Study On The Determinants Of Financial Derivatives

Introduction

Our research article is “Determinants of Financial Derivatives�. Before moving towards the definition of main purpose and significance of our research article, we want to give a brief introduction of the core keywords of our research article which are “Financial Derivatives�.

1.1. Introduction

A derivative is a financial instrument (or more simply, an agreement between two people/two parties) that has a value determined by the future price of something else. Derivatives can be thought of as bets on the price of something. Suppose you bet with your friend on the price of a bushel of corn. If the price in one year is less than $3 your friend pays you $1. If the price is more than $3 you pay your friend $1. Thus, the underlying in the agreement is the price of corn and the value of the agreement to you depends on that underlying.[1]

So derivatives are the collective name used for a broad class of financial instruments that derive their value from other financial instruments (known as the underlying), events or conditions. Essentially, a derivative is a contract between two parties where the value of the contract is linked to the price of another financial instrument or by a specified event or condition.

Derivatives are usually broadly categorized by the:

Relationship between the underlying and the derivative (e.g. forward, option, swap)

Type of underlying (e.g. equity derivatives, foreign exchange derivatives, interest rate derivatives, commodity derivatives or credit derivatives)

Market in which they trade (e.g., exchange traded or over-the-counter)

Pay-off profile (Some derivatives have non-linear payoff diagrams due to embedded optionality)

Another arbitrary distinction is between:

Vanilla derivatives (simple and more common) and

Exotic derivatives (more complicated and specialized)

There is no definitive rule for distinguishing one from the other, so the distinction is mostly a matter of custom.

Derivatives are used by investors to

Provide leverage or gearing, such that a small movement in the underlying value can cause a large difference in the value of the derivative

Speculate and to make a profit if the value of the underlying asset moves the way they expect (e.g. moves in a given direction, stays in or out of a specified range, reaches a certain level)

Hedge or mitigate risk in the underlying, by entering into a derivative contract whose value moves in the opposite direction to their underlying position and cancels part or all of it out

Obtain exposure to underlying where it is not possible to trade in the underlying (e.g. weather derivatives)

Create optionability where the value of the derivative is linked to a specific condition or event (e.g. the underlying reaching a specific price level)

Uses

Hedging

Hedging is a technique that attempts to reduce risk. In this respect, derivatives can be considered a form of insurance.

Derivatives allow risk about the price of the underlying asset to be transferred from one party to another. For example, a wheat farmer and a miller could sign a futures contract to exchange a specified amount of cash for a specified amount of wheat in the future. Both parties have reduced a future risk: for the wheat farmer, the uncertainty of the price, and for the miller, the availability of wheat. However, there is still the risk that no wheat will be available because of events unspecified by the contract, like the weather, or that one party will renege on the contract. Although a third party, called a clearing house, insures a futures contract, not all derivatives are insured against counter-party risk.

From another perspective, the farmer and the miller both reduce a risk and acquire a risk when they sign the futures contract: The farmer reduces the risk that the price of wheat will fall below the price specified in the contract and acquires the risk that the price of wheat will rise above the price specified in the contract (thereby losing additional income that he could have earned). The miller, on the other hand, acquires the risk that the price of wheat will fall below the price specified in the contract (thereby paying more in the future than he otherwise would) and reduces the risk that the price of wheat will rise above the price specified in the contract. In this sense, one party is the insurer (risk taker) for one type of risk, and the counter-party is the insurer (risk taker) for another type of risk.

Hedging also occurs when an individual or institution buys an asset (like a commodity, a bond that has coupon payments, a stock that pays dividends, and so on) and sells it using a futures contract. The individual or institution has access to the asset for a specified amount of time, and then can sell it in the future at a specified price according to the futures contract. Of course, this allows the individual or institution the benefit of holding the asset while reducing the risk that the future selling price will deviate unexpectedly from the market's current assessment of the future value of the asset.

Derivatives traded at the Chicago Board of Trade.

