Abstract
Background
Investments in pharmaceutical companies remain challenging due to the inherent uncertainties of risk assessment.
Objectives
Our paper aims to assess the impact of the drug development setbacks (DDS) on the stock price of pharmaceutical companies while taking into account the company’s financial situation, pipeline size and trend of the stock price before the DDS.
Methods
The model-based clustering based on finite Gaussian mixture modeling was employed to identify the clusters of pharmaceutical companies with homogenous parameters. An artificial neural network was constructed to aid the prediction of the positive mean rate of return 120 days after the DDS.
Results
Our results reveal that a higher pipeline size and a lower rate of return before the DDS, as well as a lower ratio of the market value of the equity and the book value of the total liabilities, are associated with a positive mean rate of return 120 days after the DDS.
Conclusion
In general, the DDS have a negative impact on the company’s stock price, but this risk can be minimized by investors choosing the companies that satisfy certain criteria.
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conceptualization, S.A., L.M., M.V. and E.S.; methodology, S.A., M.V. and A.S.; software, S.A., M.V.; validation, S.A. and A.S.; formal analysis, L.M. and E.S.; investigation, S.S. and A.S.; resources, M.V., S.A.; preparation of paper, M.V., E.S.; paper review and editing, A.S.; visualization, A.S.; supervision, S.A.
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Silvijus Abramavičius and Alina Stundžienė Shared first authorship
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Abramavičius, S., Stundžienė, A., Korsakova, L. et al. Stock price reaction to the drug development setbacks in the pharmaceutical industry. DARU J Pharm Sci 29, 1–11 (2021). https://doi.org/10.1007/s40199-020-00349-6
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DOI: https://doi.org/10.1007/s40199-020-00349-6