53928830 Impact of Gold Prices on SENSEX Sreekanta M 0447

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AN ANALYSIS TO STUDY THE IMPACT OF GOLD PRICE ON SENSEX

Submitted in partial fulfillment of the

requirements for MBA Degree of Bangalore University

Submitted By Sreekanta.M

Registration Number: 04XQCM6095

Under the Guidance Of: Professor S. Santhanam.

M.P.BIRLA INSTITUTE OF MANAGEMENT Associate Bharatiya Vidya Bhavan

Race Course Road, Bangalore-560001

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DECLARATION I hereby declare that the Project report on �An analysis to study the impact

of gold prices on SENSEX� is a record of independent work carried out by

me, towards partial fulfillment of the requirements for MBA course of

Bangalore University at M.P.Birla Institute of Management.

This has not been submitted in part or full towards any other degree or

Diploma of Bangalore University or any other University

Date: 12/06/2006 SREEKANTA.M Place: Bangalore 04XQCM6095

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PRINCIPAL�S CERTIFICATE This is to certify that this report titled �An analysis to study the impact of

gold prices on SENSEX� is the result of project work undergone by

Sreekanta.M, bearing the Register Number 04XQCM6095, under the

guidance of Prof. S.Santhanam. This has not formed a basis for the award of

any Degree/Diploma for any other University.

Place : Bangalore Date : 12-06-2006 Dr. Nagesh.S.Malavalli

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GUIDE�S CERTIFICATE

This is to certify that the dissertation entitled �An analysis to study the

impact of gold prices on SENSEX� is an original study conducted by

Sreekanta.M, bearing register number 04XQCM6095, of M. P. Birla

Institute of Management, Associate Bharatiya Vidya Bhavan, under my

guidance.

This has not formed the basis for the award of any Degree/Diploma by

Bangalore University or any other University.

I also certify that he has fulfilled all the requirements under the covenant

governing the submission of dissertation to the Bangalore University for the

award of MBA Degree.

Date : 12-06-2006 Professor S. Santhanam

Place : Bangalore

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ACKNOWLEDGEMENT A teacher is a perennial source of inspiration and guidance in all the

academic activities of his students throughout. I whole-heartedly extend my

deep and sincere gratitude to Dr.Nagesh.S.Malavalli, principal of MPBIM,

for his continuous guidance and help provided for completing this

research study.

I am also thankful to Prof. S.S. Santhanam, M.P Birla Institute of

Management for sharing his expertise in the field of Statistics with me

whenever I approached him.

I also express my gratitude to all friends and family members for extending

their helping hand whenever I approached them. Without their help this

research could not have been presented in a proper manner.

Sreekanta.M

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INDEX

CHAPTER 1 INTRODUCTION 01 CHAPTER 2 LITERATURE REVIEW 07 CHAPTER 3 RESEARCH DESIGN 13 CHAPTER 4 RESEARCH METHODOLOGY 31 CHAPTER 5 EXAMINATION OF STOCK MARKET 28 CHAPTER 6 ANALYSIS & FINDINGS 37 CHAPTER 7 CONCLUSIONS 46

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CHAPTER 1

INTRODUCTION

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Abstract

This paper reexamines the relationship between stock prices and one of best investment

considered in India i.e. gold prices for 2005 using daily time series data. The study uses

Granger non causality test procedure developed by Toda and Yamamoto(1995). The

study looks after the rise of gold market in India. The future of the gold and Gold price

movements are determined by the perception of gold as a `store of value' rather than its

fundamentals as a commodity. The precious metal's value is also determined by such

factors as inflation, interest rates and the presence of lucrative alternative investment

avenues in the economy.

The causal relationship tested between the BSE index and gold prices. Gold price is

included in the model as an additional variable, to examine whether gold price contain

any additional significant information about price movements. Since gold is an important

saving instrument in India and is very often used as a hedge against inflation, it is

expected that gold may be looked upon as alternative asset for those holding idle money,

for speculative purposes.

With the ADF UNIT ROOT TEST and JOHANSENS COINTEGRATION TEST We

find that the trend lines are deterministic and on applying GRANGERS CAUSALITY

TEST We find that gold prices have no relation with the Sensex returns.

Introduction:

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A significant amount of literature now exists that examines the relationship between

stock market returns and a range of macro economic and financial variables over a

number of different stock markets and time periods. Now a days financial economics

provide a number of models that helps to examine the relationship. The return on stocks

is highly sensitive to both fundamentals and expectations. The latter in turn is influenced

by the fundamentals which may be based on either rational or adaptive expectation

models, as well as by many subjective factors which are unpredictable and also non

quantifiable.

Empirical studies indicate that once the financial deregulation takes place, the stock

market becomes more sensitive to both domestic and external factors. The domestic

fundamentals, in principles, are related to domestic macro economic conditions. However

there may be a lot of divergence between the overall state of the economy and individual

stock return. The external factors influencing the stock return would be stock prices in

global economy, the interest rate and the exchange rate. The early survey on the

behaviour of stock return was done by Famma(1970). The Famma Theory of efficient

market hypothesis suggests that stock markets are efficient because they reflect the

fundamental macro economic behavior.

The term efficiency implies that a financial market incorporates all relevant information

(including macro economic fundamentals) in the market, in which case the outcome is the

best possible under the circumstances . Many empirical studies have been conducted to

examine the relationship between stock price and macro economic variables and findings

are generally mixed. Famma and French (1989) and Poterba and Summers (1988) have

shown that the U.S. stock returns have a mean reverting tendency and can be predictable

to some extent .

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Similar results have been found by MacDonald and Power (1991) that U.K. stock returns

have a mean reverting-tendency and so can be predicted. Subsequent studies like

Famma(1981), Famma and Gibbons(1982) Summers(1986) and Chen(1991) verified that

the efficient market hypothesis holds in US market, and there was significant linkage

between US stock market on one hand and real economic variables, such as, GDP,

industrial production, inflation and unemployment on the other hand. Naj and

Rahman(1991) studied the relationship between volatility of stock return and of

macroeconomic variables in four developed countries and confirmed the relationships

Fang and Lee(1990) studied the long term relationships between stock return on the one

hand and GNP, inflation and money supply on the other in Taiwan and concluded that the

efficient market hypothesis is not valid for an emerging market. Fang and Loo (1995)

studied the relationship between stock return volatility and international trade for four

Asian countries. They however, found evidence in favor of the efficient market

hypothesis. Their empirical results based on vector autoregressive model(VAR)

suggested that the stock return volatility in the four markets respond to information on

trade.

