Identification of Optimal Hedging Strategy

8/7/2019 Identification of Optimal Hedging Strategy

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MP BIRLA INSTITUTE OF MANAGEMENT 2

DECLARATION

I hereby declare that the research work embodied in the dissertation

entitled Identification Of Optimal Hedging Strategy has been

carried out by me under the guidance and supervision of Dr. N S

Malavalli Principal, M.P.Birla Institute Of Management Bangalore

I also declare that the dissertation has not been submitted to any

University/Institution for the award of any Degree/Diploma.

Place: Bangalore Rejani M Raju

( 03XQCM6082 )


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HEDGING STRATEGIES


AABBSSTTRRAACCTT

Among all the innovations that have flooded the international financial markets,

financial derivatives occupy the driver's seat. Derivatives are financial instruments

whose values depend on the values of underlying assets.

Stock Index Futures have been one of the success stories of the financial derivative

markets .Investors use stock index futures for several distinct investment strategies.

This research focuses on one of the uses of stock index futures viz; hedging against

adverse stock price movements. There are different strategies which are used for

hedging namely, Classic One to One Hedge strategy, Beta Hedge Strategy, Minimum

Variance Hedge Strategy. A Quantitative research is done on 20 socks selected from

National Stock Exchange .The Investigation reveals that Classic One to One Hedge

Strategy reduces the loss more compared to the other tow strategies ,however the %

reduction in loss varies from stock to stock . It is also found that for a stock having

betas less than 1 Classic One to One Hedge Strategy is comparitatively the best

strategy and for stock having beta more than 1 Beta Hedge Strategy is comparitatively

the best.


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CHAPTER - 01

IINNTTRROODDUUCCTTIIOONN


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IINNTTRROODDUUCCTTIIOONN

Among all the innovations that have flooded the international financial markets,

financial derivatives occupy the driver's seat. These specialized instruments facilitate

the shuffling and redistribution of the innumerable risks that an investor face and, thus

aids in the process of diversifying ones portfolio. The volatility in the equity markets

over the past years has resulted in greater use of equity derivatives. The volume of the

exchange traded equity futures and options in most of the mature markets have seen a

significant growth. It goes beyond doubt that the local derivative markets in the

emerging markets have witnessed widespread use of the derivative instrument for a

variety of reasons. This continuous growth and development by the emerging market

participants has resulted in capital inflows as well as helped the investors in risk

protection through hedging.

Derivatives trading commenced in India in June 2000 after SEBI granted the approval

to this effect in May 2000. SEBI permitted the derivative trading on two stock

exchanges, i.e. and BSE, and their clearing house/corporation to commence trading and

settlement in approved derivative contracts. To begin with, SEBI approved trading inindex futures contracts based on S&P CNX Nifty Index and BSE-30 (Sensex) Index.

This was followed by approval for trading in options based on these two indices and

options on individual securities. The trading in index options commenced in June 2001

and trading in options on individual securities would commence in July 2001 while

trading in futures of individual stocks started from November 2001. In June 2003,

SEBI/RBI approved the trading on interest rate derivative instruments and only NSE

introduced trading in interest rate futures contracts on June 24, 2003 on 91-day Notional

T-Bills and 10-year Notional 6% coupon bearing as well as zero coupon Bonds. Futures

and Options were also introduced on CNX IT Index in August 2003. The total exchange

traded derivatives witnessed a value of Rs.4,423,333 million during 2002-03 as against

Rs. 1,038,480 million during the preceding year. While NSE accounted for about 99.5%


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of total turnover, BSE accounted for less than 1% in2002-03. The market witnessed

higher trading levels from June 2001 with introduction of index options, and still higher

volumes with the introduction of stock options in July 2001. There was a spurt in

volumes in November 2001 when stock futures were introduced. The calendar year

2002 has been a remarkable year for the global derivatives market. This year witnessed

NSE making huge strides and also moved upward in the global ranking. According to

the Futures Industry Associations in the year 2002, NSE ranked 30 in the global futures

and options volume, whereas it ranks second in the world in terms of stock futures only.


