AAMJAF, Vol. 4, No. 2, 43–65, 2008
ASIAN ACADEMY of
M
ANAGEMENT JOURNAL
of ACCOUNTING
and
FINANCE
THE IMPACT OF DERIVATIVES ON STOCK MARKET
VOLATILITY: A STUDY OF THE NIFTY INDEX
T. Mallikarjunappa
1*
and Afsal E. M.
2
1
Department of Business Administration, Mangalore University, Mangalagangotri –
574199, Mangalore, DK, Karnataka, India
2
School of Management and Business Studies, Mahatma Gandhi University, P.D. Hills,
Kottayam – 686560, Kerala State, India
*Corresponding author: tmmallik@yahoo.com
ABSTRACT
This paper studies the volatility implications of the introduction of derivatives on stock
market volatility in India using the S&P CNX Nifty Index as a benchmark. To account for
non-constant error variance in the return series, a GARCH model is fitted by
incorporating futures and options dummy variables in the conditional variance equation.
We find clustering and persistence of volatility before and after derivatives, while listing
seems to have no stabilisation or destabilisation effects on market volatility. The post-
derivatives period shows that the sensitivity of the index returns to market returns and
any day-of-the-week effects have disappeared. That is, the nature of the volatility patterns
has altered during the post-derivatives period.
Keywords: conditional volatility, heteroscedasticity, volatility clustering, market
efficiency
INTRODUCTION
The modelling of asset returns volatility continues to be one of the key areas of
financial research as it provides substantial information on the risk patterns
involved in investment and transaction processes. A number of works have been
undertaken in this area. Given the fact that stock markets normally exhibit high
levels of price volatility, which lead to unpredictable outcomes, it is important to
examine the dynamics of volatility. With the introduction of derivatives in the
equity markets in the late nineties in the major world markets, the volatility
behaviour of the stock market has become further complicated as derivatives
open new avenues for hedging and speculation. The derivatives market was
launched mainly with the twin objectives to transfer risk and to increase liquidity,
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T. Mallikarjunappa
and Afsal E. M.
thereby ensuring better market efficiency. The examination of how far these
objectives have materialised is important both theoretically and practically.
In India, trading in derivatives started in June 2000 with the launch of
futures contracts in the BSE Sensex and the S&P CNX Nifty Index on the
Bombay Stock Exchange (BSE) and National Stock Exchange (NSE),
respectively. Options trading commenced in June 2001 in the Indian market.
Since then, the futures and options (F&O) segment has been growing
continuously in terms of new products, contracts, traded volume and value. At
present, the NSE has established itself as the market leader in this segment in
India, with more than 99.5 percent market share (NSE Fact Book, 2006, p. 85).
The F&O segment of the NSE outperformed the cash market segment with an
average daily turnover of Rs291.91 billion, as compared to Rs114.79 billion in
the cash segment from 2006 to 2007 (Derivatives Updates on NSE website,
www.nseindia.com, 2007). This shows the importance of derivatives in the
capital market sector of the economy. Previous studies on the volatility effects of
derivatives listing provide mixed results, suggesting case-based biases. In
addition, in India, there is a lack of robust examination of the impact of
derivatives on market volatility. In India, trading in derivatives contracts has
existed for the last six years, which is an adequate time period to evaluate its
major pros and cons. Against this backdrop, it is important to empirically
examine the impact of derivatives on the stock market.
