Analyzing The Outperforming Sector In Volatile Market

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PREFACE
The bookish knowledge of any program, which we get from educational institutions,
is not enough to be used in our day-to-day life. The more practical knowledge we
have, the more beneficial it is for our learning.
To make the students aware of the working of the business world every student of
MASTER OF BUSINESS ADMINISTRATION (4th
SEM) has to undergo a major
research project where he/she experiences many aspects of business under the
supervision of Professional Managers.
I strongly believe that the knowledge gained from this experience is more than the
knowledge gained from the theories in the book.
PLACE: Student Name:
INDORE PAWEL KUMAR GAUTAM
DATE: MBA (F.A) IV Sem

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CERTIFICATE
This is to certify that project on “ANALYZING THE OUTPERFORMING
SECTOR IN VOLATILE MARKET” is the benefited work carried out by PAWEL
KUMAR GAUTAM student of SHRI VAISHNAV INSTITUTE OF
MANAGEMENT during the year 2015 in partial fulfilment of the requirement for the
degree of MBA (Financial Administration).
Signature of the Head of the Dept Internal Guide
Dr. Santosh Dhar, Dr. Sandeep Malu
HOD – MBA, SVIM Indore
External Examiner Internal Examiner

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STUDENT DECLARATION
I PAWEL KUMAR GAUTAM, Student of Shri Vaishnav Institute Of Management,
Indore of MBA (Financial Administration) program has prepared Major research
Project report on “Analyzing The Outperforming Sector In Volatile Market”
The Research as per my knowledge is original and genuine and not published in any
research Journal previously.
Pawel kumar Gautam

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ACKNOWLEDGEMENT
I often wondered why the project reports always began with acknowledgement. Now,
when I have undertaken project myself, did I realize that project report involves not
just the researcher but so many people that help in making the research possible.
Therefore, I take pleasure in beginning the most beautiful part of the report.
I fall short of words to express my gratitude to my guide Dr. Sandeep Malu (internal
guide) and Dr. R.K. Patra (Director SVIM) who despite their busy schedule were
able to find some time to guide me through trouble and solve my problems to the best
of abilities. Without their unfailing guidance, encouragement and patience this project
would not have been possible. It has been a learning experience under him.

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CONTENTS
1 Introduction and History 6
2 Literature Review 21
3 Objective of the study 25
4 Research Methodology 29
5 Analysis and interpretation of results 32
6 Findings 46
7 Suggestions 49
8 Conclusions 53

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Volatility refers to the amount of uncertainty or risk about the size of changes in a
security's value. A higher volatility means that a security's value can potentially be
spread out over a larger range of values. This means that the price of the security can
change dramatically over a short time period in either direction. A lower volatility
means that a security's value does not fluctuate dramatically, but changes in value at a
steady pace over a period of time.
The relative rate at which the price of a security moves up and down. Volatility is
found by calculating the annualized standard deviation of daily change in price. If
the price of a stock moves up and down rapidly over short time periods, it
has high volatility. If the price almost never changes, it has low volatility.
Volatile markets are characterized by wide price fluctuations and heavy trading. They
often result from an imbalance of trade orders in one direction (for example, all buys
and no sells). Some say volatile markets are caused by things like economic releases,
company news, a recommendation from a well-known analyst, a popular initial
public offering (IPO) or unexpected earnings results. Others blame volatility on
day traders, short sellers and institutional investors. One explanation is that
investor reactions are caused by psychological forces. This theory flies in the face
of efficient market hypothesis (EMH), which states that market prices are correct
and adjust to reflect all information. This behavioural approach says that substantial
price changes (volatility) result from a collective change of mind by the investing
public. It's clear there is no consensus on what causes volatility, however, because
volatility exists, investors must develop ways to deal with it.
When the stock market goes up one day, and then goes down for the next five, then up
again, and then down again, that’s what you call stock market volatility.
Some cynics say volatility is a polite way of referring to investors’ nervousness.
Investors may think volatility indicates a problem. But many analysts believe that
increased volatility can indicate a rebound.

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Many investors realize that the stock market is a volatile place to invest their money.
The daily, quarterly and annual moves can be dramatic, but it is this volatility that also
generates the market returns investors experience. In this research we'll explain how
volatility affects investors' returns and how to take advantage of it.
Volatility is a measure of dispersion around the mean or average return of a security.
One way to measure volatility is by using the standard deviation, which tells you how
tightly the price of a stock is grouped around the mean or moving average (MA).
When the prices are tightly bunched together, the standard deviation is small. When
the price is spread apart, you have a relatively large standard deviation.
For securities, the higher the standard deviation, the greater the dispersion
of returns and the higher the risk associated with the investment. As described
by modern portfolio theory (MPT), volatility creates risk that is associated with the
degree of dispersion of returns around the average. In other words, the greater the
chance of a lower-than-expected return, the riskier the investment.
Another way to measure volatility is to take the average range for each period, from
the low price value to the high price value. This range is then expressed as a
percentage of the beginning of the period. Larger movements in price creating a
higher price range result in higher volatility. Lower price ranges result in lower
volatility
J. Welles Wilder is one of the most innovative minds in the field of technical analysis.
In 1978, he introduced the world to the indicators known as true range and average
true range as measures of volatility. Although they are used less frequently than
standard indicators by many technicians, these tools can help a technician enter and
exit trades, and should be looked at by all systems traders as a way to help increase
profitability.

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What Is the Average True Range?
A stock's range is the difference between the high and low price on any given day. It
reveals information about how volatile a stock is. Large ranges indicate high volatility
and small ranges indicate low volatility. The range is measured the same way for
options and commodities - high minus low -as they are for stocks.
Calculating the average true range
The true range was developed by Wilder to address this problem by accounting for the
gap and more accurately measuring the daily volatility than was possible by using the
simple range calculation. True range is the largest value found by solving the
following three equations:
1. TR = H – L
2. TR = H – C.1
3. TR = C.1 – L
Where:
TR represents the true range
H represents today's high
L represents today's low
C.1 represents yesterday's close
If the market has gapped higher, equation No.2 will accurately show the volatility of
the day as measured from the high to the previous close. Subtracting the previous
close from the day's low, as done in equation No.3, will account for days that open
with a gap down.

