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Guar Gum (GG) is used in Shale oil exploration. Excessive price increase in the Guar futures market had a spillover impact on Guar spot prices and affected Guar export from India as Shale oil producers started exploring alternate sources. In this paper, the role of excessive speculation in the futures market, and its adverse impact on the guar-based agri-business ecosystem have been empirically explored.

Volatility spillover dynamics between WTI crude oil and Guar futures have been explored using bivariate-Granger Causality, BEKK–GARCH models with Wavelet multi-resolution analysis. The wavelet-based models capture the multi-scale features of mean and volatility spillover to identify the effect of heterogenous investment behavior in the time and frequency domain.

The results provide evidence that excessive speculation in futures markets increases spot market volatility. The results also suggest that the excess presence of short-term investors can destabilize the futures market.

The purpose of the commodity futures market is to support price discovery and risk management. However, speculative practices can destabilize these purposes leading to the failure of the business ecosystem.

The novelty of this paper is twofold. First, it explores the economic linkages between the spot and futures market and tests whether the presence of heterogeneous traders affects the economic linkages. Second, it models the impact of short-term speculative investment on the destabilization of the spot market.

The nature of price volume relationship in asset market has been an interesting subject in financial research as it reveals a very important aspect which has implications for market efficiency. The purpose of this paper is to examine price volume relationships in Indian commodity futures market.

There are two competing models in price volume relationship. Mixture of distribution hypothesis, suggesting a positive contemporaneous relationship and sequential information arrival hypothesis (SIH), suggesting a positive intertemporal causal relationship. Both are tested using correlation coefficient and Granger causality test with vector auto regressive methodology.

Though there exists contemporaneous correlation between volume and price change in some of the cases, but in general on the basis of the presence of Granger causality it follows that SIH is supported.

As only three commodities futures have been studied in this paper, this study can be extended to include more number of commodities currently being traded so as to make it more exhaustive.

The research has been done with the data of MCX Gold, MCX Silver and MCX Crude. The results of causality suggest that inefficiency level is maximum in Silver which may be attributed to informational asymmetry.

The Indian commodity futures market is of very recent origin. Hence, very little research work has been undertaken in this space. The paper presents an assessment of the existence of informational asymmetry among the three commodity futures under the study.

The purpose of this paper is to test the long-term effects of price and volume with the help of Downward Sloping Demand Curve (DSDC) hypothesis, and also the short-term price and volume effects with the help of Price Pressure Hypothesis (PPH) for the index revisions on the S&P CNX Nifty 50 index.

In order to report the long-term and short-term effects, the current study reviews two testable hypotheses, namely, DSDC hypothesis and PPH. The study has used the event study approach by including GARCH (1, 1) conditional variance in the market model.

The results report that, the added stocks experienced a significant increase in price and volume on the effective date; whereas the deleted stocks experienced significant volume levels and insignificant price levels on the effective date. Accordingly, the study finds support in favor of PPH.

The study could not find evidence to support the most studied DSDC hypothesis.

Index reorganization presumably affects the fund managers, domestic as well as international investors. As a result, studying the effect of index changes is a subject of attention to academicians and investors alike.

The study contributes to the body of knowledge on index inclusion and exclusion effects by providing Indian evidence on long-term and short-term price and volume effects, and also documenting contrary results to the previous Indian and global research works.

The purpose of this paper is to estimate time‐varying conditional volatility, and examine the extent to which trading volume, as a proxy for information arrival, explain the persistence of futures market volatility using National Stock Exchange S&P CRISIL NSE Index Nifty index futures.

To estimate the volatility and capture the stylized facts of fat‐tail distribution, volatility clustering, leverage effect, and mean‐reversion in futures returns, appropriate ARMA‐generalized autoregressive conditional heteroscedastic (GARCH) and ARMA‐EGARCH models with generalized error distribution have been used. The ARMA‐EGARCH model is augmented by including contemporaneous and lagged trading volume to determine their contribution to time‐varying conditional volatility.

The paper finds evidence of leverage effect, which indicates that negative shocks increase the futures market volatility more than positive shocks of the same magnitude. In addition, the results indicate that inclusion of both contemporaneous and lagged trading volume in the GARCH model reduces the persistence in volatility, but contemporaneous volume provides a greater reduction than lagged volume. Nevertheless, the GARCH effect does not completely vanish.

Research findings have important implications for the traders, regulatory bodies, and practitioners. A positive volume‐price volatility relationship implies that a new futures contract will be successful only to the extent that there is enough price uncertainty associated with the underlying asset. Higher trading volume causes higher volatility; so, it suggests the need for greater regulatory restrictions.

Equity derivatives are relatively new phenomena in Indian capital market. This paper extends and updates the existing empirical research on the relationship between futures price volatility and volume in the emerging Indian capital market using improved methodology and recent data set.