In this paper, we attempt to study the volatility implications of the
introduction of derivatives on the cash market. Through this study, we seek
evidence regarding whether the listing of futures and options lead to any
significant change in the volatility of the cash market in India. In contrast to a
sectoral index studied in previous research from Mallikarjunappa and Afsal
(2007), we select a general index called the S&P CNX Nifty Index to which the
first derivatives contract was introduced by the NSE in India. The previous study
noted the peculiar characteristics of IT stocks and arrived at the conclusion that
stock-specific characteristics must be studied for any general conclusion. As a
benchmark index, the Nifty Index is expected to show wider, more balanced and
more applicable results and thus can be treated as a true replica of the Indian
derivatives market. Most of the Indian studies, such as Thenmozhi (2002), Sibani
and Uma (2007) and Mallikarjunappa and Afsal (2007), did not consider options
contract, but this study examines the introduction of options while also analysing
volatility. The period under analysis spans from October 1995 through June
2006. Furthermore, to allow for a non-constant error variance in the return series,
we applied a GARCH model that was more appropriate to describe the data
collected. Therefore, the present work offers a valuable addition to the existing
literature and should prove to be useful to investors as well as regulators, as this
is a broader index than the one studied by Mallikarjunappa and Afsal (2007).
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The Impact of Derivatives on Stock Market Volatility
The remainder of this paper is organised as follows. Recent literature is briefly
reviewed in Part 2, and Part 3 presents the econometric model, data and
methodology. The empirical results of our work are discussed in Part 4, and
Part 5 presents our conclusion.
RECENT LITERATURE
Various studies on the effects of futures and options listings on the volatility of
an underlying cash market have been carried out across the world. Overall, the
empirical evidence is mixed, and most studies suggest that the introduction of
derivatives does not destabilise the underlying market. These studies also show
that the introduction of derivatives contracts improves liquidity and reduces
informational asymmetries in the market. However, some evidence exists in
support of increased volatility with the onset of derivatives trading. Thus, the
volatility implications of derivatives are still debatable. In this section, we
consider the important and recent literature in this area.
Rahman (2001) examined the impact of index futures trading on the
volatility of component stocks for the Dow Jones Industrial Average (DJIA). The
study used a simple GARCH (1, 1) model to estimate the conditional volatility of
intra-day returns. The empirical results confirm that there is no change in
conditional volatility from pre- to post-futures periods. Figuerola-Ferretti and
Gilbert (2001) used error-correction models and the GARCH (1, 1) regression
model to study the effect of futures trading on volatility. In addition, they
reported the results of a VAR model and presented an impulse response analysis
to track the effects of a shock to each of the volatilities. The results show that
volatility decreases in the post-futures period. Bologna and Cavallo (2002)
examined the effect of the introduction of stock index futures for the Italian
market. Their empirical results show that the introduction of stock index futures
affects the volatility of the spot market. In addition, the results from various
GARCH (1, 1) models for pre-futures and post-futures sub-periods suggest that
the index futures market reduces volatility.
Chiang and Wang (2002) examined the impact of futures trading on
Taiwan spot index volatility. Their study also discussed the macroeconomic and
asymmetric effects of futures trading on spot price volatility behaviour. They
used an asymmetric time-varying GJR volatility model. Their empirical results
showed that the trading of futures on the Taiwan Index has stabilising impacts on
spot price volatility, while the trading of MSCI Taiwan futures has no effects,
except asymmetric response behaviour. Thenmozhi (2002) examined whether
there was any change in the volatility of the S&P CNX Nifty Index in India due
to the introduction of Nifty futures and whether movements in futures prices
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T. Mallikarjunappa
and Afsal E. M.
provided predictive information regarding subsequent movements in index
prices. The study shows that the inception of futures trading has reduced the
volatility of spot index returns.
Pilar and Rafael (2002) analysed the effect of the introduction of
derivatives on the Ibex-35 Index using a dummy variable and a GJR model to test
the impact of the introduction of derivative markets on the conditional volatility
of the underlying asset. They found that although the asymmetry coefficient
increased, the conditional volatility of the underlying index declined after
derivatives were introduced. Robert and Michael (2002) investigated the impact
of the introduction of stock index futures trading on the seasonality of daily
returns of the underlying index for seven national markets. The results indicate
reduced seasonality with respect to mean returns, thus leading to more efficiency
in these markets.