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PPRROOBBLLEEMM SSTTAATTEEMMEENNTT::

If the portfolio manager thinks that a bear market is imminent and the stock price will

fall in future, and wants to reduce their exposure in stock. One way of reducing the risk

exposure is selling the stock and repurchasing it later. But this is relatively expensive

and also there is poor realization of price. Another way for the portfolio manager is to

short stock index future contracts to reduce the market risk. The basic idea behind using

the stock index futures to hedge is that any losses arising due to movements in stock

prices will be offset by gains from opposite movements in future and all this without

any alteration in original portfolio.

Therefore, this research aims to identifying the Optimal Hedging Strategy

RREESSEEAARRCCHH OOBBJJEECCTTIIVVEE::

1) To identify the optimal hedging Strategy

2) To examine whether there is a link between beta of the stock and hedging strategies.

HHYYPPOOTTHHEESSIISS::

H0 = Classic one to one hedge strategy is not the best hedging strategy

H1 = Classic one to one hedge strategy is the best hedging strategy


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DDEERRIIVVAATTIIVVEESS

Derivatives are financial instruments whose values depend on the values of other, more

basic underlying assets. Exchange traded financial derivatives were introduced in India

in June 2000 at the two major stock exchanges, NSE and BSE. Derivatives are used by :

1.Hedgers :For protecting against adverse movement. Hedging is a mechanism to

reduce price risk inherent in open positions. Derivatives are widely used for hedging. A

Hedge can help lock in existing profits. Its purpose is to reduce the volatility of a

portfolio, by reducing the risk.

2.Speculators: To make quick fortune by anticipating/forecasting future market

movements. Hedgers wish to eliminate or reduce the price risk to which they are

already exposed. Speculators, on the other hand are those classes of investors who

willingly take price risks to profit from price changes in the underlying. While the need

to provide hedging avenues by means of derivative instruments is laudable, it calls for

the existence of speculative traders to play the role of counter-party to the hedgers. It is

for this reason that the role of speculators gains prominence in a derivatives market.

3.Arbitrageurs: To earn risk-free profits by exploiting market imperfections.

Arbitrageurs profit from price differential existing in two markets by simultaneously

operating in the two different markets.


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TTYYPPEESS OOFF DDEERRIIVVAATTIIVVEESS

Derivatives are basically classified into two based upon the mechanism that is used to

trade on them.

Over the Counter derivatives

Exchange traded derivatives

The OTC derivatives are between two private parties and are designed to suit the

requirements of the parties concerned.

The Exchange traded ones are standardized ones where the exchange sets the standards

for trading by providing the contract specifications and the clearing corporation

provides the trade guarantee and the settlement activities

CCLLAASSSSIIFFIICCAATTIIOONN OOFF DDEERRIIVVAATTIIVVEESS

The derivatives can be classified as:

Forward

Future

Option

Swaps


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gold/ oil etc. or financial instruments like equity stocks/ stock index/ bonds etc. There

are two types of Options

1)Call Option: A call option gives the holder (buyer/ one who is long call), the right to

buy specified quantity of the underlying asset at a specified price on or before a

specified time. The seller (one who is short call ) however, has the obligation to sell the

underlying asset if the buyer of the call option decides to exercise his option to buy.

2)Put Option: A Put option gives the holder (buyer/ one who is long Put), the right to

sell specified quantity of the underlying asset at a specified price on or before a

specified time. The seller (one who is short put) however, has the obligation to buy the

underlying asset if the buyer of the put option decides to exercise his option to sell.

4) Swaps:

Swap can be defined as "A financial transaction in which two counterparties agree to

exchange streams of payments, or cash flows, over time". Generally, two types of swaps

are generally seen i.e. interest rate swaps and currency swaps. A swap results in

reducing the borrowing cost of both parties. The two major types of swaps are as

follows-

Interest Rate Swap: A deal between banks or companies where borrowers switch

floating-rate loans for fixed rate loans in another country. These can be either the same

or different currencies. The advantage to this is that one company may have access to

lower fixed rates and another company may have access to lower floating rates so they

trade

Currency swap: A swap that involves the exchange of principal and interest in onecurrency for the same in another currency


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SSTTOOCCKK IINNDDEEXX FFUUTTUURREE

Trading in stock index futures contracts was introduced by the Kansas City Board of

Trade on February 24, 1982.

