AbstractThis study examines the asymmetric impact on the US S&P 500 stock index due to the changes in aggregate revenue and aggregate earnings of the index constituents. We applied the nonlinear autoregressive distributed lag model of Shin et al. (Festschrift in honor of Peter Schmidt, 2014, Springer, 281–314) to determine the long run and the short run asymmetries. The presence of a cointegrating relationship confirms that despite short‐run departures, the relationship remains stable in the long run. The nonlinear autoregressive distributed lag model estimates that when aggregate revenue increases by $1,000, the S&P index is expected to increase by 8.64 points, but when the aggregate revenue decreases by the same amount, the market decreases by 31.4 points. Similarly, when the aggregate income increases by $1,000, the S&P index is likely to increase by 22.59 points, whereas if the aggregate income decreases by the same amount, the index would decrease more steeply by 32.11 points. Based on these findings, the present study establishes an asymmetric relationship between two important accounting variables. The study also confirms the validation of prospect theory in the S&P index valuation of its constituent stocks' financial performance. Aside from using the model on aggregate data for the S&P index, we also analyzed 28 individual US stocks to validate the findings.