|
C5 |
0.56890*** (-5.032569) |
Source: SPSS Output, ** indicate that significant at 5% level, and *** indicate that significant at 10% level.
The table -1 has explored the results the coefficient of M is progressive and statistically significant in the present table, which means that the EEP intensifications with M. as M increases and the put option is more in the money market. The value of the put option increases with the time to maturity which leads to a more valuable exercise premium before maturity.
The interest rate and volatility effects depend on the degree in which the option is in the money. As shown in table, the risk free rate and volatility coefficients are negative. As far as the interest rate is apprehensive, it is increases the present value of the slowdown theprice diminishes leading to the advantage of the current price of the futures contract on the option’ strike price of the financial derivative market.
Model of the economy: - To test the hypothesis impact of Financial Risk Management on Indian capital market in the context of Financial Derivatives
The research paper has consider two financial assets in this view the study focused on the price per share of the financial derivative its related to the financial risk Management of selected portfolio is represented by B (t ) and other on is stock symbolically represented by S (t ). The portfolio is a pair values for the determine purpose it will shows that the (b (t), S (t)) and containing of the number of shares of b (t) and S (t) held at time, in the same sequence of the research study the value of the portfolio or wealth W (t) is
W (t) = portfolio (t) B (t) + stock (t) S (t)
The research paper is find that the further difference between financial risk and market share impact on the financial derivative market, according above equation extension is that the developed the following equation to determine the financial risk in derivative market.
b (t) = b+ (t) – b – (t) and S + t – s – (t)
Where (b + (t), b- (t) denoted the financial risk (“+ “) and market share value (“-“) correspondingly (S + (t), s _ (t) symbolised market value of the stock (‘+’) EPS (;-;) Correspondingly. The rebalance of the selected portfolio through stock market trading strategy in financial derivative market present (β (t) S (T))
β (T) = (β – (t), β + (t) and S (t) = (S – (t), S+ (t)
Denoting the respective rates at which market share value in the selected financial derivative market in the portfolio are financial risk and impact of the EPS. In particular, the present research study relate the strategy to the portfolio can employed the market price value in the below equation
; ,
; ,
Such that 0 <β + (t) <γ and 0 <S + (t) <γ, for the some immediacy γ < ∞, the equation noted that a large γ would indicated greater current assets liquidity with compare to financial risk in derivative market. In a representative approach will indicate the value of financial derivative market setting where there is limited liquidity Assets, the selected portfolio related assets value should be consider in the following equation
dp (t) = ƛƿ (t) dt + σ1ƿ (t) dw1 (t) + σ2ƿ (t) dw2(t)
Where ƛ, σ1 and σ2 are progressive perpetual and dw1 (t) and dw2 (2) are the variables process to determine the market values in the derivative market. The research paper consider the market current value to be β , ƿ that the measured on the scale to spread to consider to determine the market price with help by the finance constant B > 0, in particular the research paper noted that which the study has chosen market EPS value more than the liquidity of the assets. The cost of a refinancing the portfolio is represented by the following equation.
β (t) b (t) + S (t) s (t) = -S +s (t) Bp (t)
Where
Β(t) = B + (t) – B- (t) and S (t) –s (-t)
According to above formula the research study has shown the value is incomplete financial derivative market depth, the research study have collected the information of the behaviour of investor perspective. The research paper suppose that disquiets to the price of the stock in a derivative market lacking depth is given incrementally from the selected companies share values with help of the following equation.
Or
Where D>0 According to above Equation the research paper describes that, the greater the asset liquidity. The study find that the overall stock price in derivative market process can be determine the as having two components to fine the specific risk of the portfolio: financial risk under the stock price in the present market value process under perfectly liquid risk management condition, which follows the classical Black Scholes model; and price perturbation component due to limited financial derivative market
S = Sliquidity +
Sperpetuation
Or
ds = dsliquidity + ds perpetuation
The research paper after analysis the above all component values of the selected portfolio the study will be consider the individual investor expectation of the returns. The research study has given the single asset model in a derivative market with financial risk is given as follows.
Ds (t) = µs (t) dt +σ2s (t) dw 2 (t) + σ3s (t) dw3 (t) + ds (t) ds (t)
Or
Ds (t)= [µ+ds (t)] s (t) dt + σ 2s (t) dw2 (t) + σ3s (t) dw3(t)
The research paper has Provides a correlation between the capital market value in derivative and financial risk management association. The different sizes of price perturbation due to the more financial risk impact on the EPS. The result in significant changes in the option values as well as trading strategies. The financial derivative market portfolio volatility, i.e. the change in wealth during a small time interval ds, the research study differentiate. The change of the market price will be determine the following equation.
Dw(t) = β (t) B (t) + rb (t) B (t) + S9t) s (t) + [µ + ds (t) }] S (t) dt + σ2s (t) S (t) dw2 (t) + σ3s (t) S (t) dw 3 (t)
From the above equation the first term and the third term of add up to S+ (t) Bp (t). After addition the values of the market stock price be determined the help of the below equation
dw(t) = β (T) b (T) + RB (T) B (t) + s (t) S (t) + {[ µ + ds (t)] s (t) dt + σ2s (t) dw 2 (t) + σ3s (t) s (t) dw3 (t)
The research paper has given finally liquidity assets its indicating positive relation between the derivative market value of the share and financial risk.
Multivariate Analysis to test the hypothesis is there is an effect of financial derivative on expected stock return in the stock market
In this research paper the study has employed the logistic regression to test the assumption that the decision to use the derivatives as financial risk management instruments is a function of the following factors - financial sickness of the company, size and costly external financing. The variables tested in our multivariate regression model are based on the factors presented in the financial derivative gap analysis as the key rationales for the corporate finance decision use of derivative instruments risk measurement. The association can be expressed in the form of a broad function as follows:
Financial Derivative adopted the = f (S, FC, CEF) (1)
Where:
1. Financial Derivative use is a binary variable
2. S is the symbolically indicated the size of company
3. FC is the likelihood of a firm's financial sickness as well as risk, and
4. CEF is the costly external financing.
Table-2 Multivariate logistic regression results (selected companies under listed of NSE)
|
-2 Log Likelihood |
39.253 |
|||||
|
Goodness-of-fit |
34.289 |
|||||
|
Cox and Snell – R^2 |
0.356 |
|||||
|
Nagelkerke – R^2 |
0.436 |
|||||
|
Hosmer and Lemeshow Goodness-of-fit test |
||||||
|
Goodness-of-fit test |
Chi-Square
5.239 |
df
12 |
Significance
0.5236 |
|||
|
Variable |
B |
S.E |
Wald |
df |
Sig. |
R |
|
CMI |
9.235 |
4.256 |
2.568 |
4 |
0.0568 |
0.5698 |
|
FINCOST |
2.259 |
1.568 |
0.986 |
4 |
0.0010 |
0.2359 |
|
SIZE |
2.356 |
1.578 |
0.9344 |
4 |
0.2451 |
0.4736 |
|
Constant |
-0.567 |
0.167 |
0.730 |
4 |
0.5890 |
0.8467 |
|
No outliers found. Number of cases included in the analysis: 37 Independent variables: CMI – Investment expenditures-to-assets ratio, Fin cost – Long-term debt-to-assets ratio, Size – Total sales revenues |
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Source: SPSS output, indicatesand p-values respectively, at lever of 5% significant