In April 1982, the Chicago Mercantile Exchange (CME) began trading in futures

contract based on the Standard and Poor' s Index of 500 common stocks. Like most other

financial instruments, futures contracts are traded on recognized exchanges. In India,

both the NSE and the BSE have introduced index futures in the S&P CNX Nifty and the

BSE Sensex. The NSE commenced trading in index futures on June 12, 2000.These

contracts are based on the S&P CNX NIFTY INDEX

Stock index futures: are types of future contracts traded in terms of number of

contracts. Each contract is to buy or sell a fixed value of the index. The value of the

index is defined as the value of the index multiplied by the specified monetary amount.

One of the most important use of stock index futures is for hedging. Mutual funds and

other institutional investors are the main beneficiaries.

Hedging: is a technique by which such institutions can protect their portfolios from

market risks. Index futures provide investors an efficient and cost-effective means ofhedging

The main purposes of hedging are:

* Risk minimization.

* Profit maximization.

* Reaching a satisfactory risk-return trade-off using a portfolio.

Hedge ratio: It is the number of future contracts used to hedge a particular exposure in

the spot market. The hedge ratio should be the one in which the futures profit or loss

matches the spot profit or loss. There is no exact method to determine the hedge ratio.


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There are, however, several strategies which are adopted to estimate the hedge ratio.

The following are three strategies to address the estimation problem.

a) The classic one to one hedge strategy.

b) The beta hedge strategy.c) The minimum variance hedge strategy.

a)THE CLASSIC ONE TO ONE HEDGE STRATEGY:

This is the most elementary method in which the hedgers takes up a future position

which is equivalent in size but opposite in sign to the spot market, so the hedge ratio

becomes -1. If changes in the future market exactly match the changes in the spot

market, the price risk is eliminated and it is a perfect hedge.

But this proposal is relatively nave in practice, futures and spot prices may not change

in the same proportion because of basis risk, and also because portfolio may not exactly

mirror the Index composition.

Since it is not possible to have perfect correlation between spot and future prices and

returns, the hedger ratio which minimizes the variance of returns will be different from

-1.

Hedge Ratio = (Exposure in market /Value of futures contract)

The concept can be understood in detail by considering the following example:

BBEERRGGEERR PPAAIINNTT

No: of shares of the stock is 100000

Beta of the stock is 0.80

Price of the stock on February 28, 2005 is Rs 41.45

Price of the stock on March 24 ,2005 is Rs 39.95

Exposure in the spot market = 100000*41.45 = Rs 4145000

Value of 1 contract of stock index = 200 *2111.65 = Rs 422330No : of contract to be sold to hedge exposure = 4145000/422330 = 10

Loss due to fall in stock price = (41.45-39.95) *100000 = Rs 150000


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Profit due to fall in index = 200*10*95.6 =Rs 187655

Net loss/profit =187655 -150000 = Rs 37655

b)THE BETA HEDGE STRATEGY:Another strategy which is used for hedging is the Beta Hedge Strategy.

With this strategy we take into account the fact that the portfolio to be hedged may be

different than the index. Although this strategy is also based on the same objective as

the classic hedge strategy of equal size and opposite sign

Concept, it says that the number of future contracts for full hedge needs to take into

account the stocks beta.

With the Beta hedge it is recognized that the stock portfolio to be hedged may differ

from the underlying the futures contract to be used to hedge. But if the cash portfolio is

the same with underlying the futures position, the strategy will give the same value for

the hedge ratio as the classic hedge strategy. According to this strategy, while

calculating the Number of futures contract by dividing the futures position by spot

position, we also multiply by beta of the portfolio.

