Informational role of futures volume for spot volatility

Purpose The paper aims to explore the informational role of futures volume in the simultaneous relationship between option volume and spot volatility to forecast the volatility of the underlying asset. Design/methodology/approach The generalized method of moments is used to estimate the simultaneous equations of endogeneity between spot volatility and option volume. Futures volume is specified as an exogenous variable in both legs of the estimation of simultaneous equations. However, the future volume is also tested as a dependent variable to prove preference for investment by informed investors in futures along with options. Findings The result indicates that futures volume has a significant association with the bi-directional simultaneous equation estimation between spot volatility and option volume. Moreover, the result of this paper proves that informed investors also prefer futures markets over the spot market. However, there is no change observed in the relationship between option volume and spot volatility due to either call or put options or moneyness. Originality/value The possible role of futures volume in the simultaneous equations between spot volatility and option volume has not yet been researched. This paper pioneers in demonstrating that futures volume is an exogenous variable in the simultaneous equation modeling between spot volatility and option volume. Moreover, in the contemporaneous as well as predictive relationships between spot volatility and option volume, futures volume as an exogenous variable is significant in forecasting spot volatility. In addition to this, the current paper uniquely provides evidence of investment in futures also over the spot market by informed investors.

Fixed‐ k inference for volatility

We present a new theory for the conduct of nonparametric inference about the latent spot volatility of a semimartingale asset price process. In contrast to existing theories based on the asymptotic notion of an increasing number of observations in local estimation blocks, our theory treats the estimation block size k as fixed. While the resulting spot volatility estimator is no longer consistent, the new theory permits the construction of asymptotically valid and easy‐to‐calculate pointwise confidence intervals for the volatility at any given point in time. Extending the theory to a high‐dimensional inference setting with a growing number of estimation blocks further permits the construction of uniform confidence bands for the volatility path. An empirically realistically calibrated simulation study underscores the practical reliability of the new inference procedures. An empirical application based on intraday data for the S&P 500 equity index reveals highly significant abrupt changes, or jumps, in the market volatility at FOMC news announcement times, validating recent uses of various high‐frequency‐based identification schemes in asset pricing finance and monetary economics.

Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models

We consider nonparametric spot volatility estimation for diffusion models with discrete high frequency observations. Our estimator is carried out in two steps. First, using the local average of the range-based variance, we propose a crude estimator of the spot volatility. Second, we use usual nonparametric kernel smoothing to reconstruct the volatility function from the crude estimator. By inference, we find such a double smoothing operation can effectively reduce the estimation error.

Does Ban on Futures trading (de)stabilise spot volatility?

Purpose The purpose of this paper is to ascertain the possible consequences of ban on futures trading of agriculture commodities in India by examining three critical issues: first, the author explores whether price discovery dominance changes between futures and spot in the pre-ban and post-relaunch phase both in the long run and short run. Second, the author examines the impact of ban and relaunch of futures trading on its underlying spot volatility for five sample cases of agriculture commodities (Wheat, Sugar, Soya Refined Oil, Rubber and Chana) using both parametric and non-parametric tests. Third, the author revisits the destabilization hypothesis in the light of ban on futures trading by examining the impact of unexpected component of liquidity of futures on spot volatility. Design/methodology/approach The author uses widely adopted methodology of co-integration to examine long-run relationship between spot and futures, while the short-run relationship is investigated using vector error correction model (VECM) and Granger causality to test price discovery in the pre-ban and post-relaunch phases. The second objective is explored using a combination of parametric and non-parametric tests such as Welch one-way ANOVA and Kruskal–Wallis test, respectively, to gauge the impact of ban on futures trading on spot volatility along with post hoc tests to investigate pairwise comparison of spot volatility among three phases (pre-ban, ban and post-relaunch) using Dunn Test. In addition, extensive robustness test is undertaken by adopting augmented E-GARCH model to ascertain the impact of ban and relaunch of futures trading on spot volatility. The third objective is investigated using Granger causality test between spot volatility and unexpected component of liquidity of futures estimated using Hodrick and Prescott (HP) filter to re-visit the destabilization hypothesis. Findings The author found extensive evidence for the dominance of futures market in the price discovery of agriculture commodities both in the pre-ban and post-relaunch phases in India. The ban on futures trading is found to have a destabilizing impact on spot volatility as evident from the findings of Wheat, Sugar and Rubber. In addition, it is observed that spot volatility was highest during the ban phase as compared to the pre-ban and post-relaunch phases for all four commodities barring Chana. The author found that destabilisation hypothesis holds true during the pre ban phase, while weakening of destabilization hypothesis is observed in the post-relaunch phase as unexpected futures liquidity has no role in driving the spot volatility. Originality/value This study is a novel attempt to empirically examine the potential impact of ban and relaunch of futures trading of agriculture commodities on two key market quality dimensions – price discovery and spot volatility. In addition, destabilization hypothesis is revisited to investigate the impact of futures trading on spot volatility during the pre-ban and post-relaunch period.