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Market Performance and Volatility
There is a strong relationship between volatility and market performance. Volatility
tends to decline as the stock market rises and increase as the stock market falls. When
volatility increases, risk increases and returns decrease. Risk is represented by the
dispersion of returns around the mean. The greater the dispersion of returns around the
mean, the larger the drop in the compound return.
Volatility is the most basic statistical risk measure. It can be used to measure the
market risk of a single instrument or an entire portfolio of instruments. While
volatility can be expressed in different ways, statistically, volatility of a random
variable is its standard deviation. In day-to-day practice, volatility is calculated for all
sorts of random financial variables such as stock returns, interest rates, the market
value of a portfolio, etc. Stock return volatility measures the random variability of the
stock returns. Simply put, stock return volatility is the variation of the stock returns in
time. More specifically, it is the standard deviation of daily stock returns around the
mean value and the stock market volatility is the return volatility of the aggregate
market portfolio.
Volatility of stock returns has been mainly studied in the developed economies. After
the seminal work of Engle (1982) on the Autoregressive Conditional
Heteroscedasticity (ARCH) model and its generalized form (GARCH) by Bollerslev
(1986), much of the empirical work has used these models and their extensions (see,
for example, French, Schwert and Stambaugh 1987; Akgiray, 1989; Connolly, 1989;
Ballie and DeGennaro, 1990; Lamoureux and Lastrapes, 1990; Corhay and Tourani,
1994; Geyer, 1994; Nicholls and Tonuri, 1995; Booth, Martikainen and Tse, 1997; de
Lima, 1998; and Sakata and White, 1998).
Financial markets exhibit dramatic movements, and stock prices may appear too
volatile to be justified by changes in fundamentals. Such observable facts have been
under scrutiny over the years and are still being studied vigorously (LeRoy and Porter,
1981; Shiller, 1981; Zhong et al., 2003).

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Volatility as a phenomenon as well as a concept remains central to modern financial
markets and academic research. The link between volatility and risk has been to some
extent elusive, but stock market volatility is not necessarily a bad thing. In fact,
fundamentally justified volatility can form the basis for efficient price discovery. In
this context volatility dependence that implies predictability is welcomed by traders
and medium-term investors. The importance of volatility is widespread in the area of
financial economics. Equilibrium prices, obtained from asset pricing models, are
affected by changes in volatility, investment management lies upon the mean-variance
theory, while derivatives valuation hinges upon reliable volatility forecasts. Portfolio
managers, risk arbitrageurs, and corporate treasurers closely watch volatility trends, as
changes in prices could have a major impact on their investment and risk management
decisions.
Volatility may be defined as the degree to which asset prices tend to fluctuate.
Volatility is the variability or randomness of asset prices. Volatility is often described
as the rate and magnitude of changes in prices and in finance often referred to as risk.
The Nobel laureate Merton Miller writes “by volatility public seems to mean days
when large market movements, particularly down moves, occur. These precipitous
market wide price drops cannot always be traced to a specific news event. Nor should
this lack of smoking gun be seen as in any way anomalous in market for assets like
common stock whose value depends on subjective judgment about cash flow and
resale prices in highly uncertain future.
The public takes a more deterministic view of stock prices; if the market crashes, there
must be a specific reason.”
There are two schools of thought that have divergent views on the reasons of
volatility. The economists in their fundamentalist approach argue that these market
movements can be explained entirely by the information that is provided to the
market. They have tried to put forward theories to explain this phenomenon and more
still have tried to use these theories to predict future changes in prices. They go on to
say that since the efficient market hypothesis holds, the information changes affect the
prices. Market volatility keeps changing as new information flows into the market.

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Others have argued that the volatility has nothing to do with economic or external
factors. It is the investor reactions, due to psychological or social beliefs, which exert
a greater influence on the markets. The Popular Models Theory proposes that people
act inappropriately to information that they receive. Thus, freely available information
is not necessarily already incorporated into a stock market price as the efficient market
hypothesis would have proved.
The issue of changes in volatility of stock returns in emerging markets has received
considerable attention in recent years. The reason for this enormous interest is that
volatility is used as a measure of risk. The market participants also need this measure
for several reasons. It is needed as an input in portfolio management. It is
indispensable in the pricing of options.
Furthermore, in the process of predicting asset return series and forecasting
confidence intervals, the use of volatility measure is crucial. The current chapter
provides an overarching review of the equity market volatility, covering areas that
have caught the attention of researchers and practitioners alike. It aims to enlighten
financiers and anyone interested in equity markets about the theories underlying stock
market volatility, the historical trends and debates in the field, as well as the empirical
findings at the forefront of academic research.
Volatility is a natural consequence of trading, which occurs through the news arrival
and the ensuing response of traders. The chain reaction of market participants will
force equity prices to reach a post information equilibrium level. Revision of
expectations and subsequent actions will be reflected in the liquidity of the particular
market and specifically on the amount of stocks traded. If we place the above process
in a continuous time of revising expectations, and since the underlying prime mover is
common, i.e., flow of information, then it is expected that information, liquidity, and
volatility are related.
Over the recent years, scholars have made noteworthy advances in equity volatility
modelling by taking into account features of returns not previously considered. One of
the assumptions underlying time-series models is that time intervals over which price

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variations are observed are fixed. Price changes and news arrival, however, can take
place in irregular time intervals. Empirical evidence using high-frequency data
indicates that adjusting volume and volatility for the duration between trades provides
time-consistent parameter estimators in microstructure models, while allowing for
proper integration of the information proxied by trade intensity—into the regression
model (Engle and Russell, 1998; Dufour and Engle, 2000; Engle, 2000). Recent
research shows that volatility and volume are persistent and highly auto-correlated,
while shorter time duration between trades implies higher probability of news arrival
and higher volatility (Xuet al., 2006). The findings suggest that there is an inverse
relation between price impact of trades and duration between trades. A similar
relationship is documented for the speed of price adjustment to trade-related
information and the time interval between transactions.
Factor that affect the volatility
Region and country economic factors, such as tax and interest rate policy, contribute
to the directional change of the market and thus volatility. For example, in many
countries, the central bank sets the short-term interest rates for overnight borrowing by
banks. When they change the overnight rate, it can cause stock markets to react,
sometimes,violently.
Changes in inflation trends influence the long-term stock market trends and volatility.
Expanding price-earning ratios (P/E ratio) tend to correspond to economic periods
when inflation is either falling or is low and stable. This is when markets experience
low volatility as they trend higher. On the other hand, periods of falling P/E ratios
tend to relate to rising or higher inflation periods when prices are more unstable. This
tends to cause the stock markets to decline and experience higher volatility.

