Rajesh Kumar Panda
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Impact of exchange rate fluctuations on Nifty bank and FinServ indices: A financial modelling perspective
Amiya Kumar Mohapatra
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Debasis Mohanty
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Aditya Prasad Sahoo
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Shradha Gupta
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Rajesh Kumar Panda
doi: http://dx.doi.org/10.21511/bbs.21(2).2026.01
Type of the article: Research Article
Abstract
This study examines the impact of exchange rate fluctuations on banking and financial service indices in India. To validate this, five exchange rates are considered based on their relative share in the total foreign remittance inflows to India, viz., Arabian Dirham (AED/INR), Great Britain Pound (GBP/INR), Saudi Riyal (SAR/INR), Singapore Dollar (SGD/INR), and US Dollar (USD/INR). The study includes daily data of a decade (2015–2025), and employs various econometric techniques such as ADF test, Johansen cointegration, Vector Error Correction Model (VECM), and Impulse Response Function (IRF) for the analysis. The Johansen cointegration test indicates a long-run relationship between exchange rates and both the sectoral indices, as the probabilities are less than 0.05. The VECM analysis for both the Nifty Bank and Nifty FinServ identified USD/INR (2,308.66; 2,257.58) and SAR/INR (373.25; 360.73) as the dominant long-term drivers, whereas AED/INR (–2,671.406; –2,608.011) acts as a persistent structural anchor with a negative influence. In the short run, shocks in USD/INR and SGD/INR generate immediate positive effects, whereas volatility in AED/INR and SAR/INR leads to temporary negative deviations before the system converges back to the equilibrium. The impulse response function indicates that exchange rate shocks have temporary effects on both the indices, which dissipate quickly, reflecting rapid market adjustment and overall efficiency. The findings of this study will help policymakers to improve the exchange rate risk monitoring system and executives in banks and financial institutions to formulate their hedging strategies. For investors and portfolio managers, the findings suggest that currency movements can serve as early indicators of market fluctuations, thereby supporting more informed investment decisions.
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