Derivatives serve a legitimate business purpose. For example, a corporation borrows a large sum of money at a specific interest rate.[2] The rate of interest on the loan resets every six months. The corporation is concerned that the rate of interest may be much higher in six months. The corporation could buy a forward rate agreement (FRA). A forward rate agreement is a contract to pay a fixed rate of interest six months after purchases on a notional sum of money.[3] If the interest rate after six months is above the contract rate the seller pays the difference to the corporation, or FRA buyer. If the rate is lower the corporation would pay the difference to the seller. The purchase of the FRA would serve to reduce the uncertainty concerning the rate increase and stabilize earnings.

Speculation and arbitrage

Derivatives can be used to acquire risk, rather than to insure or hedge against risk. Thus, some individuals and institutions will enter into a derivative contract to speculate on the value of the underlying asset, betting that the party seeking insurance will be wrong about the future value of the underlying asset. Speculators will want to be able to buy an asset in the future at a low price according to a derivative contract when the future market price is high, or to sell an asset in the future at a high price according to a derivative contract when the future market price is low.

Individuals and institutions may also look for arbitrage opportunities, as when the current buying price of an asset falls below the price specified in a futures contract to sell the asset.

Speculative trading in derivatives gained a great deal of notoriety in 1995 when Nick Leeson, a trader at Barings Bank, made poor and unauthorized investments in futures contracts. Through a combination of poor judgment, lack of oversight by the bank's management and by regulators, and unfortunate events like the Kobe earthquake, Leeson incurred a $1.3 billion loss that bankrupted the centuries-old institution.

Types of derivatives

OTC and Exchange-traded

Broadly speaking there are two distinct groups of derivative contracts, which are distinguished by the way they are traded in the market:

Over-the-counter (OTC) derivatives are contracts that are traded (and privately negotiated) directly between two parties, without going through an exchange or other intermediary. Products such as swaps, forward rate agreements, and exotic options are almost always traded in this way. The OTC derivative market is the largest market for derivatives, and is largely unregulated with respect to disclosure of information between the parties, since the OTC market is made up of banks and other highly sophisticated parties, such as hedge funds. Reporting of OTC amounts are difficult because trades can occur in private, without activity being visible on any exchange. According to the Bank for International Settlements, the total outstanding notional amount is $684 trillion (as of June 2008).[5] Of this total notional amount, 67% are interest rate contracts, 8% are credit default swaps (CDS), 9% are foreign exchange contracts, 2% are commodity contracts, 1% are equity contracts, and 12% are other. Because OTC derivatives are not traded on an exchange, there is no central counter-party. Therefore, they are subject to counter-party risk, like an ordinary contract, since each counter-party relies on the other to perform.

Exchange-traded derivative contracts (ETD) are those derivatives instruments that are traded via specialized derivatives exchanges or other exchanges. A derivatives exchange is a market where individuals’ trade standardized contracts that have been defined by the exchange. A derivatives exchange acts as an intermediary to all related transactions, and takes Initial margin from both sides of the trade to act as a guarantee. The world's largest derivatives exchanges (by number of transactions) are the Korea Exchange (which lists KOSPI Index Futures & Options), Eurex (which lists a wide range of European products such as interest rate & index products), and CME Group (made up of the 2007 merger of the Chicago Mercantile Exchange and the Chicago Board of Trade and the 2008 acquisition of the New York Mercantile Exchange). According to BIS, the Scombined turnover in the world's derivatives exchanges totaled USD 344 trillion during Q4 2005. Some types of derivative instruments also may trade on traditional exchanges. For instance, hybrid instruments such as convertible bonds and/or convertible preferred may be listed on stock or bond exchanges. Also, warrants (or "rights") may be listed on equity exchanges. Performance Rights, Cash xPRTs and various other instruments that essentially consist of a complex set of options bundled into a simple package are routinely listed on equity exchanges. Like other derivatives, these publicly traded derivatives provide investors access to risk/reward and volatility characteristics that, while related to an underlying commodity, nonetheless are distinctive.

