Purpose : This study assessed the feasibility of utilizing fundamental analysis to predict foreign exchange rates, focusing on the Nominal Effective Exchange Rate (NEER) of INR and its relationship with various macroeconomic variables in India.

Design/Methodology/Approach : The research employed secondary data, examining quarterly and annual data spanning fiscal years 2011–2012 to 2020–2021. Analytical tools such as covariance, correlation, unit root tests, and Granger causality tests were applied to assess the impact of selected macroeconomic factors on NEER.

Findings : Covariance and correlation analyses revealed a limited association between NEER and the sampled macroeconomic factors. Granger causality experiments, notably, disproved the traditional wisdom regarding the predictive potential of macroeconomic factors by showing that none of them significantly affected NEER swings.

Practical Implications : For professionals in the sector, especially managers and marketers involved in the Indian currency market, this study has significant ramifications. The most important realization was a cautionary tale against placing undue reliance on conventional fundamental analysis to forecast exchange rates. The results highlighted the need for a more dynamic and flexible strategy that takes into account real-time data and acknowledges the limitations of traditional analysis.

Originality/Value : This study, which breaks with earlier studies, was the first to assess how well conventional fundamental analysis worked for predicting changes in foreign currency. The study offered a novel viewpoint on the subject by questioning the perceived forecasting ability of traditional indicators, which prompted a reassessment of the tactics used by market players in the Indian currency market.

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