The behavior of stock price (BSE) in relation to some key macro economic variables in

India during the scam period 1992 was studied by Bhattacharya and Chakravarty (1994).

Their dynamic forecasts indicate that the behavior of stock price is unrelated to key

macro variables. Mukherjee and Naka(1995) explored the relationship between exchange

rate, inflation , money supply, real economic activity, long term government bond rate

and call money rate with the Japanese stock market. Their empirical result suggested that

cointegration relation existed and positive relationship was found between the Japanese

industrial production and stock return. Chaudhuri and Koo(2001) investigated the

volatility of stock returns in some Asian emerging markets in terms of the volatility of

domestic and external factors, found that both domestic macroeconomic variables and

international variables have significant impact on stock return volatility. Their empirical

results suggest the presence of a significant contagion effect and integration of capital

market in this region. The results also suggested the role of government in terms of fiscal

and monetary policy in smooth functioning of the stock market is crucial in this region

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In Indian context , Bhattacharya and Mukherjee (2002) studied the nature of the causal

relationship between stock prices and macro aggregates in India by using the

methodology proposed by Toda and Yamamoto for the period of 1992-93 to 2000-

2001.Their results show that there is no causal relationship between stock price and

macro economic variables like money supply, national income and interest rate but there

exists a two way causation between stock price and rate of inflation. According to them

index of industrial production lead the stock price.

They further investigated the causal linkage between stock prices and macro economic

aggregates in the foreign sector in India like exchange rate, foreign exchange reserves

and value of trade balance by applying the technique of co integration and long run

Granger non causality test developed by T&Y(1995). Their results suggested that there is

no causal linkage between stock price and the three variables. Thus BSE sensitive index

neither leads these three variables nor do they lead the BSE sensitive index. They also

added that if these types of results hold for subsequent periods then it can be said that

Indian stock market is approaching towards informational efficiency with the three

variables, ie exchange rate, foreign exchange reserves and trade balance.

Mishra (2004) examined the relationship between stock market and foreign exchange

markets using Granger causality test and Vector Auto Regression technique .They used

monthly data for stock return exchange rate, interest rate and demand for money for the

period 1992 to 2002. The study found that there exists a unidirectional causality between

the exchange rate and interest rate and also between the exchange rate return and demand

for money. The study also suggested that there is no Granger causality between the

exchange rate return and stock return . The BSE sensex is about to cross the five digit

points mark and will be major index in the Asian market so it compel us to think whether

the market is expected to remain bullish in the long run or not? Is there any macro

economic variables which causes this bullish behavior of stock price in India?

In reference to the above statements this paper attempts to examine whether the macro

economic variables causes the recent bull phase of stock price in India . The study uses

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Granger non causality test by Toda and Yamamoto(1995)( T&Y) for the period of April

1991 to December2005.The causal relationship tested between the BSE index and

important key macro economic variable such as gold prices. Gold price is included in the

model as an additional variable, to examine whether gold price contain any additional

significant information about price movements. Since gold is an important saving

instrument in India and is very often used as a hedge against inflation, it is expected that

gold may be looked upon as alternative asset for those holding idle money, for

speculative purposes.

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CHAPTER 2

LITERATURE REVIEW

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Gold market in India.

Eternally attractive to mankind, gold has found its principal use as a store of value. Its

beauty has made it popular in decoration. Gold has also become an increasingly

important industrial metal. Because of its rarity and its durability, gold has been almost

universally acceptable as money for thousands of years. Gold is the most prominent of

the noble metals (gold, silver, platinum, and other platinum group metals), so termed

because of their inertness, or reluctance to enter into chemical reactions. Gold will not

react with common acids. Gold, the most famous of all precious metals, is widely sought

after throughout the world for both its investment qualities and industrial properties.

Indeed, gold traditionally has served three functions: as a monetary instrument, as a

financial asset, and as a raw material primarily used in jewelry and decorative objects.

As an investment, gold typically is viewed as a financial asset that will maintain its value

during times of political, social, or economic distress. As such, gold can provide

individual and institutional investors alike with a portfolio safety net against sharp

downward spikes in complementary assets such as stocks and bonds. While investment

demand is important, the largest use for gold is in jewelry, with the majority of use

occurring in the United States, Japan, Italy, India, China, and Thailand. Jewelry

production has been growing at a robust pace in the developing countries of Southeast

Asia and the Middle East since 1988. Gold also is used in electronic connectors and

dental alloys.

Gold is mined in more than 76 countries around the world, with the large number of

development projects in these countries expected to keep production growing well into

the next century. Currently, South Africa is the largest gold producing country, followed

by the United States, Australia, and Canada. Millions of people all over the world

continue to use gold as a hedge against inflation and as a basic form of savings and a

reliable store of value during times of economic uncertainty or political upheaval.

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In 2003, the price of standard gold in the Mumbai market rose 11 per cent from Rs 5,580

per 10 grams to end the year at Rs 6,175. Continuing its unabated rally, gold now trades

at about Rs 625 per gram. The year thus saw a sharp upswing in the price for ten grams,

which had hovered around the Rs 4,000 mark for the five years between 1996 and 2001.

The quantum of rise in 2003 was, to an extent, checked by the appreciation in the value

of the rupee and the steep cut in import duties. The international price of gold moved at a

much faster pace, gaining 20 per cent in 2003. It now quotes close to $419 per troy ounce

(one troy ounce = 31.1035 grams).

Behind the price divergence India imports most of its gold requirements. Hence, price

movements should largely be in line with international prices. Interestingly, though, this

has never been so. There have been price variations, caused by the fluctuations in

exchange rate and policy changes on the import duty front. Between 1997 and 2002,

international gold prices edged up just 1 per cent. In contrast, in Mumbai the price rose

16 per cent. During this period there was a consistent depreciation in the value of the

rupee, which reached a low of Rs 49 to a dollar. The reversal of this trend in 2003 was

notable, with forex reserves crossing $100 billion. The 5 per cent appreciation in the

rupee vis-à-vis the dollar made dollar-denominated gold imported into India cheaper and

capped the rise in domestic prices.