Hedge Ratio = (Exposure in market /Value of futures contract)* Beta

The concept can be understood in detail by considering the following example


No : of shares of the stock is 100000

Beta of the stock is 0.80

Exposure in the spot market Price of the stock on March 24, 2005 is Rs 39.95

Exposure in the spot market = 100000*41.45 = Rs 4145000

Value of 1 contract of stock index = 200 *2111.65 = Rs 422330

No: of contract to be sold to hedge exposure = Bet a*(4145000/422330) = 8Loss due to fall in stock price = (41.45-39.95) *100000 = Rs 150000


Net loss/profit =187655 -150000 = Rs 424


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c)THE MINIMUM VARIANCE HEDGE STRATEGY :

The last strategy which is used for hedging is the Minimum Variance Hedge strategy

The prices on the spot and futures market do not move together and hence a hedge ratio

derived from the traditional classic hedge strategy or the beta hedge strategy would notminimize the risk.

Here we use the model from the work of Johnson (1960) and Stein (1961) THE

MINIMUM VARIANCE HEDGE RATIO (MVHR) as an alternative to the classic

hedge. This strategy follows the traditional approach as it emphasizes the risk reduction

properties of future contracts.

So the MVHR,h*. as defined by Johnson is

h* = -cov(Rs Rf )/Var (Rf)

Rs = Return on the spot position.

Rf = Return on the future position.

The negative sign indicates the futures should have an opposite position to the spot

position. Minimum variance hedge ratio is a method to find out a hedge ratio (h*) which

leads to minimum variation in the return after the hedging is done.

Generally, h* is calculated by regressing the return on spot position against returns on

future on future contract, using past data.

Variance of the position is:

9 121/K

21) -1/6/)

Setting equation (1) to zero, the value of h which minimizes variance is

K 1/6/) (Model from the work of Johnson (1960) and Stein (1961)

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The concept can be understood in detail by considering the following example


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No : of shares of the stock is 100000

h * = 0.74

Exposure in the spot market = 100000*41.45 = Rs 4145000Value of 1 contract of stock index = 200 *2111.65 = Rs 422330

No: of contract to be sold to hedge exposure = 0.74*(4145000/422330) = 7

Loss due to fall in stock price = (41.45-39.95) *100000 = Rs 150000


Net loss/profit =138471-150000 = - Rs 11529


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CCHHAAPPTTEERR --00 22

RREEVVIIEEWW OOFF LLIITTEERRAATTUURREE


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RREEVVIIEEWW OOFF LLIITTEERRAATTUURREE

The determination of the appropriate statistical technique for estimating the hedge

ratio which minimizes the variance of returns has been a matter of research .Although

the simple method of ordinary Least Square regression in which the coefficient

estimate for the future prices give the hedge ratio by regressing spot on future price,

has been used by many studies, this method has suffered much criticism. It has been

shown stocks return usually show time varying conditional heteroscedasticity and so

data does support the assumption of the variance covariance matrix of return being

constant over time .In order to improve the estimation of the hedge ratio it is

necessary to consider the possible time varying nature of the second movements. In

recent literature researchers have also used the hedging strategies based on GARCH

(Generalized Autoregressive Conditional Heteroscedasticity ) models which uses the

conditional variances and co-variances as input to the hedge ratio to be time varying

.But again the high transaction cost and complexity associated with the GARCH

strategy does not appear to be warranted , Mayers(1991).

Various researchers have proposed more complex techniques. But whether a

distinctive superior hedge ratio estimation methodology exists is a question that still

needs an answer. So despite the fact that there exist large amount of literature, there is

no consequences about the technique that could systematically provide a better

estimation of optimal hedge ratio. In this scenario, if the Ordinary least Square model

shows various inadequacies from the statistical point of view, more complex models

have offered conflicting results from the empirical point of view.

Holmes study in (1995) investigated hedging effectiveness for the UK in relation to

FSTE-100 contract. For the period 1984-1992 , he showed the possibility to achieve a

risk reduction of more than 80% in comparison with the unhedged portfolio. He

shows that in terms of risk reduction a hedge strategy based on minimum variance

hedge ratio estimated through the Ordinary Least Square model slightly outperforms

the strategy based on more advanced techniques such as GARCH approach but also


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by simpler techniques like the beta hedge and the unhedged portfolio .Moosa (2003)

questioned the theory that the choice of the model used to estimate the hedge ratio can

really affect the effectiveness of hedging .His results showed that the model

specification does nor make any significant difference for the hedge effectiveness .He

concludes that although the theoretical arguments for why model specification does

matter as elegant . What really matters for the success or failure of a hedge is the

correlation between the prices of the unhedged position and the hedging instruments.