Common derivative contract types

There are three major classes of derivatives:

Futures/Forwards are contracts to buy or sell an asset on or before a future date at a price specified today? A futures contract differs from a forward contract in that the futures contract is a standardized contract written by a clearing house that operates an exchange where the contract can be bought and sold, while a forward contract is a non-standardized contract written by the parties themselves.

Options are contracts that give the owner the right, but not the obligation, to buy (in the case of a call option) or sell (in the case of a put option) an asset. The price at which the sale takes place is known as the strike price, and is specified at the time the parties enter into the option. The option contract also specifies a maturity date. In the case of a European option, the owner has the right to require the sale to take place on (but not before) the maturity date; in the case of an American option, the owner can require the sale to take place at any time up to the maturity date. If the owner of the contract exercises this right, the counter-party has the obligation to carry out the transaction.

Swaps are contracts to exchange cash (flows) on or before a specified future date based on the underlying value of currencies/exchange rates, bonds/interest rates, commodities, stocks or other assets.

More complex derivatives can be created by combining the elements of these basic types. For example, the holder of a swaption has the right, but not the obligation, to enter into a swap on or before a specified future date.

1.2. PROBLEM STATEMENT:

The problem statement on which we are doing research is as follows:

What are the Determinants that define the activities towards Financial Derivatives?

1.3. OBJECTIVE OF THE STUDY:

The main objective of our research is that which one of this independent variable like Risk, Yield Spread etc affects the financial derivatives the most or which one of the following indicates the most involvement in financial derivative.

1.4. Limitations:-

There are few limitations which are as under.

The data which we are considering is only from Islamabad stock exchange.

Out of numerous variables we have selected only four.

1.5. Plan:-

Rest of the thesis is organized as fallows. In chapter II we have produced a literature review. In chapter III Data is collected and statistical tools are applied. In chapter IV the results are interpreted. In chapter V conclusions and recommendations are given.

Chapter II

Literature Review

Credit derivatives and risk aversion in this article author discuss the valuation of credit derivatives in extreme regimes such as when the time-to-maturity is short, or when payoff is contingent upon a large number of defaults, as with senior trenches of collateralized debt obligations. In these cases, risk aversion may play an important role, especially when there is little liquidity, and utility-indifference valuation may apply. Specifically, we analyze how short-term yield spreads from default able bonds in a structural model may be raised due to investor risk aversion.

Using derivatives to manage risk this Refers to some well-publicized failures with derivatives, and seeks explanations for these problems; points to the role of the US treasury department as a profit centre, and presents a three-phase risk management framework for the successful use of derivatives risk identification/determination of the desired risk profile, implementation (to include factors such as the role of the board in the co-ordination of resources), evaluation/feedback. Shows how three celebrated cases of derivatives fiasco failed in respect of various aspects of this framework (these being Gibson Greetings, Procter & Gamble and Metallgesellschaft AG).

Petersen and Thiagarajan (2000) Estimates and compares the risk exposure of two firms operating in the gold mining industry. Suggests that the difference between the two firms lies in the risks that they choose to manage and the tools that they use. It presents an extensive analysis of the building blocks underlying the effects of risk management including operating cash flows, taxable income, investment opportunities and equity risk exposure. Shows how one uses adjustments to the quality of ore extracted as a partial hedge against gold price fluctuations, whilst the other uses derivatives to reduce the fluctuations in its revenues and therefore operating cash flows. Comments on the incentives for risk reduction and their effect on the management of gold price risk, noting that compensation strategies can lead to differing managerial objectives. Argues that the use of alternative forms of risk management is a conscious choice by firms and that the use of derivatives should be seen against the alternative tools available.