Shembagaraman (2003) explored the impact of the introduction of
derivative trading on cash market volatility using data on stock index futures and
options contracts traded on the Nifty Index. The results suggest that futures and
options trading has not led to a change in the volatility of the underlying stock
index, but the nature of volatility seems to have changed in the post-futures
market. The study also examined whether greater futures trading activity in terms
of volume and open interest was associated with greater spot market volatility. It
found no evidence of any link between trading activity variables in the futures
market and spot market volatility.
Sung, Taek and Park (2004) studied the effect of the introduction of
index futures trading in the Korean markets on spot price volatility and market
efficiency of the underlying KOSPI 200 stocks relative to the carefully matched
non-KOSPI 200 stocks; they found evidence that market volatility was not
affected by futures trading, while market efficiency was improved. Taylor (2004)
tried to uncover the determinants of trading intensity in futures markets. In
particular, the time between adjacent transactions on the FTSE 100 index futures
market was modelled using various augmentations of the basic autoregressive
conditional duration (ACD). As predicted by various market microstructure
theories, he found that the bid-ask spread and transaction volume have a
significant impact on subsequent trading intensity. However, there was evidence
that a large (small) difference between the market price and the theoretical price
of the futures contract, which is known as pricing error, leads to high (low) levels
of trading intensity in the subsequent period.
Boyer and Popiela (2004) looked into whether the introduction of futures
to the S&P500 Index altered the effect of addition to, or removal from, the
S&P500 Index. This study used the S&P500 price effect to show that overall
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The Impact of Derivatives on Stock Market Volatility
price volatility did not show any significant increase for added stocks after
trading began on the S&P500 Index futures.
Calado, Garcia and Pereira (2005) used data for eight derivative products
to study the volatility effect of the initial exchange listing of options and futures
on the Portuguese capital market. They did not find significant differences in the
unadjusted and adjusted variance and beta for the underlying stocks after the
listing of derivatives. However, some of the underlying stocks taken individually
have experienced significant increases or decreases in variance after derivatives
listing. Finally, they concluded that the introduction of a derivatives market in the
Portuguese case has not had the average stabilisation effect on risk as detected in
other markets. Gannon (2005) tested contemporaneous transmission effects
across volatilities of the Hong Kong stock and index futures markets and futures
volume of trade by employing a structural systems approach. Competing
measures of volatility spillover, constructed from the overnight S&P500 Index
futures, were tested and found to impact asset return volatility and volume of
trade patterns in Hong Kong. Antoniou, Koutmos and Pericli (2005) tested the
hypothesis that the introduction of index futures has increased positive feedback
trading on the spot markets of six industrialised nations. Their findings support
the view that futures markets help stabilise underlying spot markets by reducing
the impact of feedback traders and attracting a greater number of rational
investors.
Floros and Vougas (2006) examined the effect of futures trading on the
volatility of the underlying spot market taking the FTSE/ASE-20 and FTSE/ASE
Mid 40 Indices in Greece. The results for the FTSE/ASE-20 Index suggest that
futures trading has led to decreased stock market volatility, but the results for the
FTSE/ASE Mid 40 Index indicate that the introduction of stock index futures has
led to increased volatility, while the estimations of the unconditional variances
indicate a lower market volatility after the introduction of stock index futures.
Sibani and Uma (2007) used OLS and GARCH techniques to capture the
time-varying nature of volatility and volatility clustering phenomenon of the
Nifty Index due to the introduction of futures trading. The results suggest that
there are no significant changes in the volatility of the spot market of the Nifty
Index, but the structure of volatility changes to some extent. The study also
reported that new information is assimilated into prices more rapidly than before,
and there is a decline in the persistence of volatility since the introduction of
futures trading.
Drimbetas, Nikolaos and Porfiris (2007) explored the effects of the
introduction of futures and options into the FTSE/ASE 20 Index on the volatility
of the underlying index using an EGARCH model. It is shown that the
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