Investment decisions and passive portfolio construction utilizing patent analytics: A multi-case study on COVID-19 treatment technologies

Abstract

The question of which stocks to buy remains at the heart of every investment decision. New, non-priced information sources and rationales linking such information to financial theory are constantly investigated. Patent metrics are often relied upon to capture technological change. Prior research detected positive corporate performance implications when relating corporate patent metrics to corporate financial performance indicators like stock prices. However, largely anecdotal evidence from the corporate sector on building investment strategies based on such patent metrics exists. In this multi-case study comprising COVID-19 treatment technologies, we select investment targets from a pool of companies previously identified based on patent analytics via patent portfolio sizes, average patent qualities, and patent portfolio strengths. Casting our thematic investment choice into passively constructed portfolios and benchmarking the portfolios' performance against the sector and three established global benchmarks, we find that relying on patent information in the selection process results in substantial outperformance compared to these global benchmarks. This finding holds true in the short- and mid-term. These findings provide ample opportunities for future research and may guide investment, managerial, and policy decision-makers in crafting promising investment strategies.