It is generally accepted that the introduction of financial derivatives that facilitate hedging is an important step in the development of stock markets. However, financial derivatives can potentially increase volatility in the underlying cash market, which might be detrimental to the development of the stock market itself. Using data from India, we examine one possible route through which derivatives trading can increase cash market volatility: expiration day effect. Our results indicate that expiration of equity derivatives contracts does not have any effect on the intra-day volatility of the market index, and it reduces the volatility of inter-day returns to the index.
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We thank John Hunter, Kyri Kyriacou and Menelaos Karanasos for useful discussions about expiration day effects, as well as GARCH models and their use in financial economics. We also thank an anonymous referee and editor Josef Brada for their helpful comments. We remain responsible for all remaining errors.
Critics argue that (G)ARCH models are often unreliable because while they have significant in-sample parameter estimates and can capture well inter-temporal persistence of volatility, their performance with respect to out-of-sample predictions are poor. However, Andersen and Bollerslev (1998) have convincingly refuted this argument.
An ‘expiration week’ in our sample corresponds to 5 days of trading ending on an expiration day. Hence, if there are n expiration days in the time period under consideration, the sample for expiration weeks would have 5n observations. Correspondingly, the sample for non-expiration weeks has 4n fewer observations than the sample for non-expiration days.
Jarque-Bera test statistics, not reported in the paper, indicate that the distributions of these growth rates are non-normal for expiration days and weeks, as well as for non-expiration days and weeks, and hence we use the t-test for testing equality of means and variances. The equality of medians was tested using the Wilcoxon rank sum test.
The ADF test statistic was -14.3, thereby rejecting the null hypothesis of unit root at the 1% level.
The Ljung-Box test statistic for our AR(4) model was 24.41, and hence the null hypothesis of no serial correlation could not be rejected. Other specifications for the ARMA(p, q) model, for example, AR(2) and ARMA(2, 2) had larger Ljung-Box statistics that led to the rejection the aforementioned null hypothesis.
The coefficient estimates for this sub-period are not reported in the paper, but can be provided upon request.
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Bhaumik, S., Bose, S. Impact of Derivatives Trading on Emerging Stock Markets: Some Evidence from India. Comp Econ Stud 51, 118–137 (2009). https://doi.org/10.1057/ces.2008.18
- stock market development
- derivatives contracts
- expiration day effect