In fact, each method has some advantage s and disadvantages that the investors should

consider. Most often model like the Ordinary Least Square could give reliable results

with less complexity and cost .But the implication of the misspecification problems

should be carefully considered. There are other areas where research may be

undertaken like the developments of new measures of hedging effectiveness that take

into account the transaction cost and taxes, the ability of the GARCH models to

capture irregular market fluctuation and other phenomenon to understand the

implications for the hedge ratio estimation.


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CCHHAAPPTTEERR --0033

MMEETTHHOODDOOLLOOGGYY


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MMEETTHHOODDOOLLOOGGYY

Stock Index Futures have been one of the a success stories of the financial derivative

markets .These cash settled contracts derive their value from an underlying stock index.Investors use stock index futures for several distinct investment strategies. This

research focuses on one of the uses of stock index futures viz; hedging against adverse

stock price movements.

This is primarily a quantitative research. For the analysis 20 stocks has been selected

randomly from a sample population of 719 stocks listed in the National stock Exchange,

on which individual stock future contract are not available. The data used consist of the

closing price on the last day of every month for the 20 stocks selected from the National

Stock exchange for the period of 3 years starting from March 2002 to February 2005.

The S&P CNX NIFTY INDEX price is also taken as the closing price on the last day of

every month for 3 year period starting from March 2002 to February 2005. For the

purpose of Index futures ,contracts are available for one ,two and three months .But for

calculating the standard deviation of index futures contract the data for period of 3

years starting from March 2002 to February 2005 is used . The methods of roll over is

used since the near month future contracts are usually the most actively traded, the data

for the near month contract is used and then rolled over to the next month .To avoid the

expiration effect, the roll over was done on the last trading day of the third week of the

month (ie; Friday) to the next month The life of the hedge is considered to be from

February 28, 2005 to March 24, 2005. The method of stratified Random Sampling was

employed to select the 20 stocks used for the analysis .Data gathering was done with the

help of websites and through journals and books. The data used are mostly secondary

data collected from the website of National Stock Exchange .The table below gives the

list of stock used for the analysis.


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For the research purposed I have assumed the number of shares I hold of each company

is equal to 100000

The return for each month was calculated using the following equation ,

R t = Pt /Pt-1

Pt is the value of the security on month t and Pt-1 is the value of the security on month

t-1

Standard Deviation of the return is calculated using the following equation,

SSTTOOCCKK

BERGER PAINT

APPOLO

BAJAJ

BRITANIA

TVS

MARICO

MASTEK

RAYMOND

THOMASCOOK

ZEETELE

AARTI INDUSTRIES LTD

BAYER ABS LIMITED

AHMEDNAGAR FORGINGS LTD

ALEMBIC LIMITED

ALFA LAVAL INDIA LTD

ALPS INDUSTRIES LTD

THE ANDHRA SUGAR LTD

TATA COFFEE

DHAMPURSUG

EICHERMOT


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HEDGING STRATEGIES


where Rt is the average return over the period.

Beta of the stock is calculated using the following equation,

Beta = Cov (Stock, Index) / Var (Stock)

HEDGE RATIO:

Hedge ratiofor the 3 strategies is calculated using the following equation,

THE CLASSIC ONE TO ONE HEDGE STRATEGY:

Hedge Ratio = (Exposure in market /Value of futures contract)

THE BETA HEDGE STRATEGY:

Hedge Ratio = (Exposure in market /Value of futures contract)* Beta

THE MINIMUM VARIANCE HEDGE RATIO

K 1/6/)

Hedge Ratio = (Exposure in market /Value of futures contract)* (h*)


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CCHHAAPPTTEERR --0044

AANNAALLYYSSIISS AANNDD DDIISSCCUUSSSSIIOONN


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ANALYSIS

To arrive at the results the analysis is carried out on 20 stocks selected from the

National Stock Exchange. As mentioned in the methodology the standard deviation,beta and h * of the stocks in found out using the last trading day prices of the stock for

the period March 2002 to February 2005 .These datas appropriately for the different

strategies to find out the Optimal Strategy which reduces the loss more .