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Industry and sector factors can also cause increased stock market volatility. For
example, in the oil sector, a major weather storm in an important producing area can
cause prices of oil to jump up. As a result, the price of oil-related stocks will follow
suit. Some benefit from the higher price of oil, others will be hurt. This increased
volatility affects overall markets as well as individual stocks.
The higher level of volatility that comes with bear markets has a direct impact on
portfolios. It also adds to the level of concern and worry on the part of investors as
they watch the value of their portfolios move more violently and decrease in value.
This causes irrational responses which can increase investors' losses. As an investor's
portfolio of stocks declines, it will likely cause them to "rebalance" the weighting
between stocks and bonds by buying more stocks as the price falls. Investors can use
volatility to help them buy lower than they might have otherwise.

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History & Evolution of Stock Exchanges in India
Before research the analyzing outperforming sector in volatile market, let us first
know what are :
a) Stock Markets,
b) Stock exchanges
a) Stock Markets: Stock Market is a market where the trading of company stock,
both listed securities and unlisted takes place. It is different from stock exchange
because it includes all the national stock exchanges of the country. For example, we
use the term, "the stock market was up today" or "the stock market bubble."
b) Stock Exchanges: Stock Exchanges are an organized marketplace, either
corporation or mutual organization, where members of the organization gather to trade
company stocks or other securities. The members may act either as agents for their
customers, or as principals for their own accounts. Stock exchanges also facilitates for
the issue and redemption of securities and other financial instruments including the
payment of income and dividends. The record keeping is central but trade is linked to
such physical place because modern markets are computerized. The trade on an
exchange is only by members and stock broker do have a seat on the exchange.
History of Indian Stock Market:
Indian stock market marks to be one of the oldest stock market in Asia. It dates back
to the close of 18th century when the East India Company used to transact loan
securities. In the 1830s, trading on corporate stocks and shares in Bank and Cotton
presses took place in Bombay. 13 Though the trading was broad but the brokers were
hardly half dozen during 1840 and 1850.
An informal group of 22 stockbrokers began trading under a banyan tree opposite the
Town Hall of Bombay from the mid-1850s, each investing a (then) princely amount of

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Rupee 1. This banyan tree still stands in the Horniman Circle Park, Mumbai. In 1860,
the exchange flourished with 60 brokers. In fact the 'Share Mania' in India began with
the American Civil War broke and the cotton supply from the US to Europe stopped.
Further the brokers increased to 250. The informal group of stockbrokers organized
themselves as the The Native Share and Stockbrokers Association which, in 1875, was
formally organized as the Bombay Stock Exchange (BSE).
BSE was shifted to an old building near the Town Hall. In 1928, the plot of land on
which the BSE building now stands (at the intersection of Dalal Street, Bombay
Samachar Marg and Hammam Street in downtown Mumbai) was acquired, and a
building was constructed and occupied in 1930.
Premchand Roychand was a leading stockbroker of that time, and he assisted in
setting out traditions, conventions, and procedures for the trading of stocks at Bombay
Stock Exchange and they are still being followed.
Several stock broking firms in Mumbai were family run enterprises, and were named
after the heads of the family.
The following is the list of some of the initial members of the exchange, and who are
still running their respective business:
 D.S. Prabhudas & Company (now known as DSP, and a joint venture partner with
Merrill Lynch)
 Jamnadas Morarjee (now known as JM)
 Champaklal Devidas (now called Cifco Finance)
 Brijmohan Laxminarayan
In 1956, the Government of India recognized the Bombay Stock Exchange as the first
stock exchange in the country under the Securities Contracts (Regulation) Act.
The most decisive period in the history of the BSE took place after 1992. In the
aftermath of a major scandal with market manipulation involving a BSE member

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named Harshad Mehta, BSE responded to calls for reform with intransigence. The
foot-dragging by the BSE helped radicalise the position of the government, which
encouraged the creation of the National Stock Exchange (NSE), which created an
electronic marketplace. NSE started trading on 4 November 1994. Within less than a
year, NSE turnover exceeded the BSE. BSE rapidly automated, but it never caught up
with NSE spot market turnover. The second strategic failure at BSE came in the
following two years. NSE embarked on the launch of equity derivatives trading. BSE
responded by political effort, with a friendly SEBI chairman (D. R. Mehta) aimed at
blocking equity derivatives trading. The BSE and D. R. Mehta succeeded in delaying
the onset of equity derivatives trading by roughly five years. But this trading, and the
accompanying shift of the spot market to rolling settlement, did come along in 2000
and 2001 - helped by another major scandal at BSE involving the then President Mr.
Anand Rathi. NSE scored nearly 100% market share in the runaway success of equity
derivatives trading, thus consigning BSE into clearly second place. Today, NSE has
roughly 66% of equity spot turnover and roughly 100% of equity derivatives turnover.
Stock Exchange provides a trading platform, where buyers and sellers can meet to
transact in securities.

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Introduction to NSE:
The National Stock Exchange (NSE) is India's leading stock exchange covering 364
cities and towns across the country. NSE was set up by leading institutions to provide
a modern, fully automated screen-based trading system with national reach. The
Exchange has brought about unparalleled transparency, speed & efficiency, safety and
market integrity. It has set up facilities that serve as a model for the securities industry
in terms of systems, practices and procedures.
NSE has played a catalytic role in reforming the Indian securities market in terms of
microstructure, market practices and trading volumes. The market today uses state-of-
art information technology to provide an efficient and transparent trading, clearing and
settlement mechanism, and has witnessed several innovations in products & services
viz. demutualisation of stock exchange governance, screen based trading, compression
of settlement cycles, dematerialisation and electronic transfer of securities, securities
lending and 19 borrowing, professionalization of trading members, fine-tuned risk
management systems, emergence of clearing corporations to assume counterparty
risks, market of debt and derivative instruments and intensive use of information
technology.
The National Stock Exchange of India Limited has genesis in the report of the High
Powered Study Group on Establishment of New Stock Exchanges, which
recommended promotion of a National Stock Exchange by financial institutions (FIs)
to provide access to investors from all across the country on an equal footing. Based
on the recommendations, NSE was promoted by leading Financial Institutions at the
behest of the Government of India and was incorporated in November 1992 as a tax-
paying company unlike other stock exchanges in the country. On its recognition as a
stock exchange under the Securities Contracts (Regulation) Act, 1956 in April 1993,
NSE commenced operations in the Wholesale Debt Market (WDM) segment in June
1994. The Capital Market (Equities) segment commenced operations in November
1994 and operations in Derivatives segment commenced in June 2000.