The steep cut in import duties over the years has also narrowed the gap between

international and domestic prices. Import duties on gold were slashed from Rs 400 per 10

gm in 1999 to Rs 100 per 10 gm in 2003. These two factors explain the wide divergence

in the returns from gold in the domestic and international markets. Shining performance

The year 2003 was a bonanza for those who set much store by the traditional value of

gold. Equities had a dream year too. But it was the yellow metal that outperformed most

fixed-income investment options, gaining about 11 per cent in value. And this in a year

when your savings or fixed deposit earned just about five per cent.

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Even small saving schemes or bonds earned, at best, an 8.5 per cent return. At the global

level, too, gold regained fancy, even if just as a bulwark against the dollar, which has

been on a relentless decline. Gold prices are seldom governed by fundamentals. The

direction of its movement is governed by various external factors, such as central bank

sales, tendency to shift in and out of gold depending upon currency, speculative activity

and the US economy's strength.

Weak dollar drives gold

Gold price movements are determined by the perception of gold as a `store of value'

rather than its fundamentals as a commodity. The precious metal's value is also

determined by such factors as inflation, interest rates and the presence of lucrative

alternative investment avenues in the economy. In the past two years, gold has regained

popularity as a `store of value'. The weakening dollar and the prevailing low interest rates

at the global level have left investors with limited alternative investment avenues.

The spectre of even a moderate increase in inflation levels, fuelled by the spurt in

commodity prices, would further squeeze the real rate of return on debt investments.

This has forced investors to look for a relatively risk-free investment option. In these

circumstances, there has been a rush towards gold as it is an eternal asset with an intrinsic

value. For long, dollar-denominated instruments were considered the favourite assets for

central banks and institutional investors.

But, of late, the consistent depreciation in the value of the dollar vis-à-vis currencies such

as the euro and the yen has forced a shift in the investment strategy. The euro appreciated

20 per cent against the dollar during the year. The US' mounting current account deficit

has been eroding the value of the dollar.

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As of 2002, the deficit, at $435.2 billion, was over 5 per cent of the US' GDP. A

mounting current account deficit means its debt obligation to foreign countries has been

increasing, weakening the purchasing power of the dollar. Asian countries, especially

China and Japan, hold over 30 per cent of the US' external debt. A weakness in the value

of the dollar would dent the returns on the dollar-denominated reserve assets held by

them. To overcome this problem, China has been investing a larger part of its reserves in

gold.

China is now one of the top ten countries holding a large quantum of gold in its reserves,

a distinction it has gained in the past two years. Its gold reserves increased from 391

tonnes in December 2001 to 600 tonnes in December 2003.

China's unwillingness to let the Yuan appreciate, much to the discomfiture of the US, has

also played a significant role in the firm trend in gold prices. Empirical research proves

that the value of gold measured in terms of its purchasing power parity has remained

unchanged in the long run, even over about 2,500 years. Hence, in the current

circumstances, gold has regained its position as a `store of value.'

Investment demand picks up

The gold price rally could also be attributed to the lack of alternative investment options.

Globally, interest rates have fallen sharply. The US Fed rates are at a 45-year low of 1 per

cent. The Federal Reserve has not indicated that it will raise interest rates as it would

hamper the economic growth that is now picking up after a prolonged slowdown. A

similar situation in most other parts of the world has led to an increased investment

demand for gold.

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Outlook

In the near term, gold prices are likely to show a firm undertone. Their direction would

hinge largely on how the dollar moves. If it remains weak vis-à-vis other currencies and

if interest rates remain stable, gold prices may get a boost.

The trend of a rapidly widening US current account deficit may get accentuated as its

economy is now on a recovery path and needs more capital from the rest of the world.

This looming risk may ensure that the dollar continues to remain weak in the near future.

Interest rates appear to be stabilizing after the relentless rate-cutting over the past three

years; a sharp spike from the current levels, however, appear unlikely as central bankers

may not want to disturb the trends of economic revival in the US, Europe and Japan.

The price performance of gold over the past two years may, however, not be repeated.

But even if returns move into single-digit territory, the precious metal would still be

competitive, at least for the short term, as the yield on debt is unlikely to be vastly

superior.

For retail investors, though, it may be better not to divert much of the portfolio into gold.

Gold in a portfolio can be used for diversification purposes to lend stability but it also

tends to drag returns.

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CHAPTER 3

RESEARCH DESIGN

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OBJECTIVE:

To study if there is any dynamic relationship between the volatility in the stock market

with the fluctuations in the gold prices. Analyzing the causal relation of the gold prices

with Sensex returns

JUSTIFICATION AND RELEVANCE:

Is gold a golden investment?

Gold and silver have been sought and prized since prehistoric times. They have also been

both a cause of war and a medium of exchange.

Gold is the standard by which the value of anything is assessed; it is universally accepted.

Silver does not lag behind in global trade markets and as an investment. In the code of

Menes, an Egyptian ruler of 3100 BC, it is declared that �one unit of gold is equal to two-

and-a-half units of silver in value�. Silver was actually more widely employed as the

standard of value until the nineteenth century.

According to the World Gold Council Report, India stands today as the world�s largest

single market for gold consumption. In developing countries, people have often trusted

gold as a better investment than bonds and stocks.

Gold and silver have been popular in India because historically these acted as a good

hedge against inflation. In that sense these metals have been more attractive than bank

deposits or gilt-edged securities.

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Despite recent hiccups, gold is an important and popular investment for many reasons:

In many countries gold remains an integral part of social and religious customs,

besides being the basic form of saving. Shakespeare called it �the saint-seducing gold�.

Superstition about the healing powers of gold persists. Ayurvedic medicine in India

recommends gold powder and pills for many ailments.

Gold is indestructible. It does not tarnish and is also not corroded by acid � except by a

mixture of nitric and hydrochloric acids.

Gold has aesthetic appeal. Its beauty recommends it for ornament making above all

other metals.

Gold is so malleable that one ounce of the metal can be beaten into a sheet covering

nearly a hundred square feet.

Gold is so ductile that one ounce of it can be drawn into fifty miles of thin gold wire.

Gold is an excellent conductor of electricity; a microscopic circuit of liquid gold

�printed� on a ceramic strip saves miles of wiring in a computer.

Gold is so highly valued that a single smuggler can carry gold worth Rs. 50 lakh

underneath his shirt.