Alister and Mansfield (1980) states that Derivatives have been an expanding and controversial feature of the financial markets since the late 1980s. They are used by a wide range of manufacturers and investors to manage risk. This paper analyses the role and potential of financial derivatives investment property portfolio management. The limitations and problems of direct investment in commercial property are briefly discussed and the main principles and types of derivatives are analysed and explained. The potential of financial derivatives to mitigate many of the problems associated with direct property investment is examined.

The management of foreign currency risk: derivatives use and the natural hedge of geographic diversification Summer 1999 Notes the lack of evidence of large companies' use of foreign exchange derivatives (FXDs), related to the geographical diversification natural hedge, an alternative method of avoiding risk. Builds a model of company behavior, sampling 309 US companies by industry, including FXD, foreign sales, a sales-based Herfindahl index, and market value. Finds a significant and positive relationship between the use of FXDs and the level of foreign exchange exposure; and a negative relationship between geographic dispersion and FXD. Shows that there are economies of scale in FXD use, and that the findings are robust to industry membership and geographic diversification.

Emory presents evidence consistent with managers using derivatives and discretionary accruals as partial substitutes for smoothing earnings. Using 1994-1996 data for a sample of Fortune5 00 firms, I estimate a set of simultaneous equations that captures managers' incentives to maintain a desired level of earnings volatility through hedging and accrual management. These incentives include increasing managerial compensation and wealth, reducing corporate income taxes and debt financing costs, avoiding underinvestment and earnings surprises, and mitigating volatility caused by low diversification. After controlling for such incentives,

I find a significant negative association between derivatives' notional amounts and proxies for the magnitude of discretionary accruals.

Gay and Nam analyzed the underinvestment problem as a determinant of corporate hedging policy. We find evidence of a positive relation between a firm’s derivatives use and its growth opportunities, as proxied by several alternative measures. For firms with enhanced investment opportunities, derivatives use is greater when they also have relatively low cash stocks. Firms whose investment expenditures are positively correlated with internal cash flows tend to have smaller derivatives positions, which suggest potential natural hedges. Our findings support the argument that firms’ derivatives use may partly be driven by the need to avoid potential underinvestment problems.

Patil (2008) states that the Reserve Bank of India's Working Group on Rupee Derivatives has, interalia, recommended introduction of exchange traded derivatives to supplement OTC derivatives. But before we introduce exchange traded interest rates futures it is necessary to be fully aware of the ground realities. The basic issue is the healthy development of the market and abolition of the regulations that artificially protect the interests of a set of intermediaries whose role and functions have got significantly reduced with massive induction of IT applications into the capital and financial markets. Regulatory reforms should facilitate continuous reduction in transaction costs and up gradation of transactional efficiency across different segments of the market. A regulatory regime that ends up protecting the role of certain players merely because they played a useful role in the past in the development of some segments of the markets would be doing a disservice

Hentschel and Kothari makes Public discussion about corporate use of derivatives focuses on whether firms use derivatives to reduce or increase firm risk. In contrast, empirical academic studies of corporate derivatives use take it for granted that firms hedge with derivatives. Using data from financial statements of 425 large U.S. corporations, we investigate whether firms systematically reduce or increase their riskiness with derivatives. We find that many firms manage their exposures with large derivatives positions. Nonetheless, compared to firms that do not use financial derivatives, firms that use derivatives display few, if any, measurable differences in risk that are associated with the use of derivatives.

Brinson, Randolph Hood and Beebower (1986), states that in order to delineate investment responsibility and measure performance contribution, pension plan sponsors and investment managers need a clear and relevant method of attributing returns to those activities that compose the investment management process- investment policy, market timing and security selection. The authors provide a simple framework based on a passive, benchmark portfolio representing the plan's long-term asset classes, weighted by their long-term allocations. Returns on this "investment policy" portfolio are compared with the actual returns resulting from the combination of investment policy plus market timing (over or underweighting asset classes relative to the plan benchmark) and security selection (active selection within an asset class). Data from 91 large U.S. pension plans over the 1974-83 period indicate that investment policy dominates investment strategy (market timing and security selection), explaining on average 93.6 per cent of the variation in total plan return. The actual mean average total return on the portfolio over the period was 9.01 per cent, versus 10.11 per cent for the benchmark portfolio. Active management cost the average plan 1.10 per cent per year, although its effects on individual plans varied greatly, adding as much as 3.69 per cent per year. Although investment strategy can result in significant returns, these are dwarfed by the return contribution from investment policy-the selection of asset classes and their normal weights.