PRICES OF THE STOCKS FEBRUARY 28,2005 & MARCH 24, 2005

STOCK P1 P2

BERGER PAINT 41.45 39.95

APPOLO 298.15 285.35

BAJAJ 171.75 146.65

BRITANIA 930.05 860.55

TVS 72.55 69.7

MARICO 249.35 231.28

MASTEK 385.35 338.05

RAYMOND 327.15 309.15

THOMASCOOK 495.05 425.05

ZEETELE 142.30 130.30

HCL 844.75 830.25

AARTI INDUSTRIES LTD 108.65 89.30

BAYER ABS LIMITED 133.80 112.35

AHMEDNAGAR FORGINGS LTD 203.40 173.70

ALEMBIC LIMITED 304.55 271.70

ALFA LAVAL INDIA LTD 720.90 700.10

ALPS INDUSTRIES LTD 100.50 86.20

THE ANDHRA SUGAR LTD 139.45 110.25

TATA COFFEE 313.85 294.80

DHAMPURSUG 159.20 131.15

EICHERMOT 334.55 297.90


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HEDGING STRATEGIES


CCAALLCCUULLAATTEEDD SSTTAANNDDAARRDD DDEEVVIIAATTIIOONN ,,BBEETTAA && HH** OOFF SSTTOOCCKK

STOCK SD OF STOCK BETA H*

BERGER PAINT 0.17 0.80 0.74

APPOLO 0.16 1.82 0.60

BAJAJ 0.27 1.81 1.75

BRITANIA 0.07 0.47 0.44

TVS 0.20 0.34 0.28

MARICO 0.17 0.96 1.00

MASTEK 0.17 0.99 1.00

RAYMOND 0.10 0.77 0.70

THOMASCOOK 0.10 0.78 0.70

ZEETELE 0.14 0.80 0.70

HCL 0.20 1.05 1.10

AARTI INDUSTRIES LTD 0.22 0.83 0.80

BAYER ABS LIMITED 0.15 0.81 0.80

AHMEDNAGAR FORGINGS LTD 0.43 0.74 0.60

ALEMBIC LIMITED 0.21 1.12 1.10

ALFA LAVAL INDIA LTD 0.11 0.60 0.50

ALPS INDUSTRIES LTD 0.20 1.11 1.10

THE ANDHRA SUGAR LTD 0.18 1.06 1.00

TATA COFFEE 0.11 0.83 0.78

DHAMPURSUG 0.32 2.12 1.93

EICHERMOT 0.17 0.67 0.61


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HEDGING STRATEGIES



THE CLASSIC ONE TO ONE HEDGE STRATEGY

EXPOSURE IN SPOT MARKET 4145000

VALUE OF ONE CONTRACT OF STOCK INDEX 422330

NO: OF CONTRACT TO BE SOLD TO HEDGE EXPOSURE 10

STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 41.45 2111.65

MARCH 24 2005 39.95 2016.05

CHANGE IN VALUE FROM FEB 28 TO MARCH 24 2005 1.5 95.6

STOCK PRICE FALLEN ,SO LOSS 150000

INDEX VALUE FALLEN ,SO PROFIT 187655

NET LOSS/PROFIT 37655

BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 41.45 2111.65

MARCH 24 2005 39.95 2016.05




NET LOSS/PROFIT 424

MINIMUM VARIANCE HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 41.45 2111.65

MARCH 24 2005 39.95 2016.05




NET LOSS/PROFIT -11529


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HEDGING STRATEGIES


AAPPPPOOLLOO TTYYRREESS





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 298.15 2111.65

MARCH 24 2005 285.35 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 298.15 2111.65

MARCH 24 2005 285.35 2016.05



INDEX VALUE FALLEN ,SO PROFIT 2460878NET LOSS/PROFIT 1180878





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 298.15 2111.65

MARCH 24 2005 285.35 2016.05CHANGE IN VALUE FROM FEB 28 TO MARCH 24 2005 12.8 95.6





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HEDGING STRATEGIES


BBAAJJAAJJ HHIINNDDUUSSTTHHAANN LLTTDD

THE CLASSIC ONE TO ONE HEDGE RATIO




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 171.75 2111.65

MARCH 24 2005 146.65 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 171.75 2111.65

