PurposeBy examining the impact of product innovation on abnormal financial returns following the launch of new products, this study aims to test the explanatory power of a new compound measure of product innovativeness (Ganbaatar and Douglas, 2019).Design/methodology/approachIt is a longitudinal study in which the authors used the compound product innovativeness score (CPIS) for the first time to measure product innovativeness. The abnormal financial returns are estimated through the event study design, where four different models are used. Artificial neural network analysis is done to determine the impact of the CPIS on abnormal returns by utilising a hexic polynomial regression model.FindingsThe authors find effect sizes that substantially exceed practically significant levels and that the CPIS explain 65% of the variance in the firm’s abnormal returns in market valuation. Moreover, new-to-the-market novelty predicts 83% of the variation, while new-to-the-firm (catch-up) innovation insignificantly impacts firm value.Research limitations/implicationsThis paper demonstrates how the CPIS, an objective and direct measure of product innovativeness, can be used to gain more insight into the innovation effect.Practical implicationsImplications for the business practice of this study include the necessity of relentless innovation by firms in contested differentiated markets, particularly where technological advance is ongoing. Larger and mature firms must practice corporate entrepreneurship to renew their products on a continuous basis to avoid slipping backwards in their markets. Innovation leadership, rather than following the leader, is also important to increase competitive advantage, given the result that innovation followship does not produce abnormal financial returns.Originality/valueIn this study, the authors focused on the effect of product innovativeness on firm performance. While the literature affirms a positive relationship between innovation and firm performance, the effect size of this relationship varies, due largely to the authors contend to simplistic measures of innovativeness. In this study, the authors adopt the relatively novel “compound” measure of product innovativeness (Ganbaatar and Douglas, 2019) to better encapsulate the nuances of both technical novelty and market novelty. This measure of product innovativeness is applicable to firms of all sizes but is more easily applied to entrepreneurial new ventures and SMEs, and it avoids the shortcomings of prior firm-level and subjective measures of innovativeness for both smaller and larger firms. Using a more effective analytical method (Artificial Neural Network), the authors investigated whether there is a “practically” significant effect size due to product innovation, which could be valuable for entrepreneurs in practice. The authors show that the CPIS measure can very effectively explain abnormalities in the stock market, exhibiting a moderate effect size and explaining 65% of the variation in abnormal returns.