Markides (1995) concluded that there is increasing evidence (especially in the business press) that over the past decade, many U.S. corporations have 'restructured.' For example, Lewis (1990: 43) estimates that 'nearly half of large U.S. corporations have "restructured" in the 1980s.' Similarly, a special report on corporate restructuring published in the Wall Street Journal (1985: 1) found that out of the 850 of 'North America's largest corporations,' 398 (47%) of them restructured. A major problem with many of these studies on restructuring is that they do not define exactly what is meant by restructuring. Corporate actions such as share repurchasing, refocusing, alliances, consolidations and leveraged recapitalizations can all fall under the general term 'restructuring;' therefore, a researcher needs to look at these forms of restructuring separately if any generalizations are to be made. In this study, we focus on one specific type of restructuring, namely corporate refocusing. By this we mean the voluntary or involuntary reduction in the diversification of U.S. firms-usually, but not necessarily, achieved through major divestitures-what Bhagat, Shleifer, and Vishny (1990) call 'the return to corporate specialization.'

We focus on this type of restructuring because according to the existing evidence it is by far the most common and most beneficial form of restructuring undertaken by firms (e.g., Lewis, 1990; Wall Street Journal, 1985). According to existing evidence, a significant proportion of major diversified firms in the U.S. have reduced their diversification in the 1980s by refocusing on their core businesses (for statistical evidence, see Lichtenberg, 1990; Mark- ides, 1990; Porter, 1987; Williams, Paez and Sanders, 1988). For example, Markides (1993) reported that at least 20 percent and as many as 50 percent of the Fortune 500 firms refocused in the period 1981-87. He also found that refocusing is a 1980s phenomenon: using the Rumelt (1974) strategic categories of diversification, he reported that whereas only 1 percent of the Fortune 500 firms were refocusing in the 1960s, more than 20 percent were doing so in the 1980s. Other studies have shown that these refocusing firms are characterized by high diversification and poor profitability relative to their industry counter- parts, and that refocusing is associated ex-ante with improved stockmarket value (e.g., Comment and Jarrell, 1991; Markides, 1992a,b; Montgom- ery and Wilson, 1986). Yet, as Shleifer and Vishny (1991: 54) argue, there is very little ex- post evidence that refocusing is associated with profitability improvements.

Doukas and Lang In this study they present evidence that geographic diversification increases shareholder value and improves long-term performance when firms engage in core-related foreign direct (greenfield) investments. Non-core-related foreign investments are found to be associated with both short-term and long-term losses. Our results suggest that the synergy gains stemming from the internalization of markets are rooted in the core business of the firm. Geographic diversification outside the core business of the firm bears strongly against the prediction of the internalization hypothesis. The analysis also shows that, regardless of the industrial structure of the firm (that is, number of segments), foreign direct investments outside the core business of the firm are associated with a loss in shareholder value, whereas core-related (focused) foreign direct investments are found to be value increasing. Unrelated international diversification, however, is less harmful for diversified (multi- segment) than specialized (single-segment) firms. The larger gains to diversified firms suggest that operational and internal capital market efficiency gains are considerably greater in multi-segment than single-segment firms when both expand their core business overseas.

