The aim of this research it to analyze the sensitivity of the returns of the top ten European pharmaceutical companies to changes in nine explanatory factors over the sample period from June 2004 to January 2020. Specifically, this research estimates an expansion of Fama and French’s (2015) [1] five-factor model [1], combined with the Stone’s (1974) [2] two-factor model, to which have been added the momentum and momentum reversal risk factors of Carhart (1997) [3] and the traded liquidity factor of Pastor and Stambaugh (2003) [4]. This nine-factor model has been estimated by the quantile regression approach to assess whether economic conditions affect these pharmaceutical companies’ returns. The findings are rigorously tested by splitting the whole sample period into three sub-periods: before, during, and after the crisis. The principal findings reveal that the most significant factors explaining the performance of the largest European pharmaceutical companies are the original three factors of Fama and French’s model, in addition to the investment factor. Moreover, this expanded model exhibits increased explanatory power in both the lower and upper quantiles, displaying a U-shaped pattern across all periods, achieving its peak during the crisis sub-period. This underscores the appropriateness of utilizing the quantile regression approach for model estimation, as it demonstrates greater explanatory power in extreme quantiles associated with the most severe economic conditions. In conclusion, the study highlights the heightened sensitivity of the ten largest European pharmaceutical companies to variations in nine risk factors during extreme economic circumstances in the market.