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NSE's mission is setting the agenda for change in the securities markets in India.
The NSE was set-up with the following objectives:
 establishing a nation-wide trading facility for equities, debt instruments and
hybrids,
 ensuring equal access to investors all over the country through an appropriate
communication network,
 providing a fair, efficient and transparent securities market to investors using
electronic trading systems,
 enabling shorter settlement cycles and book entry settlements systems, and
 meeting the current international standards of securities markets.
The standards set by NSE in terms of market practices and technologies have become
industry benchmarks and are being emulated by other market participants. NSE is
more than a mere market facilitator. It's that force which is guiding the industry
towards new horizons and greater opportunities.
Till the advent of NSE, an investor wanting to transact in a security not traded on the
nearest exchange had to route orders through a series of correspondent brokers to the
appropriate exchange. This resulted in a great deal of uncertainty and high transaction
costs. One of the objectives of NSE was to provide a nationwide trading facility and to
enable investors spread all over the country to have an equal access to NSE.
NSE has made it possible for an investor to access the same market and order book,
irrespective of location, at the same price and at the same cost. NSE uses sophisticated
telecommunication technology through which members can trade remotely from their
offices located in any part of the country. NSE trading terminals are present in 363
cities and towns all over India.
NSE has been promoted by leading financial institutions, banks, insurance companies
and other financial intermediaries

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NSE is one of the first demutualised stock exchanges in the country, where the
ownership and management of the Exchange is completely divorced from the right to
trade on it. Though the impetus for its establishment came from policy makers in the
country, it has been set up as a public limited company, owned by the leading
institutional investors in the country.
From day one, NSE has adopted the form of a demutualised exchange - the ownership,
management and trading is in the hands of three different sets of people. NSE is
owned by a set of leading financial institutions, banks, insurance companies and other
financial intermediaries and is managed by professionals, who do not directly or
indirectly trade on the Exchange. This has completely eliminated any conflict of
interest and helped NSE in 21 aggressively pursuing policies and practices within a
public interest framework.
The NSE model however, does not preclude, but in fact accommodates involvement,
support and contribution of trading members in a variety of ways. Its Board comprises
of senior executives from promoter institutions, eminent professionals in the fields of
law, economics, accountancy, finance, taxation, etc, public representatives, nominees
of SEBI and one full time executive of the Exchange.
While the Board deals with broad policy issues, decisions relating to market
operations are delegated by the Board to various committees constituted by it. Such
committees include representatives from trading members, professionals, the public
and the management. The day-to-day management of the Exchange is delegated to the
Managing Director who is supported by a team of professional staff.

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The study of financial assets volatility is important to academics, policy makers, and
financial market participants for several reasons. First, prediction of financial market
volatility is important to economic agents because it represents a measure of risk
exposure in their investments.
Sandeep Malu; Uttam Rao Jagtap; Rahul Deo (2012) “Analyzing the
Outperforming Sector in the Volatile Market,” found that the FMCG sector has shown
a positive gain which has outperformed during the volatile market.
In 2011, Crestmont’s research examined the historical relationship between stock
market performance and the volatility of the market. For this analysis, Crestmont used
the average range for each day to measure the volatility of the Standard & Poor's 500
Index (S&P 500) index. His research tells us that higher volatility corresponds to a
higher probability of a declining market. Lower volatility corresponds to a higher
probability of a rising market.
Blitz and Vliet in 2007 presented that portfolios of stocks with the lowest historical
volatility are associated with Sharpe-ratio improvements that are even greater than
those documented by Clarke et al (2006), and have a statistically significant positive
alpha. Blitz et al (2007) found that low volatility stocks have superior risk-adjusted
returns relative to the FTSE World Development Index. They also found that low beta
stocks had higher returns than predicted while the reverse held for high beta stocks.
Kaur in 2002 analysed the extent and pattern of stock return volatility during 1990-
2000 and examined the effect of company size, day-of the- week, and FII investments
on volatility measured as the sample standard deviation.

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Poshakwale and Murinde in 2001and Raju M.T., Ghosh and Anirban in 2004
found in their research that “A volatile stock market is a serious concern for policy
makers because instability of the stock market creates uncertainty and thus adversely
affects growth prospects”. Recent evidence shows that when markets are perceived as
highly volatile, it “may act as a potential barrier to investing”
Reddy in (1997-98) analysed the effects of market microstructure, e.g., establishment
of the National Stock Exchange (NSE) and the introduction of Bombay Stock
Exchange Online Trading (BOLT) system on the stock return volatility measured as
the sample standard deviation of the closing prices.
Roy and Karmakar in 1995 focused on the measurement of the average level of
volatility as the sample standard deviation and examined whether volatility has
increased in the early 1990s.
Goyal in 1995 used conditional volatility estimates as suggested by Schwert (1989)
to study the nature and trend of stock return volatility and the impact of carry forward
system on the level of volatility
Garner in 1990 found that the stock market volatility causes reduction in consumer
spending. Garner found that the stock market crash in 1987 brought about a reduction
in the consumer spending in the U.S.

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Black in 1976 first noted the leverage effect. The changes in stock prices tend to be
negatively correlated with changes in stock volatility. Black (1976) argued that the
changes in stock volatility are too large in response to changes in return direction, to
be explained by the leverage effect alone. The works of Christie (1982) and Schwert
(1989) later supported this conclusion.
Across the world, in different markets there have been many instances of low-
volatility stocks giving higher risk-adjusted returns. Robert Haugen (1967) noted an
abnormality—lower-risk portfolios provided superior returns to the supposedly
efficient market portfolio. Nevertheless, this insight has had limited empirical support
and was not verified until the last decade.
Mandelbrot in 1963 noticed that “large changes in stock prices tend to be followed
by large changes of either sign, whereas small changes tend to be followed by small
changes of either sign”. This implies that volatility of returns changes with time and
that the changes in volatility are non-random.

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The research aims to cover the following objective
1. To study the returns & volatility of the market for the relevant period.
2. To study the sector wise performance for the relevant period.
3. To study the best sector and its returns.

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Hypothesis
H01: There is no significant difference between the returns of the market and the
returns of the various sectors.
H02: There is no significant difference between the returns of various sectors.

