In this paper, we present an entropy-based approach to measure the asymmetry of stock returns. By applying this approach, we use the Bootstrap method that our asymmetry measure exhibits a significantly enhanced ability to detect asymmetry compared to skewness. Moreover, our empirical findings reveal that stocks characterized by higher upside asymmetries, as determined by our innovative entropy measure, exhibit lower average returns across a crosssection of stocks. This supports the conclusions drawn by Han et al. (2018). In contrast, when employing the three-moment skewness measure, the relationship between asymmetry and stock returns remains inconclusive within the Chinese market.