MARCH 24 2005 146.65 2016.05









STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 171.75

MARCH 24 2005 146.65

CHANGE IN VALUE FROM FEB 28 TO MARCH 24 2005 25.1





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HEDGING STRATEGIES


BBRRIITTAANNIIAA





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 930.05 2111.65

MARCH 24 2005 860.55 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 930.05 2111.65

MARCH 24 2005 86055 2016.05









STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 930.05 2111.65

MARCH 24 2005 860.55 2016.05






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HEDGING STRATEGIES


TTVVSS





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 72.55 2111.65

MARCH 24 2005 69.70 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 72.55 2111.65

MARCH 24 2005 69.70 2016.05



INDEX VALUE FALLEN ,SO PROFIT 111181NET LOSS/PROFIT -173819





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 72.55 2111.65

MARCH 24 2005 69.70 2016.05CHANGE IN VALUE FROM FEB 28 TO MARCH 24 2005 2.85 95.60



INDEX VALUE FALLEN ,SO PROFIT -194216


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HEDGING STRATEGIES


MMAARRIICCOO IINNDDUUSSTTRRIIEESS LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 249.35 2111.65

MARCH 24 2005 231.28 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 249.35 2111.65

MARCH 24 2005 231.28 2016.05





MINIMUM VARIANCE HEGDE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 249.35 2111.65

MARCH 24 2005 231.28 2016.05






33/52

HEDGING STRATEGIES


MMAASSTTEEKK LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 385.35 2111.65

MARCH 24 2005 338.05 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 385.35 2111.65

MARCH 24 2005 338.05 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 385.35 2111.65

MARCH 24 2005 338.05 2016.05






34/52

HEDGING STRATEGIES


RRAAYYMMOONNDD LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 327.15 2111.65

MARCH 24 2005 309.15 2016.05

CHANGE IN VALUE FROM FEB 28 TO MARCH 24 2005 18 95.60




BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 327.15 2111.65

MARCH 24 2005 309.15 2016.05




MINIMUM VARIANCE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 327.15 2111.65

MARCH 24 2005 309.15 2016.05






35/52

HEDGING STRATEGIES


TTHHOOMMAASS CCOOOOKK ((IINNDDIIAA)) LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 495.05 2111.65

MARCH 24 2005 425..05 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 495.05 2111.65

MARCH 24 2005 425.05 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 495.05 2111.65

MARCH 24 2005 425.05 2016.05






36/52

HEDGING STRATEGIES


ZZEEEE TTEELLEEFFIILLMMSS LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 142.30 2111.65

MARCH 24 2005 130.30 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 142.30 2111.65

MARCH 24 2005 130.30 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 142.30 2111.65

MARCH 24 2005 130.30 2016.05






37/52

HEDGING STRATEGIES


AAAARRTTII IINNDDUUSSTTRRIIEESS LLTTDD.





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 108.65 2111.65

MARCH 24 2005 89.60 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 108.65 2111.65

MARCH 24 2005 89.60 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 108.65 2111.65

MARCH 24 2005 89.60 2016.05






38/52

HEDGING STRATEGIES


BBAAYYEERR AABBSS LLIIMMIITTEEDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 133.80 2111.65

MARCH 24 2005 112.35 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 133.80 2111.65

MARCH 24 2005 112.35 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 133.80 2111.65

MARCH 24 2005 112.35 2016.05






39/52

HEDGING STRATEGIES


AAHHMMEEDDNNAAGGAARR FFOORRGGIINNGGSS LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 203.40 2111.65

MARCH 24 2005 173.70 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 203.40 2111.65

MARCH 24 2005 173.70 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 203.40 2111.65

MARCH 24 2005 173.70 2016.005






40/52

HEDGING STRATEGIES


AALLEEMMBBIICC LLIIMMIITTEEDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 304.55 2111.65

MARCH 24 2005 271.70 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 304.55 2111.65

MARCH 24 2005 271.70 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 304.55