Gold is so dense that all the 90,000 tonnes estimated to have been mined through

history could be transported by one single modern super tanker.

Finally, gold is scam-free. So far, there have been no Mundra-type or Mehta-type

scams in gold.

Thus, the lure of this yellow metal continues.

On the other hand, it is interesting to note that apart from its aesthetic appeal gold has no

intrinsic value. You cannot eat it, drink it, or even smell it. This aspect of gold compelled

Henry Ford, the founder of Ford Motors, to conclude that �gold is the most useless thing

in the world�.

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DATA DESCRIPTION

We obtain the aggregate daily gold prices AND RETURNS OF SENSEX, that is, from

January 2005 to Dec 2006 from India Infoline and Equity Master. The Reserve Bank of

India and the Securities Exchange Board of India also provide the data on FII SENSEX.

We look at the relationship between VOLUME and market returns using both, the returns

on the Bombay stock exchange (BSE).. The data on market index is obtained from the

respective stock exchanges. The return for market i for month t would be given by;

Established in 1875, BSE is not only the oldest stock exchange in India, but is also the

oldest in Asia. It accounts for over one-third of the total trading volume in the country.

The National Stock Exchange (NSE), located in Bombay, was set up in 1993 to

encourage stock exchange reform through system modernization and competition. It

opened for trading in mid-1994. Since then the NSE has made major strides and is now

the dominant stock exchange in the country. Most other studies on Indian market use the

BSE Sensex index to compute market returns. With NSE being an equally prominent

stock exchange in India, we also use the S&P CNX Nifty index to compute returns.

Between the two exchanges, NSE being demutualized provides a better market quality.

With lower execution cost, lower price volatility and higher liquidity compared to BSE,

NSE has emerged to be superior by providing improved market quality and high

standards of investor protection .

BSE Sensex is a basket of 30 constituent stocks representing a sample of large, liquid and

representative companies. The base year of SENSEX is 1978-79 and the base value is

100. The index is widely reported in both domestic and international markets through

print as well as electronic media. The Index was initially calculated based on the �Full-

market capitalization� methodology but was shifted to the �Free-float methodology� with

effect from September 1, 2003.

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SENSEX: THE BAROMETER OF INDIAN ECONOMY

For the premier Stock Exchange that pioneered the stock broking activity in India, 128

years of experience seems to be a proud milestone. A lot has changed since 1875 when

318 persons became members of what today is called "The Stock Exchange, Mumbai" by

paying a princely amount of Re1.Since then, the country's capital markets have passed

through both good and bad periods. The journey in the 20th century has not been an easy

one. Till the decade of eighties, there was no scale to measure the ups and downs in the

Indian stock market. The Stock Exchange, Mumbai (BSE) in 1986 came out with a stock

index that subsequently became the barometer of the Indian stock market.

SENSEX is not only scientifically designed but also based on globally accepted

construction and review methodology. First compiled in 1986, SENSEX is a basket of 30

constituent stocks representing a sample of large, liquid and representative companies.

The base year of SENSEX is 1978-79 and the base value is 100. The index is widely

reported in both domestic and international markets through print as well as electronic

media.

The Index was initially calculated based on the "Full Market Capitalization"

methodology but was shifted to the free-float methodology with effect from September 1,

2003. The "Free-float Market Capitalization" methodology of index construction is

regarded as an industry best practice globally. All major index providers like MSCI,

FTSE, STOXX, S&P and Dow Jones use the Free-float methodology.

Due to is wide acceptance amongst the Indian investors; SENSEX is regarded to be the

pulse of the Indian stock market. As the oldest index in the country, it provides the time

series data over a fairly long period of time (From 1979 onwards). Small wonder, the

SENSEX has over the years become one of the most prominent brands in the country.

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The growth of equity markets in India has been phenomenal in the decade gone by. Right

from early nineties the stock market witnessed heightened activity in terms of various

bull and bear runs. The SENSEX captured all these events in the most judicial manner.

One can identify the booms and busts of the Indian stock market through SENSEX.

SENSEX Calculation Methodology

SENSEX is calculated using the "Free-float Market Capitalization" methodology. As per

this methodology, the level of index at any point of time reflects the Free-float market

value of 30 component stocks relative to a base period. The market capitalization of a

company is determined by multiplying the price of its stock by the number of shares

issued by the company. This market capitalization is further multiplied by the free-float

factor to determine the free-float market capitalization. The base period of SENSEX is

1978-79 and the base value is 100 index points. This is often indicated by the notation

1978-79=100. The calculation of SENSEX involves dividing the Free-float market

capitalization of 30 companies in the Index by a number called the Index Divisor. The

Divisor is the only link to the original base period value of the SENSEX. It keeps the

Index comparable over time and is the adjustment point for all Index adjustments arising

out of corporate actions, replacement of scrips etc. During market hours, prices of the

index scrips, at which latest trades are executed, are used by the trading system to

calculate SENSEX every 15 seconds and disseminated in real time.

Dollex-30

BSE also calculates a dollar-linked version of SENSEX and historical values of this

index are available since its inception.

25

Understanding Free-float Methodology Concept:

Free-float Methodology refers to an index construction methodology that takes into

consideration only the free-float market capitalization of a company for the purpose of

index calculation and assigning weight to stocks in Index. Free-float market capitalization

is defined as that proportion of total shares issued by the company that are readily

available for trading in the market. It generally excludes promoters' holding, government

holding, strategic holding and other locked-in shares that will not come to the market for

trading in the normal course. In other words, the market capitalization of each company

in a Free-float index is reduced to the extent of its readily available shares in the market.

In India, BSE pioneered the concept of Free-float by launching BSE TECk in July 2001

and BANKEX in June 2003. While BSE TECk Index is a TMT benchmark, BANKEX is

positioned as a benchmark for the banking sector stocks. SENSEX becomes the third

index in India to be based on the globally accepted Free-float Methodology.

Major advantages of Free-float Methodology:

A Free-float index reflects the market trends more rationally as it takes into

consideration only those shares that are available for trading in the market.

Free-float Methodology makes the index more broad-based by reducing the

concentration of top few companies in Index. For example, the concentration of

top five companies in SENSEX has fallen under the free-float scenario thereby

making the SENSEX more diversified and broad-based.