James and Finkelshtain (1965) said the effects of multivariate risk are examined in a model of portfolio choice. The conditions under which portfolio choices are separable from consumption decisions are derived. Unless the appropriate restrictions hold on investors' preferences or on the probability distribution of risks, the optimal portfolio is affected by other risks. This requires generalizing the usual measures of risk aversion. With one risky asset, matrix measures of risk aversion are used to generalize the results of Arrow (1965) and Pratt (1964) concerning the effects of risk aversion and wealth on the optimal portfolio. With two risky assets, the choices made by two investors coincide if and only if their generalized risk-aversion measures are identical. Ross's notion of stronger risk aversion is then used to characterize the effect of risk aversion on the level of investment in the riskier asset.

Browne (2000) tells us that Active portfolio management is concerned with objectives related to the out performance of the return of a target benchmark portfolio. In this paper, we consider a dynamic active portfolio management problem where the objective is related to the tradeoff between the achievement of performance goals and the risk of a shortfall. Specifically, we consider an objective that relates the probability of achieving a given performance objective to the time it takes to achieve the objective. This allows a new direct quantitative analysis of the risk/return tradeoff, with risk defined directly in terms of probability of shortfall relative to the bench- mark, and return defined in terms of the expected time to reach investment goals relative to the benchmark. The resulting optimal policy is a state-dependent policy that provides new insights. As a special case, our analysis includes the case where the investor wants to minimize the expected time until a given performance goal is reached subject to a constraint on the shortfall probability.

On the basis of this literature review we have developed the following Theoretical framework.

2.2. THEORATICAL FRAMEWORK:

The importance of:

Risk_

Response Index

Yield Spread_

Response Index

Liquidity_

Response Index

Geographical Diversification_

Response Index

Financial Derivatives

(Swap, Option, Future and Forward Contracts)

For

2.3 Hypothesis:

H0: µ < 3.5

H1: µ ≥ 3.5

If the mean respondent is 3.5 or above it means the factor is important because at the rating scale 1 is for strongly disagree and 5 is for strongly agree.

Chapter III

Data and Methodology

3.1. NATURE OF STUDY:

This study was descriptive in nature and will describe the Risk, Yield spread, Liquidity, Geographical diversification in the term of determinants of Financial Derivatives. The study setting for this study is non-contrived in nature i.e. it was conducted in the normal work place and routine working conditions.

3.2. PRIMARY DATA COLLECTION:

Data for this study was collected from the participants of the Islamabad Stock Exchange. These people were working or participating in the stock exchange where the people had knowledge about risk, yield spread, liquidity and geographical diversification. That is why; it was easier for us to conduct our research in Islamabad Stock Exchange to conclude our results that which one of the following factors like risk, yield spread, liquidity, and geographical diversification shows the maximum involvement in the determining of financial derivatives.

3.3. RESPONDENTS OF RESEARCH:

Data were collected from 100 participants. Participants were asked to fill the questionnaire which was helpful to lead us towards the result and conclusion of our research. All participants were asked to write down on the questionnaire their gender and age.

3.4. RESEARCH INSTRUMENT:

Questionnaire is an efficient data collection mechanism where we know exactly what is required and measures the variables of interest. Questionnaires were made with enough number of questions covering all the related areas. This helped us to conclude our result by measuring the affect of determinants on financial derivatives.

Questionnaires were personally handed over to the participants by us. All surveys were completed during working hours. Respondents were guaranteed that their data would remain confidential. Respondents were instructed to indicate their opinions about the questions to rate on a Likert Scale. This scale was designed to examine how strongly respondents agree or disagree with statements on a 5-points scale with the following anchors;

1

2

3

4

5

Strongly Disagree

Disagree

Neutral

Agree

Strongly Agree

3.5. DATA INTERPRETATION:

Statistical tools were used for the interpretation of data. These tools included t-test, correlation and descriptive statistics to find the involvement of independent variables in determining the financial derivatives. In other words, statistical tool of correlation were applied to interpret the relationship between the indexes of independent variables and t-test was used to determine the involvement of independent variable in determining the financial derivatives. The total data was divided into two halves:

Participants Below median age (39 and below)

Participants above median age (above 39)

We have applied sample mean test at µ=3.5.

