This study examined the impact of macroeconomic factors on stock prices in the pharmaceutical industry utilizing monthly data for the period January 2015 through December 2025. The autoregressive distributed lag (ARDL) modeling approach and bounds testing were used to evaluate whether or not there is a long-term relationship between macroeconomic variables and stock prices in the pharmaceutical sector, and the evidence found no long-term stable cointegration between macroeconomic variables and stock price movement, thus the focus of this study was on short-run dynamics. Empirical findings of this study document that inflation has a significant effect on stock returns, and the sensitivity of stock returns to inflation is increased by changes in the foreign exchange rate (i.e., a devaluation of the rupee). Furthermore, the interaction of inflation with changes in the foreign exchange rate provides evidence for transmission mechanisms which impact the performance of the pharmaceutical sector at the macroeconomic level. Also, the GARCH (1,1) volatility model indicates a short-lived event driven volatility which exhibits a high level of mean reversion. Results of structural break tests also indicate beginning in 2020 that there are issues with instability resulting primarily from global events (such as the COVID-19 pandemic), however these newly found structural breaks do not alter any of the conclusions drawn from this study’s models. Finally, the findings of this research indicate that the derived models demonstrated strong forecasting capabilities which outperformed the benchmark models employed. In conclusion, this study demonstrates that inflation and the value of the US dollar/euro exchange rate significantly influence the determination of stock returns in the pharmaceutical sector and provide useful insights to investors and policymakers for managing macroeconomic risks.