Familiarity, Disruptiveness, and Stock returns

Abstract

There is an emerging interest in studying how the stock market responds to firm innovation. Many studies have observed that more radical innovation is underappreciated by the stock market and attribute this to the “categorical imperative” (i.e., innovation that does not fit existing cognitive framework is confusing for the market and therefore undervalued). We propose an alternative “creative destruction” hypothesis: more radical innovation is undervalued because it disrupts existing business model and therefore faces a high level of uncertainty. Using a large dataset of 1 million USPTO utility patents granted between 1980 and 2010, we measure patent stock return using the Kogan et al (2017) measure based on stock price response to the issuing of patents, patent familiarity by how similar the patent text is to prior patents using cleaned patent keywords data developed by Arts et al (2021), and patent disruptiveness by how a patent disrupts the citation network proposed by Funk and Owen-Smith (2017). We found that patents with a higher level of familiarity generate lower stock return, demonstrating the market’s appetite for novelty in contrary to what the categorical imperative predicts. We found that patents with a higher level of disruptiveness generate lower stock returns, supporting the creative destruction hypotheses. More interesting, patent familiarity moderates the effect of patent disruptiveness on stock returns, more specifically, when patent familiarity is high, the negative effect of disruptiveness on stock returns is smaller, indicating that the market in unable to recognize the disruptive nature of patents that are unfamiliar to the market. This supports the categorial imperative hypothesis. These complex patterns advanced our understanding on the relation between innovation and stock returns and contributes to the innovation and finance literatures.