Volatility Analysis of the Indian Stock Market: Insights from Bank Nifty Index and Futures Trading
Tetiana Paientko
Profil Orcid et Rashmi Ravindra Kumar Pundir
Profil Orcid 
Publié en ligne: 15 mai 2025
Pages: 5 - 41
DOI: https://doi.org/10.2478/joim-2024-0013
Mots clés
© 2024 Tetiana Paientko et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License.
Objective
To diagnose the relationship between futures contract trading and the volatility of stocks in the Bank Nifty Index.
Methodology
Time series analysis and the GARCH model are employed to study the interaction between futures trading and spot market volatility.
Findings
The analysis revealed that out of the six banks analyzed, just two demonstrated a statistically significant influence of future trading on volatility, while the remaining four did not exhibit any such relationship.
Value Added
This study provides a nuanced understanding of the impact of futures trading on stock volatility within the Bank Nifty Index, specifically highlighting variations across banks. By including the COVID -19 period, this research captures the influence of unprecedented market shocks on volatility dynamics in an emerging market context, providing valuable insights into how futures trading operates under unique stress conditions. Moreover, the study fills a gap in the existing literature by including all top -weighted banks in the Bank Nifty, especially those that were previously overlooked, thereby enhancing the relevance of the findings for policymakers and market participants.
Recommendations
Policymakers and regulators should consider adopting tailored guidelines that reflect the different responses of individual banks to futures trading, as one-size-fits-all regulations may overlook stock -specific volatility dynamics. Market participants, especially investors and retail traders, are advised to apply targeted risk management and hedging strategies based on each bank’s unique volatility patterns rather than generalizing across the industry.