Chapter IV

Findings

R1: Risky nature of instrument is not a matter of concern for me.

R2: Since high risk means high return therefore I will shift to the risky securities.

R3: Would you shift from one stock to another to reduce risk at the cost of return?

R4: It is feasible to add a percentage of low risk securities to a portfolio.

L1: Is a highly liquid security attractive to an investor

L2: The stocks in which you trade are relatively liquid which attracts you towards them.

L3: Liquidity reflects the performance of a firm therefore for diversification it is important

Y1: Yield spread helps the investor to determine which security would be the better investment.

Y2: Change in demand & supply of the securities effect the yield spread change therefore I shift towards low yield spread.

Y3: The market is forecasting a greater risk of default which implies a slowing economy (narrowing of spreads between bonds of different risk ratings)

G1: Geographical diversification increases the potential return on your investment / portfolio.

G2: Geographical diversification allows combining a diversification across domestic and foreign securities.

JUNIOR:

Risk:

 

R1

R2

R3

R4

T cal

-3.21

-0.77

-3.24

-2.12

T tab

2

2

2

2

Mean

2.96

3.38

3.1

3.2

Standard deviation

1.18

1.09

0.86

0.99

In case of R1, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of R2, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of R3, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of R4, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

Liquidity:

 

L1

L2

L3

T cal

1.94

-0.69

-0.28

T tab

2

2

2

Mean

3.76

3.42

3.46

Standard deviation

0.94

0.81

0.99

In case of L1, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of L2, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of L3, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

Yield spread:

 

Y1

Y2

Y3

T cal

0.13

-1.19

-2.60

T tab

2

2

2

Mean

3.52

3.32

3.14

Standard deviation

1.05

1.06

0.97

In case of Y1, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of Y2, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of Y3, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

Geographical Diversification:

 

G1

G2

T cal

0.32

-0.92

T tab

2

2

Mean

3.54

3.36

Standard deviation

0.89

0.92

In case of G1, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of G2, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

SENIOR:

Risk:

 

R1

R2

R3

R4

T cal

-3.44

-2.68

0

5.06

T tab

2

2

2

2

Mean

2.56

3.02

3.5

4.2

Standard deviation

1.51

1.25

1.02

0.97

In case of R1, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of R2, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of R3, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of R4, H0 is rejected it implies people consider this factor as important determinant of financial derivative.

Liquidity:

 

L1

L2

L3

T cal

3.95

3.59

1.78

T tab

2

2

2

Mean

4.08

3.98

3.74

Standard deviation

1.03

0.94

0.94

In case of L1, H0 is rejected it implies people consider this factor as important determinant of financial derivative.

In case of L2, H0 is rejected it implies people consider this factor as important determinant of financial derivative.

In case of L3, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

Yield spread:

 

Y1

Y2

Y3

T cal

3.94

-3.16

-0.92

T tab

2

2

2

Mean

3.86

3.1

3.34

Standard deviation

0.64

0.89

1.22

In case of Y1, H0 is rejected it implies people consider this factor as important determinant of financial derivative.

In case of Y2, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of Y3, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

Geographical Diversification:

 

G1

G2

T cal

1.75

5.56

T tab

2

2

Mean

3.72

4.02

Standard deviation

0.88

0.65

In case of G1, H0 is accepted it implies people do not consider this factor as important determinant of financial derivative.

In case of G2, H0 is rejected it implies people consider this factor as important determinant of financial derivative.

Junior:

Correlations

R_Index

L_Index

Y_Index

G_Index

R_Index

Pearson Correlation

1

.310*

.002

.163

Sig. (2-tailed)

.029

.991

.257

N

50

50

50

50

L_Index

Pearson Correlation

.310*

1

.366**

.326*

Sig. (2-tailed)

.029

.009

.021

N

50

50

50

50

Y_Index

Pearson Correlation

.002

.366**

1

.616**

Sig. (2-tailed)

.991

.009

.000

N

50

50

50

50

G_Index

Pearson Correlation

.163

.326*

.616**

1

Sig. (2-tailed)

.257

.021

.000

N

50

50

50

50

*. Correlation is significant at the 0.05 level (2-tailed).