MARCH 24 2005 271.70

CHANGE IN VALUE FROM FEB 28 TO MARCH 24 2005 32.85





41/52

HEDGING STRATEGIES


AALLFFAA LLAAVVAALL IINNDDIIAA LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 720.90 2111.65

MARCH 24 2005 700.10 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 720.90 2111.65

MARCH 24 2005 700.10 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 720.90 2111.65

MARCH 24 2005 700.10 2016.05






42/52

HEDGING STRATEGIES


AALLFFAA LLAAVVAALL IINNDDIIAA LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 100.50 2111.65

MARCH 24 2005 86.20 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 100.50 2111.65

MARCH 24 2005 86.20 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 100.50 2111.65

MARCH 24 2005 86.20 2016.05






43/52

HEDGING STRATEGIES


TTHHEE AANNDDHHRRAA SSUUGGAARRSS LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 139.45 2111.65

MARCH 24 2005 110.25 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 139.45 2111.65

MARCH 24 2005 110.25 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 139.45 2111.65

MARCH 24 2005 110.25 2016.05






44/52

HEDGING STRATEGIES


TTAATTAA CCOOFFFFEEEE





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 313.85 2111.65

MARCH 24 2005 294.80 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 313.85 2111.65

MARCH 24 2005 294.80 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 313.85 2111.65

MARCH 24 2005 294.80 2016.05






45/52

HEDGING STRATEGIES


TTHHEE DDHHAAMMPPUURR SSUUGGAARR MMIILLLLSS LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 159.20 2111.65

MARCH 24 2005 131.15 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 159.20 2111.65

MARCH 24 2005 131.15 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 159.20 2111.65

MARCH 24 2005 131.15 2016.05






46/52

HEDGING STRATEGIES


EEIICCHHEERR MMOOTTOORRSS LLTTDD





STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 334.55 2111.65

MARCH 24 2005 297.90 2016.05





BETA HEDGE STRATEGY




STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 334.55 2111.65

MARCH 24 2005 297.90 2016.05








STOCK

PRICE

INDEX

FUTURES

FEB 28 2005 334.55 2111.65

MARCH 24 2005 297.90 2016.05






47/52

HEDGING STRATEGIES


IS CLASSIC ONE TO ONE THE OPTIMAL HEDGING STRATEGY?

The above investigation carried out reveals that the Classic One to One hedge reduces

the loss more when compared to the other two strategies. While all three strategies

reduce the loss significantly, the Minimum Variance Hedge surprisingly provides the

least effective hedge contrary to the popular expectation. Also it is found that if the beta

value of the stock is less than 1 Classic One to One Hedge is comparitatively best

strategy and in case if beta value of the stock is greater than 1 Beta Hedge strategy is

comparitatively the best strategy.


48/52

HEDGING STRATEGIES


CCHHAAPPTTEERR -- 0055

CCOONNCCLLUUSSIIOONN


49/52

HEDGING STRATEGIES


CCOONNCCLLUUSSIIOONN

It is found that the Classic Hedge Strategy is superior in reducing the loss for the

selected stock when compared to the other two strategies Beta strategy and Minimum

Variance Strategy; however the % reduction of loss varies from stock to stock

.Therefore the Classic Hedge Strategy has been identified as the most optimal hedging

strategy.

It is found that a powerful link exist between the Beta of the stocks and the

corresponding strategies to be followed.


50/52

HEDGING STRATEGIES


REFERENCES

1) C M Madtha, Jyoti Ahulwalia, Hedging With Stock Index Futures , ICFAI Journal,

May 2005, pp 64 732) D C Patwari,Financial Futures & Options in Indian Perspective , 2000 Edition,

pp 152-190.

3) D C Patwari, Futures & Options in Indian Perspective , 2001 Edition, pp 128-171.

4) B Brahmaiah, P Subba Rao, Financial Futures & Options, 1998 Edition,

pp213-246.


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HEDGING STRATEGIES


BIBLIOGRAPHY

www.5paisa.com/scho/ch10.html

www.indiainfoline.com

www.thehindubusinessline.comwww.Chartered Treasury Manager

www.nse-india.com

ICFAI Journal Of Applied Finance ,May 2005


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HEDGING STRATEGIES

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Identification of Optimal Hedging Strategy

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