five

Descriptive statistics.

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Descriptive_statistics_/30457161
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资源简介:
This study examines the impact of patent activity on the idiosyncratic volatility (IVOL) of U.S. pharmaceutical companies, addressing a critical gap in the literature on the relationship between innovation and firm-specific risk. Using panel data from Thomson Reuters/Refinitiv covering 2,910 firms over 2005−2024, we employ the Fama-French 5-factor model to isolate firm-specific volatility and analyze how patent events and pharmaceutical development activities affect stock price risk. Our findings reveal a complex relationship between innovation and volatility that varies by development stage. While patent activity overall reduces idiosyncratic volatility, early and mid-stage development projects (Phase I and II) initially increase firm-specific risk, reflecting inherent uncertainties in drug development. Conversely, newly launched products significantly reduce volatility, indicating that risk mitigation occurs primarily at commercialization. These relationships remain robust during crisis periods, including the 2008−09 financial crisis and COVID-19 pandemic. The results provide valuable insights for investors seeking to assess pharmaceutical investment risks, managers optimizing innovation portfolios, and policymakers designing intellectual property frameworks. The study’s focus on the U.S. market and reliance on patent counts rather than quality measures suggest important avenues for future research across different regulatory environments and innovation metrics.
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2025-10-27
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