Purpose: Investors’ short-term fears or expectations are expressed in India through the India Volatility Index, a volatility index based on Nifty call options. The microstructure of the market was largely composed of trading volume, stock index returns, and implied volatility. Understanding the microstructure of the market is crucial because it gives investors important knowledge about its dynamics and empowers them to make wise decisions.

Methodology: For the years 2018 through 2023, the study took into account the closing values of the Nifty, volatility index, and trading volume. To examine the dynamic link between the variables, quantile regression and Granger causality models were applied.

Findings: The findings suggested that the volatility index’s lag returns cause fluctuations in the current returns of the Nifty. The Nifty returns and changes in trading volume are unrelated. It is observed that Nifty returns have an asymmetric relationship with returns from the volatility index and a positive association with trading volume. Markets responded more strongly to negative news shocks when the Nifty had negative returns.Practical

Implications: The volatility index would be used by investors as a hedging tool to forecast near-term Nifty volatility as well as diversify the risk in their portfolio.

Originality: The current work investigated a new temporal regime in light of the pandemic era and is an attempt to understand the dynamics of the market since downturns cause markets to become more volatile.

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