Modeling and forecasting stock market volatility has been the subject of interest around
the world. Vast empirical and theoretical investigations have been undertaken by academicians
as well as practitioners in finance. In finance literature different approaches have been used
to measure volatility. One of the simplest models of volatility is the historical estimate,
which involves calculating standard deviation or variance of asset returns. It is used as the
elementary measure of risk of financial assets. The second class of model is implied volatility
models. Implied volatility is the market's forecast of the volatility of the underlying asset returns over
the lifetime of the option. The third class of model is ARCH/GARCH class of models, which are
most extensively used in the finance literature. The justification for the use of this type of
models comes from certain features of financial asset returns viz., volatility clustering and
time-varying conditional variance. The classical linear regression model assumes that the variance of
the errors remains constant, but this is unlikely in the context of financial time series. So it
becomes necessary to overcome these limitations, and the volatility models like ARCH/GARCH
models are better suited for estimating volatility of the financial time series than the historical
volatility models.
Several studies have investigated volatility patterns in developed and emerging
markets from various dimensions. Difference in the volatility pattern among developed and
emerging markets, time-varying relationship between volatility and other variables, impact of
structural changes on volatility, and international transmission of volatility are some of vastly
investigated areas. The transmission of information across international equity markets has been the
subject of interest over the past decade or so, mainly due to the increased integration of
markets around the world. The studies have investigated the dynamic relations of returns and
volatility across markets. In the theoretical literature, we find two broad categories of explanations
for comovement in stock market returns. First, the aggregate shocks in one country could
affect the fundamentals of stock prices in more than one country. These are the shocks which
are basically related to the information regarding the fundamentals, which affects the stock
prices. Second explanation is contagion, which is not explained by fundamentals. |