A Free-float index aids both active and passive investing styles. It aids active

managers by enabling them to benchmark their fund returns vis-à-vis an

investable index. This enables an apple-to-apple comparison thereby facilitating

better evaluation of performance of active managers. Being a perfectly replicable

portfolio of stocks, a Free-float adjusted index is best suited for the passive

managers as it enables them to track the index with the least tracking error.

26

Free-float Methodology improves index flexibility in terms of including any stock

from the universe of listed stocks. This improves market coverage and sector

coverage of the index. For example, under a Full-market capitalization

methodology, companies with large market capitalization and low free-float

cannot generally be included in the Index because they tend to distort the index by

having an undue influence on the index movement. However, under the Free-float

Methodology, since only the free-float market capitalization of each company is

considered for index calculation, it becomes possible to include such closely held

companies in the index while at the same time preventing their undue influence

on the index movement.

Globally, the Free-float Methodology of index construction is considered to be an

industry best practice and all major index providers like MSCI, FTSE, S&P and

STOXX have adopted the same. MSCI, a leading global index provider, shifted

all its indices to the Free-float Methodology in 2002. The MSCI India Standard

Index, which is followed by Foreign Institutional Investors (FIIs) to track Indian

equities, is also based on the Free-float Methodology. NASDAQ-100, the

underlying index to the famous Exchange Traded Fund (ETF) - QQQ is based on

the Free-float Methodology.

Definition of Free-float:

Share holdings held by investors that would not, in the normal course come into the open

market for trading are treated as 'Controlling/ Strategic Holdings' and hence not included

in free-float. In specific, the following categories of holding are generally excluded from

the definition of Free-float:

Holdings by founders/directors/ acquirers which has control element

Holdings by persons/ bodies with "Controlling Interest"

Government holding as promoter/acquirer

Holdings through the FDI Route

Strategic stakes by private corporate bodies/ individuals

Equity held by associate/group companies (cross-holdings)

Equity held by Employee Welfare Trusts

27

Locked-in shares and shares which would not be sold in the open market in

normal course.

The remaining shareholders would fall under the Free-float category.

Determining Free-float factors of companies:

BSE has designed a Free-float format, which is filled and submitted by all index

companies on a quarterly basis with the Exchange. The Exchange determines the Free-

float factor for each company based on the detailed information submitted by the

companies in the prescribed format. Free-float factor is a multiple with which the total

market capitalization of a company is adjusted to arrive at the Free-float market

capitalization. Once the Free-float of a company is determined, it is rounded-off to the

higher multiple of 5 and each company is categorized into one of the 20 bands given

below. A Free-float factor of say 0.55 means that only 55% of the market capitalization

of the company will be considered for index calculation

Index Closure Algorithm

The closing SENSEX on any trading day is computed taking the weighted average of all

the trades on SENSEX constituents in the last 30 minutes of trading session. If a

SENSEX constituent has not traded in the last 30 minutes, the last traded price is taken

for computation of the Index closure. If a SENSEX constituent has not traded at all in a

day, then its last day's closing price is taken for computation of Index closure. The use of

Index Closure Algorithm prevents any intentional manipulation of the closing index

value.

Maintenance of SENSEX

One of the important aspects of maintaining continuity with the past is to update the base

year average. The base year value adjustment ensures that replacement of stocks in Index,

28

additional issue of capital and other corporate announcements like 'rights issue' etc. do

not destroy the historical value of the index. The beauty of maintenance lies in the fact

that adjustments for corporate actions in the Index should not per se affect the index

values.

The Index Cell of the exchange does the day-to-day maintenance of the index within the

broad index policy framework set by the Index Committee. The Index Cell ensures that

SENSEX and all the other BSE indices maintain their benchmark properties by striking a

delicate balance between frequent replacements in index and maintaining its historical

continuity. The Index Committee of the Exchange comprises of experts on capital

markets from all major market segments. They include Academicians, Fund-managers

from leading Mutual Funds, Finance-Journalists, Market Participants, Independent

Governing Board members, and Exchange administration.

On-Line Computation of the Index:

During market hours, prices of the index scrips, at which trades are executed, are

automatically used by the trading computer to calculate the SENSEX every 15 seconds

and continuously updated on all trading workstations connected to the BSE trading

computer in real time. Adjustment for Bonus, Rights and Newly issued Capital:

The arithmetic calculation involved in calculating SENSEX is simple, but problem arises

when one of the component stocks pays a bonus or issues rights shares. If no adjustments

were made, a discontinuity would arise between the current value of the index and its

previous value despite the non-occurrence of any economic activity of substance. At the

Index Cell of the Exchange, the base value is adjusted, which is used to alter market

capitalization of the component stocks to arrive at the SENSEX value.

The Index Cell of the Exchange keeps a close watch on the events that might affect the

index on a regular basis and carries out daily maintenance of all the 14 Indices.

29

Adjustments for Rights Issues:

When a company, included in the compilation of the index, issues right shares, the free-

float market capitalisation of that company is increased by the number of additional

shares issued based on the theoretical (ex-right) price. An offsetting or proportionate

adjustment is then made to the Base Market Capitalisation (see 'Base Market

Capitalisation Adjustment' below).

Adjustments for Bonus Issue:

When a company, included in the compilation of the index, issues bonus shares, the

market capitalisation of that company does not undergo any change. Therefore, there is

no change in the Base Market Capitalisation, only the 'number of shares' in the formula is

updated.

Other Issues:

Base Market Capitalisation Adjustment is required when new shares are issued by way of

conversion of debentures, mergers, spin-offs etc. or when equity is reduced by way of

buy-back of shares, corporate restructuring etc.

Base Market Capitalisation Adjustment:

The formula for adjusting the Base Market Capitalisation is as follows:

New Base Market = Old Base Market X New Market Capitalisation / Old Base

capitalisation

30

To illustrate, suppose a company issues right shares which increases the market

capitalisation of the shares of that company by say, Rs.100 crores. The existing Base

Market Capitalisation (Old Base Market Capitalisation), say, is Rs.2450 crores and the

aggregate market capitalisation of all the shares included in the index before the right

issue is made is, say Rs.4781 crores. The "New Base Market Capitalisation " will then be:

This figure of 2501.24 will be used as the Base Market Capitalisation for calculating the

index number from then onwards till the next base change becomes necessary.

