Purpose : The paper explored the time-varying interconnectedness among the Brent crude oil, Indian Rupee, and Nifty50 using the high-frequency data during the Ukraine crisis.

Methodology : The study applied the Dynamic Johansen Cointegration, Wavelet Coherency, and Markov Regime-Switching GARCH model on high-frequency data from June 2021 to June 2022, to capture the long-run and time-frequency dynamics, and regime-dependent volatility patterns.

Findings : The results of the study indicated the long-term association of oil with the Indian Rupee and Nifty 50, particularly during the Ukraine crisis. Moreover, the wavelet coherency found the co-movement at the lower scales at the time of crisis. The Markov regime found that volatility was higher in the regime of crisis.

Practical Implications : The results have crucial implications for intraday traders, algorithmic investors, and policymakers, as the study established the transmission of shocks from oil markets to financial markets during periods of geopolitical crisis. The knowledge and understanding of such dynamics could be critical in risk management and policy responses.

Originality : The study contributed to the literature by integrating time–frequency analysis and regime-switching volatility modeling with high-frequency financial data to examine the interconnected dynamics of oil prices, exchange rates, and stock markets during a geopolitical crisis.

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