In this table above:

Association between R_Index and L_Index is 31% which shows a medium relationship.

Association between R_Index and Y_Index is 2% which shoes a weak relationship.

Association between R_Index and G_Index is 16% which shows a weak relationship

Association between L_Index and Y_Index is 36% which shows a medium relationship.

Association between L_Index and G_ndex is 32% which shows a medium relationship.

Association between Y_Index and G_Index is 61% which shows relatively significant relationship.

Senior:

Correlations

R_Index

L_Index

Y_Index

G_Index

R_Index

Pearson Correlation

1

.605**

.240

.423**

Sig. (2-tailed)

.000

.093

.002

N

50

50

50

50

L_Index

Pearson Correlation

.605**

1

.219

.689**

Sig. (2-tailed)

.000

.126

.000

N

50

50

50

50

Y_Index

Pearson Correlation

.240

.219

1

.068

Sig. (2-tailed)

.093

.126

.640

N

50

50

50

50

G_Index

Pearson Correlation

.423**

.689**

.068

1

Sig. (2-tailed)

.002

.000

.640

N

50

50

50

50

*. Correlation is significant at the 0.05 level (2-tailed).

In this table above:

Association between R_Index and L_Index is 60% which shows a medium relationship.

Association between R_Index and Y_Index is 24% which shows weak relationship.

Association between R_Index and G_Index is 42% which shows a medium relationship.

Association between L_Index and Y_Index is 21% which shows weak relationship.

Association between L_Index and G_ndex is 68% which shows relatively significant relationship.

Association between Y_Index and G_Index is 6% which shows relatively significant relationship.

Descriptive Statistics: (junior)

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

R_Index

50

2

4

3.16

.584

L_Index

50

2

5

3.55

.689

Y_Index

50

1

5

3.33

.812

G_Index

50

1

5

3.45

.835

Valid N (listwise)

50

Descriptive Statistics: (Senior)

Descriptive Statistics

N

Minimum

Maximum

Mean

Std. Deviation

R_Index

50

2

5

3.57

.530

L_Index

50

2

5

3.93

.765

Y_Index

50

2

5

3.43

.664

G_Index

50

2

5

3.87

.596

Valid N (listwise)

50

Chapter V

Conclusion and Recommendations:

Conclusion:

This research was mainly conducted to assess the indication of the involvement of Risk, Yield Spread, Liquidity and Geographical Diversification on Financial Derivatives. The influence of these four independent variables was examined. Data was collected by questionnaires which were given or distributed in the Islamabad Stock Exchange participants. We have used the sample mean test (t-test) to find the major influence of these four Risk, Yield Spread, Liquidity and Geographical Diversification on Financial Derivatives.

From this study we can conclude that in case of juniors none of these four factors affects majorly in the determination of financial derivatives. While in the case of seniors not fully but partially all factors are important in the determination of financial derivatives. That means the senior investors just look the factors in determining or doing diversification. In Pakistani market these factors play some role because here the market is manipulated my big investors, the market rates or index is influenced by the speculations in the market.

So by this we concluded that the seniors do consider these factors the reason for diversification in Pakistani Market. It might be due to their age they are frightened of loss.

This means that we should improve our trade relations with our neighboring countries or countries located geographically near to us.

Thus, to make our research more purposeful, we have made some recommendations which are as follows.

Recommendations:

Awareness should be increased amongst the investors regarding the risk factor of each stock.

A standard should be developed to identify the risk factor attached with every stock and this information should be made public.

Investors should be educated about the calculations of yield spread of every stock.

A standard should be developed to identify the liquidity factor attached with every stock and this information should be made public.

Investors should be educated about how to decrease risk factor by using various diversification techniques.

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