2450 X (100+4781) = 2501.24 crores

4781

Criteria for Selection and Review of SENSEX Constituents

The scrip selection and review policy for BSE Indices is based on the objective of:

Improvement

Transparency

Simplicity

Qualification Criteria:

The general guidelines for selection of constituent scrips in SENSEX are as follows:

A. Quantitative Criteria:

1. Final Rank: The scrip should figure in the top 100 companies listed by Final

Rank. The final rank is arrived at by assigning 75% weightage to the rank on the

basis of six-month average full market capitalisation and 25% weightage to the

liquidity rank based on six-month average daily turnover & six-month average

impact cost.

31

2. Trading Frequency: The scrip should have been traded on each and every trading

day for the last six months. Exceptions can be made for extreme reasons like scrip

suspension etc.

3. Market Capitalization Weightage: The weight of each scrip in SENSEX based on

six-month average Free-Float market capitalisation should be at least 0.5% of the

Index.

4. Industry Representation: Scrip selection would take into account a balanced

representation of the listed companies in the universe of BSE. The index

companies should be leaders in their industry group.

5. Listed History: The scrip should have a listing history of at least 3 months on

BSE. However, the Committee may relax the criteria under exceptional

circumstances.

B. Qualitative Criteria:

Track Record In the opinion of the Committee, the company should have an acceptable

track record.

Index Review Frequency:

The Index Committee meets every quarter to review all BSE indices. However, every

review meeting need not necessarily result in a change in the index constituents. In case

of a revision in the Index constituents, the announcement of the incoming and outgoing

scrips is made six weeks in advance of the actual implementation of the revision of the

Index.

32

BSE India Today

India's stockmarket has been among the most volatile in the region, with a sell-off on

May 22nd causing the 30-share Bombay Sensitive Index (Sensex) to lose as much as 10%

of its value�triggering an automatic suspension of trading for one hour. With a rebound

after this hiatus, reportedly led by state-run mutual funds and institutions, the Sensex

recovered to record a 4.2% loss for the day. On May 23rd it rose 3.3% to close at

10,822.78, breaking a losing streak which had seen the index lose around 14% of its

value since May 17th.

The Sensex had doubled in value in 2005 and hit a record on May 10th of around

12,600�up around a third in year-to-date terms. But a correction had long been

expected. Foreign investors spent a record US$10.7bn on Indian shares in 2005, and so

far this year they have spent a net US$3.8bn. Uncertainty about the global economy and

US monetary policy, coupled with concerns over the sustainability of India's economic

boom, brought a slightly larger correction than had been expected. Unsubstantiated fears

that the government's Left Front allies would insist on higher taxes on foreign investors

also caused market jitters.

More fundamental problems belie the confidence investors had placed in Indian equities

until recently. India's stock market lacks depth and liquidity�market capitalisation as a

percentage of GDP remains low, and only a relatively small number of companies are

actively traded�so that new capital inflows tend to trigger price increases. The trend also

reflects the high returns that investments in highly profitable Indian companies offer, as

well as foreign institutional investors' desire to exploit these opportunities, made possible

by economic liberalisation. However, the increasingly common assertion that the ongoing

Indian boom is "different" and "warranted by fundamentals" sounded naïve, and has been

tempered by the recent volatility.

33

VOLATILITY OF BSE SENSEX

As the potential for spectacular profit declines, FIIs may be less willing to rush in, the

way they have done over the past few years. But that may not be as bad a thing to happen

as it�s sometimes made out to be. a fair amount of flak for intervening against the bears in

the stock markets. There is little doubt that when the government lines up on the side of

the bulls, it distorts the market values of shares. The popular argument about protecting

investors too does not hold as those who have benefited from a spectacular boom must

know that they stand the risk of an equally spectacular bust.

And yet, if we look at the stock markets not in isolation, but in the context of capital

flows in and out of the economy, the FM had no option but to intervene. Indeed, if he is

to be faulted it is not because he intervened to prevent a crisis but because the

government refuses to see that such crises are inherent in allowing foreign institutional

investors to bloat the size of the stock markets. With the sensex having lost over 800

points in a day, panic could easily have resulted in an even more dramatic drop the next

day. Sooner rather than later this would have encouraged flight of FII capital out of the

country.

Since FII investments are currently much greater than foreign direct investment (FDI),

this would have had an impact on the rupee. In fact, the pressure on the rupee was

beginning to show. Even if the rupee did not collapse dramatically this would have, in

turn, had a dampening effect on growth by raising the costs of imports including oil. The

trouble is the instruments the FM has at his disposal to influence the stock markets are

deeply flawed. Getting state-controlled institutions to buy shares may appear very

effective in the short run as the market slide was halted. But in this effectiveness lie the

seeds of an even bigger crisis. The reason the FII outflow was halted is because these

investors realised they were now in a no-loss situation. They could keep buying shares

and book profits at higher prices.

34

The risk of their profit-taking leading to a collapse in the markets was now minimised

since the government could be relied upon to step in and prevent a dramatic fall in prices.

But as the FII investment keeps growing, the costs of stepping in to provide stability will

also increase. And a point could well be reached where the investments required to

prevent a collapse are well beyond the capabilities of government-controlled institutions.

The collapse then would result in a full-blown currency crisis.

To make matters worse, far from offering the FM more and better instruments to stabilise

capital flows, the government may in fact be moving to remove the brakes that already

exist. If the FII pressure in the stock markets did not affect foreign direct investment it

was because of the absence of full convertibility. But with the prime minister revealing

an ideological passion to push towards full convertibility this critical safeguard will be

removed. The flight of FIIs in the stock markets will then be accompanied by the outflow

of foreign direct investment in the rest of the economy.

The way out of this potentially dangerous situation is to ensure that the markets become

inherently less volatile. In theory this should happen if there are more long-term investors

in the market. They will see an opportunity when speculators drop prices well below the

intrinsic value of the share, thereby limiting the fall in prices.

Conversely when speculators take prices to unrealistically high levels, the long-term

investors will bring sanity into the market by booking profits. A case can then be made to

bring in more long-term investors, especially pension funds, into the market.

In practice, though things don�t always work out that way. When price-earning ratios

remain at extraordinarily high levels, long-term investors too have to recognise that

prices may not remain all that sensitive to earnings. Instead long-term expectations of the

35

price of a share too may be determined by what speculators do to a share. The long-term

investors are then also forced to be guided by speculators.

