Indian lournal of Commerce & Managemsnt Studies ISSN: 2249-0310 EIS9.
N: 2229-5674
Dor URL: n*r,o* offi i3.I3ffiiffil:f3r'il;
VOLATILITY IN STOCK MARKETS: A COMPARISON OF
DEVBLOPBD AND BMERGING MARKETS OF THE WORLD
SonaliAgarwal,
Ph.D. Research Scholar,
Jamia Hamdard University, India
ABSTRACT
is the growing area of crucial attention which is being analysed by many
academicians over the world. The reason being that with the passage of time, the probability of
deviation of the prices from the initial intrinsic value increases. In this research we have tried to
model the volatility of rwo indices: MSCI emerging markets index and MSCI world index with the use
ofARCH and GARCH models.
The volatility clustering and ARCH ffict were seen and the models were constructed. Both the
ARCH and GARCH terms werefound to be significant in both the market indices.
It was found that in emerging markets, yesterday's volatility had greater influence in explaining
today's volatility while in case of developed markets, both yesterday's volatility and information had
immense influence in explaining today's volatility. The information is of immense use to the finance
professionals and investors and can help them in taking correct portfolio decisions.
Keywords: ARCH, GA;RCH, volatility, developed markets, emerging markets, MSCI index
these historical models deals with the assumption that
Volatility refers to the measure of risk due to the time
the past variance of variables (returns) can be
predicted with considerable accuracy. The most
change in price of any financial inshument. It is usually
popular model which defines volatility is the
measured in terms of annualized returns. Any frnancial
"Random walk model". This model says that the
security whose price follows a random Gaussian
market has no memory and the change in prices of
distribution usually tends to increase as the 'time
shares is independent of previous information. In such
increases, the reason being that with the passage of
a situation the best estimate for today's volatility is the
time, the probability of deviation of the prices from the
realaed value of yesterday's volatility because the
initial intrinsic value increases. We can measure the
information that has got reflected once, remains.
market risk of one security or of the entire portfolio
The next thing of importance in this context is the
with different financial assets. In daily routine,
volatility clustering. It refers to the large change in
volatility can be used to measure the risks associated
prices followed by large change in prices and small
with changing interest rates, exchange rates, stock
change in prices followed by small change in prices in
prices etc, Volatility has been defined as a measure of
either direction for prolonged periods. The existence
variability in prices of stocks by academicians. It is
ofnon constant variances and volatility clustering has
helpful in'prediction of markets and selection of
portfolios by assessment of risk associated. Investors
furally helped' in the estimation of volatility of the
current day with the use of ARCH family modeling.
also define volatility as upswings or downswings or
Here the underlying theory is that, current volatility
rapid price movements within a short time.
can be gauged by seeing the impact of preceding
The degree of unpredictable change in a certain
period's mean and variance.
variable over time is commonly referred to as
Justified volatility can lead to effrcient price discovery
volatility. Stock volatility is time varying and this
which can be helpful to investors due to its certainty
displays pattems rendering the return' distribution
feature. Change is volatility affects equilibrium.prices
abnormal. Many time series models have been
while valuation of derivatives depends upon accuracy
proposed to explain such features. The simplest of
Volume WII Issue 2, May 2017 87 wwt.scholarshub.net