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Rational of study
The exploratory research will focus on the investment during the volatile market. It
will also suggest investor that how to invest, where to invest to get maximum profit
and minimize the risk during the volatile market.
Estimation of volatility in the equity market has got important implications for many
issues in economics and finance. High volatility in the stock prices has many adverse
effects in an economy. The investment decisions by investors may undergo changes
due to high volatility, which may lead to a fall in the long-term capital flows from
foreign as well as domestic investors.
The analysis of bear and bull markets allows us to investigate in greater detail and in
an episodic manner, the evolution of stock market instability. In an overall sense,
therefore, the aim of this study is to give economic significance to changes in the
pattern of stock market volatility in India.
The study of volatility becomes more important due to the growing linkages of
national markets in currency, commodity and stock with rest of the world markets and
existence of common players have given volatility a new property- that of its speedy
transmissibility across markets.

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Research methodology is partly descriptive, partly exploratory and partly casual. All
the data collected & incorporated in the study are related to FMCG, Automobile,
Pharmaceutical, Banks etc. Researcher also incorporated monthly opening & closing
value of NSE Nifty of relevant period etc.
Research methodology is a way to systematically solve the research problem. It may
be understand as a science of studying how research is done scientifically. In it we
study the various steps that are generally adopted by researchers in studying his
research problem along with the logic behind them.
The research methodology adopted for carrying out the study is as follows-
Research design:
In this I applied exploratory research and descriptive research.
Descriptive research or statistical research provides data about the NIFTY index.
Descriptive research is used when the objective is to provide a systematic description
that is as factual and accurate as possible. It provides the number of times something
occurs, or frequency, lends itself to statistical calculations such as determining the
average number of occurrences or central tendencies.
One of its major limitations is that it cannot help determine what causes a specific
behaviour, motivation or occurrence. In other words, it cannot establish a causal
research relationship between variables. The two most commonly types of descriptive
research designs are observation.
Sample Design:
The sample used in the project will be exploratory based on the NIFTY index from the
selective indices of the financial year 1 April 2005 to 31 March 2015.

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Tools for Data Collection:
Secondary Data is data collected by someone other than the user. Common sources
of secondary data for social science include censuses, organizational records and data
collected through qualitative methodologies or qualitative research.
Secondary data analysis saves time that would otherwise be spent collecting data and
particularly in the case of qualitative data, provides larger and higher-quality
databases that would be unfeasible for any individual researcher to collect on their
own. In addition, analysts of social and economic change consider secondary data
essential, since it is impossible to conduct a new survey that can adequately capture
past change and/or developments.
 Source- Books, internet website, govt. magazines, newspaper has used as
source of secondary data collection.
Formula used:-
(a). To calculate change = (closing – opening).
(b). To calculate percentage change = (change/opening * 100)

32
5. ANALYSIS AND
INTERPRETATION OF
RESULTS

33
YEAR OPENING CLOSING CHANGE % CHANGE
2005-06 2035.9 3402.55 1366.65 67.12756
2006-07 3403.15 3821.55 418.4 12.294492
2007-08 3820 4734.5 914.5 23.939791
2008-09 4735.65 3020.95 -1714.7 -36.208335
2009-10 3023.85 5249.1 2225.25 73.58996
2010-11 5249.2 5833.75 584.55 11.135983
2011-12 5835 5295.55 -539.45 -9.2450728
2012-13 5296.35 5682.55 386.2 7.2918142
2013-14 5697.35 6704.3 1006.95 17.674006
2014-15 6729.5 8491 1761.5 26.175793
TOTAL 6409.85 193.77599
TABLE 1.1 NIFTY
After the analysis of above table, Researcher found that nifty was 2035.9 in the year of 2005-
06 which is 8491 in the year of 2014-15. It shows that there is a rise 6409.85 points nearly
(193.77%) in the period of the study.
Above table shows the declining trend of nifty in the year
 2008-09 (-36.20%)
 2011-12 (9.25%)
But there was the positive trend in the year
 2005-06 (67.13%),
 2006-07 (12.30%),
 2007-08 (23.94%),
 2009-10 (73.59%),
 2010-11 (11.14%),
 2012-13 (7.29%),
 2013-14 (17.67%),
 2014-15 (26.17%).

34
There was a surprisingly big change has been noted in the year of 2005-06, 2009-10, 2014-15
and which was positive. But in the year of 2008-09, the nifty has shown drastic negative
change.
-60
-40
-20
0
20
40
60
80
1 2 3 4 5 6 7 8 9 10
NIFTY % CHANGE
NIFTY % CHANGE

35
TABLE 1.2 BANK
The opening index for Banking sector in 2005-06 was 3609.11 which is
18206.65 in the year of 2014-15 i.e. the index rise by 14462.9 points nearly
(234.95%).
The table shows that the maximum downfall in the relevant period is in 2008-09
by 2573.5 points and maximum rise is in the year of 2009-10 by 5306.05 points.
-60
-40
-20
0
20
40
60
80
100
120
140
RETURN
NIFTY
BANK
YEAR
OPENING CLOSING CHANGE % CHANGE
2005-06 3609.11 4661.5 1052.39 29.159266
2006-07 4661.5 5308.5 647 13.879652
2007-08 5267.7 6655 1387.3 26.335972
2008-09 6706.7 4133.2 -2573.5 -38.372076
2009-10 4153.55 9459.6 5306.05 127.74735
2010-11 9464.14 11705.45 2241.31 23.682131
2011-12 11713.05 10212.75 -1500.3 -12.80879
2012-13 10186.8 11361.85 1175.05 11.535026
2013-14 11414.95 12742.05 1327.1 11.625982
2014-15 12806.15 18206.65 5400.5 42.171144
TOTAL 14462.9 234.95566

36
2005-06 1099.4 2167.21 1067.81 97.126615
2006-07 2231.79 1970.92 -260.87 -11.688824
2007-08 1849.15 1878.43 29.28 1.5834302
2008-09 1860.57 1341.89 -518.68 -27.877478
2009-10 1346.02 3206.79 1860.77 138.24237
2010-11 3207 3862.41 655.41 20.436857
2011-12 3882.15 4207 324.85 8.3677859
2012-13 4244.5 4224.6 -19.9 -0.468842
2013-14 4215.1 5803.2 1588.1 37.676449
2014-15 5838.55 8621.75 2783.2 47.66937
TOTAL 7509.97 311.06774
TABLE 1.3 AUTO
The opening index for Auto sector in 2005-06 was 1099.4 which is 8621.75 in the year of
2014-15 i.e. the index rise by 7509.97 points nearly (311.067 %).
The table shows that the maximum downfall in the relevant period is in 2008-09 by 518.68
points and maximum rise is in the year of 2009-10 by 1860.77 points.
-60
-40
-20
0
20
40
60
80
100
120
140
160
RETURN
YEAR
NIFTY
AUTO