This has happened to several mutual funds, and there is no guarantee that pension funds

will be immune to this lure. The critical task then is to bring price-earning ratios closer to

a level where actual earnings play a more important role in the decision making of long-

term investors. This would happen if there are more shares that attract the attention of all

investors. Some companies may have to be groomed to play this role. This could happen

by introducing an effective, separate Small Cap market. This market would be designed

in such a way that it attracts minimal attention from global speculators, if that. Such a

market would allow new companies to be traded in the initial years without having to

cope with the volatility that global speculators bring. And when these shares come in

their own they can be graduated into the big league.

Analysis of Indian stock market BSE Sensex Index

The BSE SENSEX is not only scientifically designed but also based on globally accepted

construction and review methodology. First compiled in 1986, SENSEX is a basket of 30

constituent stocks representing a sample of large, liquid and representative companies.

The base year of SENSEX is 1978-79 and the base value is 100. The index is widely

reported in both domestic and international markets through print as well as electronic

media.

The Index was initially calculated based on the "Full Market Capitalization"

methodology but was shifted to the free-float methodology with effect from September 1,

2003. The "Free-float Market Capitalization" methodology of index construction is

regarded as an industry best practice globally. All major index providers like MSCI,

FTSE, STOXX, S&P and Dow Jones use the Free-float methodology.

36

Due to is wide acceptance amongst the Indian investors; SENSEX is regarded to be the

pulse of the Indian stock market. As the oldest index in the country, it provides the time

series data over a fairly long period of time (From 1979 onwards). Small wonder, the

SENSEX has over the years become one of the most prominent brands in the country.

37

CHAPTER 4

RESEARCH METHODOLOGY

38

Unit Root Test and Co integration:

Empirical studies (for example, Engle and Granger, 1987) have shown that many time

series variables are non-stationary or not integrated of order zero. The time series

variables considered in this paper are the stock prices and fii flows. In order to avoid a

spurious regression situation the variables in a regression model must be stationary or

cointegrated. Therefore, in the first step, we perform unit root tests to investigate whether

they are stationary or not.

The Augmented Dickey-Fuller (ADF) unit root test is used for this purpose. The

ADF regression equations are:

where åô is white noise. The additional lagged terms are included to ensure that the

errors are uncorrelated.

39

ADF UNIT ROOTS TEST

The tests are based on the

null hypothesis (H0): Yt is not I (0). If the calculated ADF statistics are less than their

critical values from Fuller�s table then the null hypothesis (H0) is rejected and the series

are stationary or not integrated of order zero.

COINTEGRATION

In the second step we estimate cointegration regression using variables having the same

order of integration. The cointegration equation estimated by the OLS method is

given as:

In the third step residuals (Zt) from the cointegration regression are subject to the

stationarity test based on the following equations:

40

Toda and Yamamoto Version of Granger Causality:

Toda and Yamamoto (1995) proposed a simple procedure requiring the estimation of an

�augmented� VAR, even when there is cointegration, which guarantees the asymptotic

distribution of the statistic. Therefore, the Toda-Yamamoto causality procedure has been

labelled as the long-run causality tests. All one needs to do is to determine the maximal

order of integration dmax, which we expect to occur in the model and construct a VAR in

their levels with a total of (k + dmax) lags. Toda and Yamamoto point out that, for d=1,

the lag selection procedure is always valid, at least asymptotically, since k 1 . =d. If d=2,

then the procedure is valid unless k=1. Moreover, according to Toda and Yamamoto, the

statistic is valid regardless whether a series is I (0), I (1) or I (2), non-cointegrated or

cointegrated of an arbitrary order.

In order to clarify the principle, let us consider the simple example of a bivariate model,

with one lag (k=1). That is,

41

The statistic will be asymptotically distributed as a Chi Square, with degrees of freedom

equal to the number of "zero restrictions", irrespective of whether x1t and x2t are I (0), I

(1) or I (2), non-cointegrated or cointegrated of an arbitrary order. In this study, we used

monthly data series for three variables for the period January 1993 to March 2005

forming around 147 observations. The monthly return on stock prices (RBSE) is

calculated by taking a percentage change in the BSE Sensitive Index (base: 1978-

79=100).

42

GRANGER CAUSALITY TEST Granger causality is a technique for determining whether one time series is useful in

forecasting another. Ordinarily, regressions reflect "mere" correlations.

A time series X is said to Granger-cause Y if it can be shown, usually through a series of

F-tests on lagged values of X (and with lagged values of Y also known), that those X

values provide statistically significant information on future values of Y.

The test works by first doing a regression of ÄY on lagged values of ÄY. Once the

appropriate lag interval for Y is proved significant (t-stat or p-value), subsequent

regressions for lagged levels of ÄX are performed and added to the regression provided

that they 1) are significant in of themselves and 2) add explanatory power to the model.

This can be repeated for multiple ÄX's (with each ÄX being tested independently of other

ÄX's, but in conjunction with the proven lag level of ÄY). More than 1 lag level of a

variable can be included in the final regression model, provided it is statistically

significant and provides explanatory power.

43

CHAPTER 5

ANALYSIS & FINDINGS

44

EMPIRICAL RESULTS:

AUGMENTED DICKEY FULLER TEST:

THE FOLLOWING TESTS ARE CONDUCTED TO TEST THE

STATIONARITY OF THE RETURNS OF THE SENSEX.

The augmented dickey fuller test for the time series values of trading volumes of sensex.

To check the values are stationary we conduct the unit root test and thus the result

indicates the following information

ADF Test Statistic -12.86430 1% Critical Value* -2.5739

5% Critical Value -1.9409

10% Critical Value -1.6163

*MacKinnon critical values for rejection of hypothesis of a unit root.

Augmented Dickey-Fuller Test Equation

Dependent Variable: D(SENSEX)

Method: Least Squares

Date: 06/12/06 Time: 17:47

Sample(adjusted): 2 248

Included observations: 247 after adjusting endpoints

Variable Coefficient Std. Error t-Statistic Prob.

