Information Transmission Performance of the GIFT Nifty Futures: Evidence from High-Frequency Data

This paper investigates the information transmission performance of GIFT Nifty futures using high-frequency data, a novel area of study given their recent introduction. We employ Johansen cointegration tests, Granger causality tests, GARCH models, Hasbrouck’s Information Share (IS) model, and Gonzalo–Granger’s Component Share (CS) model to assess market integration, volatility, and price discovery dynamics. Our findings reveal significant bidirectional Granger causality and cointegration between the GIFT Nifty futures price and the Nifty index price, indicating a stable long-term equilibrium. Additionally, the GARCH model captures substantial volatility, reflecting the market’s responsiveness to new information. The IS and CS models confirm that the GIFT Nifty futures play a crucial role in the price discovery process, leading the Nifty index. This research is timely, within eight months of the first anniversary of GIFT Nifty futures trading since its launch. The findings highlight the information transmission performance and importance of the GIFT Nifty futures in enhancing market stability and transparency, offering valuable insights into market behaviour, integration, and forecasting abilities.