37
2005-06 3607.61 5397.04 1789.43 49.601537
2006-07 5490.54 5915.4 424.86 7.7380367
2007-08 5683.23 8580.92 2897.69 50.986675
2008-09 8782.5 6500.27 -2282.23 -25.986109
2009-10 6619.24 9020.84 2401.6 36.282111
2010-11 9056.16 9480.65 424.49 4.6873068
2011-12 9474.6 7557.2 -1917.4 -20.237266
2012-13 7563.55 7551.5 -12.05 -0.1593167
2013-14 7593.65 8329.45 735.8 9.6896749
2014-15 8369.75 8264.25 -105.5 -1.2604917
TOTAL 4356.69 111.34216
TABLE 1.4 ENERGY
The opening index for energy sector in 2005-06 was 3607.04 which is 8264.25 in the year of
-60
-40
-20
0
20
40
60
80
RETURN
YEAR
NIFTY
ENERGY

38
TABLE 1.5 FINANCE
The opening index for Finance sector in 2005-06 was 1257.15 which is 7548.65 in the year of
-60
-40
-20
0
20
40
60
80
100
120
140
RETURN
YEAR
NIFTY
FINANCE
2005-06 1257.15 1795.59 538.44 42.830211
2006-07 1816.28 2165.14 348.86 19.207391
2007-08 2032.84 2890.19 857.35 42.174987
2008-09 2862.31 1670.5 -1191.81 -41.638048
2009-10 1718.51 3744.37 2025.86 117.88468
2010-11 3775.36 4629.58 854.22 22.626187
2011-12 4612.49 4143.75 -468.74 -10.162407
2012-13 4135.6 4732.25 596.65 14.427169
2013-14 4750.1 5273.65 523.55 11.021873
2014-15 5293.15 7548.65 2255.5 42.611677
TOTAL 6339.88 260.98372

39
TABLE 1.6 FMCG
The opening index for Fmcg sector in 2005-06 was 2811.75 which is 19879.6 in the year of
-60
-40
-20
0
20
40
60
80
100
120
RETURN
YEAR
NIFTY
FMCG
2005-06 2811.75 5897.48 3085.73 109.74411
2006-07 6036.81 4724.77 -1312.04 -21.733995
2007-08 4572.85 5817.72 1244.87 27.223067
2008-09 5933.72 5134.66 -799.06 -13.466426
2009-10 5117.6 7273.7 2156.1 42.131077
2010-11 7264.26 9188.45 1924.19 26.488452
2011-12 9180.95 11426.05 2245.1 24.453896
2012-13 11430.25 15321.9 3891.65 34.046937
2013-14 15310.3 18085.25 2774.95 18.124726
2014-15 18119.2 19879.6 1760.4 9.7156607
TOTAL 16971.89 256.7275

40
TABLE 1.7 INFORMATION TECHNOLOGY
The opening index for it sector in 2005-06 was 2927.7which is 12083 in the year of 2014-15
i.e. the index rise by 9106 points nearly (236.103%).
-50
0
50
100
150
200
RETURNS
YEARS
NIFTY
IT
2005-06 2927.7 4352.9 1425.2 48.679851
2006-07 4373.1 5180.7 807.6 18.467449
2007-08 5141.15 3704.95 -1436.2 -27.935384
2008-09 3739.8 2318.7 -1421.1 -37.999358
2009-10 2317.35 5855.95 3538.6 152.70028
2010-11 5861.45 7148.1 1286.65 21.951053
2011-12 7136.8 6516 -620.8 -8.6985764
2012-13 6511.85 7219.05 707.2 10.860201
2013-14 7230.65 9298 2067.35 28.591482
2014-15 9331.5 12083 2751.5 29.486149
TOTAL 9106 236.10315

41
TABLE 1.8 MEDIA
The opening index for media sector in 2005-06 was 1000 which is 2188.9 in the year of
2014-15 i.e. the index rise by 1163.67 points nearly (165.95%).
-80
-60
-40
-20
0
20
40
60
80
100
120
140
RETURN
YEARS
NIFTY
MEDIA
2005-06 1000 1337.94 337.94 33.794
2006-07 1379.1 1873.9 494.8 35.878471
2007-08 1798.15 1886.35 88.2 4.9050413
2008-09 1872.16 750.77 -1121.39 -59.898192
2009-10 761.25 1669.96 908.71 119.37077
2010-11 1682.36 1430.18 -252.18 -14.989657
2011-12 1437.46 1232.25 -205.21 -14.275876
2012-13 1239.05 1631.5 392.45 31.67346
2013-14 1647.3 1793.25 145.95 8.8599526
2014-15 1814.5 2188.9 374.4 20.633783
TOTAL 1163.67 165.95175

42
2005-06 1195.63 1690.04 494.41 41.351421
2006-07 1721.5 2190.23 468.73 27.227999
2007-08 2102.85 3701.77 1598.92 76.035856
2008-09 3641.06 1712 -1929.06 -52.980725
2009-10 1719.75 4861.78 3142.03 182.70272
2010-11 4923.17 4293.65 -629.52 -12.786883
2011-12 4339.56 3054.75 -1284.81 -29.606919
2012-13 3047.25 2232.1 -815.15 -26.750349
2013-14 2242.05 2520.65 278.6 12.426128
2014-15 2531.95 2324.45 -207.5 -8.1952645
TOTAL 1116.65 209.42398
TABLE 1.9 METAL
The opening index for metal sector in 2005-06 was 1195.63 which is 2324.45 in the year of
2014-15 i.e. the index rise by 1116.65 points nearly (209.42%).
-100
-50
0
50
100
150
200
RETURN
YEARS
NIFTY
METAL