SENSEX(-1) -0.806367 0.062682 -12.86430 0.0000

R-squared 0.402169 Mean dependent var 3.11E-05

Adjusted R-squared 0.402169 S.D. dependent var 0.011877

S.E. of regression 0.009184 Akaike info criterion -6.538776

Sum squared resid 0.020747 Schwarz criterion -6.524568

Log likelihood 808.5388 Durbin-Watson stat 1.999033

45

Here the null hypothesis is rejected since the t-statistics value is -12.86, which is less than

the critical values hence at 5% and 1% significance level.

Thus we can conclude that, the values are stationary and the trend is deterministic.

-0.03

-0.02

-0.01

0.00

0.01

0.02

0.03

50 100 150 200

SENSEX

46

TEST FOR THE STATIONARITY OF THE GOLD

THE FOLLOWING TESTS ARE CONDUCTED TO TEST THE

STATIONARITY OF THE GOLD PRICES.

The augmented dickey fuller test for the time series values of gold prices. To check the

values are stationary we conduct the unit root test and thus the result indicates the

following information

ADF Test Statistic -14.45353 1% Critical Value* -2.5706

5% Critical Value -1.9403

10% Critical Value -1.6160

*MacKinnon critical values for rejection of hypothesis of a unit root.

Augmented Dickey-Fuller Test Equation

Dependent Variable: D(GOLD)

Method: Least Squares

Date: 06/12/06 Time: 17:50

Sample(adjusted): 3 412

Included observations: 410 after adjusting endpoints

Variable Coefficient Std. Error t-Statistic Prob.

GOLD(-1) -1.016117 0.070302 -14.45353 0.0000

D(GOLD(-1)) 0.001759 0.049354 0.035646 0.9716

R-squared 0.508725 Mean dependent var 1.09E-05

Adjusted R-squared 0.507521 S.D. dependent var 0.003987

S.E. of regression 0.002798 Akaike info criterion -8.914947

Sum squared resid 0.003194 Schwarz criterion -8.895356

Log likelihood 1829.564 Durbin-Watson stat 1.998592

47

Here the null hypothesis is rejected since the t-statistics value is -14.453, which is less

than the critical values hence at 5% and 1% significance level.

Thus we can conclude that, the values are stationary and the trend is deterministic

-0.020

-0.015

-0.010

-0.005

0.000

0.005

0.010

0.015

50 100 150 200 250 300 350 400

GOLD

48

JOHANSEN COINTEGRATION TEST

The cointegration test, suggests the likelihood of the existence of the other model due to

the initial model.

Thus calculating the likelihood ratio will show the probability of the regression of other

equation with initial equation.

Date: 06/12/06 Time: 17:54 Sample: 1 414 Included observations: 247

Test assumption: Linear deterministic

trend in the data

Series: GOLD SENSEX Lags interval: No lags

Likelihood 5 Percent 1 Percent Hypothesized Eigenvalue Ratio Critical Value Critical Value No. of CE(s)

0.534427 320.3265 15.41 20.04 None ** 0.412795 131.4982 3.76 6.65 At most 1 **

*(**) denotes rejection of the hypothesis at

5%(1%) significance level

L.R. test indicates 2 cointegrating

equation(s) at 5% significance level

Unnormalized Cointegrating Coefficients:

GOLD SENSEX 20.78813 -0.931143 2.201458 6.838642

Normalized

Cointegrating Coefficients: 1 Cointegrating Equation(s)

GOLD SENSEX C 1.000000 -0.044792 8.52E-05

(0.01982)

Log likelihood 1827.365

49

Here, the likelihood ratio is 320.326 which is greater than critical values at 5 %

significance value. Hence by looking at the table we can say that rejection of the

hypothesis at 5%(1%) significance level.

-0.03

-0.02

-0.01

0.00

0.01

0.02

0.03

50 100 150 200

GOLD SENSEX

50

GRANGER CAUSALITY TEST

FROM THE TABLE BELOW, WE INTERPRETE THE FOLLOWING , FINDINGS

AND CONCLUSIONS

Pairwise Granger Causality Tests

Date: 06/12/06 Time: 17:57

Sample: 1 414

Lags: 2

Null Hypothesis: Obs F-Statistic Probability

SENSEX does not Granger Cause GOLD 246 1.04892 0.35191

GOLD does not Granger Cause SENSEX 1.56900 0.21037

51

HYPOTHESIS:

We took the null hypothesis , that sensex doesn�t granger cause gold and vice versa,

In case 1:

Sensex on granger cause to gold

Here,

f-statistic value is 1.04892 which is less than the critical value of 1.7 and 1.58 at 5 %

and 1 % significance level respectively.

Thus we reject the null hypothesis and can say sensex causes the gold

On the other hand analyzing the impact of gold on sensex for monthly basis we see that

F-statistic value is 1.56900 which is less than the critical value of 1.7 and 1.58 at 5 %

and 1 % significance level respectively.

Thus we again reject the null hypothesis and can say gold has cause on sensex returns.

Now following is the finding for grangers causality test.:

There is no relation between gold and sensex returns.

52

CHAPTER 6

CONCLUSION

53

Conclusion

The causal relationship was tested between the BSE index and gold . Gold price is

included in the model as an additional variable, to examine whether gold price contain

any additional significant information about price movements. Since gold is an important

saving instrument in India and is very often used as a hedge against inflation, it is

expected that gold may be looked upon as alternative asset for those holding idle money,

for speculative purposes.

After looking at the following testing , we found the times series for the year 2005 for

gold prices and stock returns, which shows both the trends are deterministic, and the

values are stationary, these trends were tested for cointigration, and were found that the

multicollinearity exits as the likelihood ratio was high .

The causality test proved that null hypothesis exits and thus proved there is no relation

between the gold prices and stock returns. Even though gold is considered to be the best

alternative source of investment. We find investors tendency to switch to gold investment

when they find the market to be too risky.

54

BIBLOGRAPHY: Bhattacharya, B.B. and Chakravarty, S. (1994). Share price behaviour in India: An

Econometric Analysis, paper presented in Econometric Conference, Pune, 1994.

Bhattacharya,B.B. and Chakravarty,S.(2002).Stock Volatility in India. Institute of

Economic Growth Discussion paper series.55/2002

Bhattacharya B and Mukherjee J(2002) Causal relationship between stock market and

exchange rate,foreign exchange reserves and value of trade balance :A case study for

India .www.igidr.ac.in

Bhattacharya B and Mukherjee J(2001) The nature of the causal relationship between

stock market and macroeconomic aggregates in India: An empirical analysis .

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