43
2005-06 1870.24 2765.19 894.95 47.852147
2006-07 2835.1 2720.26 -114.84 -4.0506508
2007-08 2646.25 2928.48 282.23 10.665281
2008-09 2906.34 2200.35 -705.99 -24.291377
2009-10 2176.18 4016.85 1840.67 84.582617
2010-11 4020.44 4335.85 315.41 7.8451612
2011-12 4541.5 5036.6 495.1 10.901684
2012-13 5033.6 5953 919.4 18.265257
2013-14 5976.05 7630.4 1654.35 27.683001
2014-15 7659.8 12844.8 5185 67.691062
TOTAL 10766.28 247.14418
TABLE 1.10 PHARMA
The opening index for pharma sector in 2005-06 was 1870.24 which is 12844.8 in the year of
-60
-40
-20
0
20
40
60
80
100
RETURN
YEARS
NIFTY
PHARMA

44
2005-06 1423.75 1674.9 251.15 17.640035
2006-07 1695.35 1607.76 -87.59 -5.1664848
2007-08 1488.95 2249.1 760.15 51.052755
2008-09 2261.65 1566.09 -695.56 -30.754538
2009-10 1574.48 3312.57 1738.09 110.39137
2010-11 3351.48 4454 1102.52 32.896511
2011-12 4454.9 3385.1 -1069.8 -24.014007
2012-13 3390.5 3048 -342.5 -10.101755
2013-14 3066.35 2738.65 -327.7 -10.686973
2014-15 2757.2 3410.4 653.2 23.690701
TOTAL 1981.96 154.94761
TABLE 1.11 PSU BANK
The opening index for psu bank sector in 2005-06 was 1423.75 which is 3410.4 in the year of
-60
-40
-20
0
20
40
60
80
100
120
RETURN
YEARS
NIFTY
PSU BANK

45
2005-06 --- --- --- ---
2006-07 1000 755.17 -244.83 -24.483
2007-08 717.62 1042.01 324.39 45.20359
2008-09 1030.97 199.97 -831 -80.603703
2009-10 212.23 427.74 215.51 101.54549
2010-11 432.38 313.3 -119.08 -27.540589
2011-12 312.85 239.05 -73.8 -23.58958
2012-13 238.95 223.95 -15 -6.2774639
2013-14 224.45 189.05 -35.4 -15.771887
2014-15 189.55 216.15 26.6 14.033237
TOTAL -752.61 -17.483904
TABLE 1.12 REALITY
The opening index for reality sector in 2006-07 was 1000 which is 216.15 in the year of
2014-15 i.e. the index downfall by 752.61 points nearly (-17.48 %).
The table shows that the maximum downfall in the relevant period is in 2008-09 by 831
-100
-50
0
50
100
150
RETURN
YEARS
Chart Title
NIFTY
REALITY

47
1. After analysis of the table 1.13, researcher have been found that there is significant
differences between return of market and return of various sector but the direction of
return were same (positive) except REALITY. Thus we reject null hypothesis (H01).
2. After the study of tables 1.2 to 1.12 researcher concluded that there is a significant
difference between the returns of various sectors during the relevant period. All the
sectors have given positive return except Reality where Auto sector has shown the
highest positive returns i.e. 311.0677% and Energy sector has given lowest positive
return i.e. 111.3422 % during the relevant period. Thus we reject Null Hypothesis
(H02).
 In the study NIFTY was found to be increased by 193.77% from the financial
year 2005-15, which shows that the investment in the stock market is profitable
in long run.
 The bank sector shows that it was increased by 235%, i.e. investment in bank
sector is profitable.
 The auto sector shows that it was increased by 311.1%, i.e. investment in auto
 The energy sector shows that it was increased by 111.3%, i.e. investment in
energy sector is profitable.
 The finance sector shows that it was increased by 261%, i.e. investment in
finance sector is profitable.
 The FMCG sector shows that it was increased by 257%, i.e. investment in
FMCG sector is profitable.
 The IT sector shows that it was increased by 236%, i.e. investment in IT sector
is profitable.
 The media sector shows that it was increased by 166%, i.e. investment in media

48
 The metal sector shows that it was increased by 209.4%, i.e. investment in
metal sector is profitable.
 The pharma sector shows that it was increased by 247%, i.e. investment in
pharma sector is profitable.
 The PSU bank sector shows that it was increased by 155%, i.e. investment in
PSU bank sector is profitable
 The reality sector shows that it was decreased by -17.48%, i.e. investment in
reality sector is under severe risk, which is overall loss.

50
When market is in volatile condition, retail investor feel hesitation over investing in
stock market, but it is wrong decision not to invest.
Meanwhile investing in volatile market can provide lot of profit if investment is done
with good strategies like investing money in packets.
We know this that investor’s prime motive is to have more and more return by
investing in favourable market. After having intensive and deep study on various
market trend researcher advices to investor is that reality sector had negative return, so
investing in that sector will be suicidal attempt.
FMCG is the best if we talk about the performance because it is consistence.
So investor can attain growth here. Talking about automobile sector definitely it is
providing profit but it is not consistent. New and small investor can’t sustain in
automobile, experienced investor can take risk by investing in automobile.
In overall context FMCG is the best investing destination.
When volatility increases
It is important to understand the difference between volatility and risk. Volatility in
the financial markets is seen as extreme and rapid price swings. Risk is the possibility
of losing some or all of an investment. So as volatility increases, so does profit
potential and the risk of loss, as the market swings from peaks to troughs. There is a
marked increase in the frequency of trades during these periods and a corresponding
decrease in the amount of time that positions are held. During times of increased
volatility, a hyper-sensitivity to news is often reflected in market prices.
The markets don’t always behave the way we’d like them to: Geopolitical turmoil,
natural disasters, interest rates and world events can have a profound effect on market
movements. If market volatility has you concerned about the economy, you are not
alone; this is a confusing time for many investors. Some have decided to stay the
course, while others are sitting on the sidelines waiting for the market to rebound.

51
However, since no one can predict how the markets will perform, it’s important to
develop an investment strategy that can help you stay on the right track to meeting
your long-term financial goals. Here are some strategies that you can implement today
that may help to manage risk during these uncertain times.
1. Work with a Financial Advisor. There are a lot of do-it-yourself investment
resources available to investors today. However, none of those resources can replace
the experienced, personal service a Financial Advisor provides. A Financial Advisor
can offer an understanding of your complete financial picture, not just your
investments. Additionally, in periods of market volatility when you need the most
support, a Financial Advisor can provide:
• Access to important decision-making research and information;
• Periodic review of your investment portfolio, while anticipating your changing
needs; and
• A market-volatility strategy.
2. Have a plan. Developing a financial plan is one of the best ways to help you meet
your long-term goals. Your plan should also include an actionable strategy to address
market volatility, and should be developed well in advance of a turbulent market.
Having a market-volatility strategy will help you to set realistic goals and
appropriately manage your return expectations.
3. Invest regularly. It may not seem intuitive, but investing regularly—even during
market downturns— can help to reduce your overall costs. Dollar cost averaging is
one of the best ways to invest regularly, since you’re investing a fixed amount on a
fixed schedule, regardless of how the markets perform. Investing regularly can also
have intrinsic benefits: It encourages discipline and may also ease the anxiety of daily
market fluctuations.

52
4. Diversify. If you’ve ever heard the saying, “Don’t put all your eggs in one basket,”
then you already have a basic understanding of diversification. Diversifying your
portfolio can reduce risk and volatility if the assets have little or no correlation to each
other.
5. Put volatility to work for you. Do you think of the glass as half empty or half full?
Your perspective can affect the investment decisions you make during market
downturns. Investors who view market volatility negatively can make irrational
decisions. A down market can be an opportunity for you to build your portfolio and
take advantage of lower unit costs.
6. Stay invested. You are probably anxious during times when the value of your
investments has decreased. As a result, you may be tempted to move out of the
market, sit on the sidelines and wait for the market to rebound. However, since no one
knows how the markets will move, how do you know you’re leaving at the right time?
Also, how will you know when it is the right time to get off the sidelines and start
investing again? 6. If you have worked with a Financial Advisor, your investment
strategy was developed to help you meet your long-term goals. Timing the market
could potentially jeopardize your investment strategy—and your future goals.
7. Be patient. There will always be uncertainty in the markets; market volatility is a
natural part of the investment cycle. Although it may take some time, markets
generally do rebound.* In the meantime, call your Financial Advisor to help you
develop an action plan for market volatility and continue to focus on your long-term
investment goals rather than short-term market moves.

54
In the study it is concluded that when market is volatile and flow takes place in
upward direction then it show’s growth of automobile sector. Meanwhile if talk about
downfall trend, then it shows growth of FMCG sector. Performance of reality index
was very poor during research period.
The analysis concluded that investment in stock market is overall profitable but there
are certain risk factors.
NIFTY shows overall profit which makes the investor lured to invest in the market.
Study also reveals that bank, auto, energy, FMCG, finance, IT, media, metal, pharma,
PSU bank, are profitable sectors, which means the investment in these sector is always
safe for long run.
Whereas the reality sector shows overall loss indicating that investment is under
severe risk.

55
REFERENCES
BIBLIOGRAPHY
1 Sandeep Malu; Uttam Rao Jagtap; Rahul Deo (2012) “Analyzing the
Outperforming Sector in the Volatile Market,” International Journal of Research in
Computer Application & Mana;Mar2012, Vol. 2 Issue 3, p60
2 David Blitz, Pim Van Vliet (2007) “The volatility effect: Lower risk without lower
return” Journal of Portfolio Management pages 102-113
3 M. T. Raju, Anirban Ghosh (2004) Stock Market Volatility – An International
Comparison SEBI, working paper series 8
4 Kaur, Harvinder 2004 “Time Varying Volatility in the Indian Stock Market”
Vikalpa: The Journal for Decision Makers;Oct-Dec2004, Vol. 29 Issue 4, p25
5 Kaur, H.2002.Stock Market Volatility in India, New Delhi:Deep and Deep
Publication.
6 Poshakwale and Murinde (2001) „Modelling the volatility in East European
emerging stock markets: evidence on Hungary and Poland‟, Applied Financial
Economics, 11, 445-456.
7 Reddy, Y S (1997-98). “Effects of Microstructure on Stock Market Liquidity
andVolatility,” Prajnan, 26(2), 217- 231
8 Roy, M.K., & Karmakar, M. (1995). Stock market volatility: Roots and results.
Vikalpa, 20(1), 37-48.
9 Goyal, R. (1995). Volatility in stock market returns. Reserve Bank of India
Occasional Papers, 16(3), 175-195.
10 Garner, C. A. (1990) Has the stock market crash reduced consumer spending?,
Financial Market Volatility and the Economy, Federal Reserve Bank of Kansas City.

56
11 Black, F., 1976, “Studies of Stock Market Volatility Changes”, Proceedings of
1976 Meetings of American Statistical Association, Business and Economics
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12 Benoit Mandelbrot, 1963 “The Variation of Certain Speculative Prices” The
Journal of Business, Vol. 36, No. 4 (Oct., 1963), pp. 394-419 Published by: The
University of Chicago Press
13 Pandey, A.2002. Modeling and Forecasting Volatility in Indian Capital Markets,
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www.nseindia.com
14 Fama, E.1965. The Behaviour of Stock Market Prices , Journal of Business, 38.1.,
34-105.
15 Tse, Y.K. .1991. Stock Returns volatility in the Tokyo Stock Exchange , Japan and
The World Economy, 3,258-298.
16 Tse, S. H. and K. S. Tung.1992. Forecasting Volatility in the Singapore Stock
Market , Asia Pacific Journal of Management, 9, 1- 13.
17 Schwert, G.W.1989. Why does Stock Market Volatility Change Over time? ,
Journal of Finance, 54, 1115-1153.
18 Aggarwal, R., C.Inclan and R. Leal (1999) “ Volatility in Emerging Stock
Markets”, Journal of Financial and Quantitative Analysis 34.
19 De Santis, Giorgio and S. Imrohoroglu (1997) “ Stock Returns and Volatility in
Emerging Financial Markets”, Journal of International Money and Finance 16
(August) 561-57
20 Edwards, Sebastian, Javier Gómez Biscarri, Fernando Pérez de Gracia
(2003).“ Stock Market Cycles, Financial Liberalization and Volatility” National
Bureau for Economic Research Working Paper No. 9817.
Security analysis and Portfolio management – Press ICFAI University

57
Investment Management, by V. K. Bhalla, S. Chand 15th Revised Edition 2008
Investment Management, Fisher & Jordan
Security Analysis and Portfolio Management, Avadhani, VII edition
WEBLIOGRAPHY
 www.nseindia.com
 www.investopedia.com
 www.commonwealth.com
 www.en.wikipedia.com
 www.mainstreet.com
 www.investorwords.com
 www.shodhganga.inflibnet.ac.in
 www.dbhowmik.blog.com
 www.sebi.gov.in
 www.morganstanleyfa.com

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