Perspective | Published:

Just how good an investment is the biopharmaceutical sector?

Nature Biotechnology volume 35, pages 11491157 (2017) | Download Citation

Abstract

Uncertainty surrounding the risk and reward of investments in biopharmaceutical companies poses a challenge to those interested in funding such enterprises. Using data on publicly traded stocks, we track the performance of 1,066 biopharmaceutical companies from 1930 to 2015—the most comprehensive financial analysis of this sector to date. Our systematic exploration of methods for distinguishing biotech and pharmaceutical companies yields a dynamic, more accurate classification method. We find that the performance of the biotech sector is highly sensitive to the presence of a few outlier companies, and confirm that nearly all biotech companies are loss-making enterprises, exhibiting high stock volatility. In contrast, since 2000, pharmaceutical companies have become increasingly profitable, with risk-adjusted returns consistently outperforming the market. The performance of all biopharmaceutical companies is subject not only to factors arising from their drug pipelines (idiosyncratic risk), but also from general economic conditions (systematic risk). The risk associated with returns has profound implications both for patterns of investment and for funding innovation in biomedical R&D.

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Acknowledgements

We thank Jayna Cummings for editorial support. Funding support from the MIT Laboratory for Financial Engineering is gratefully acknowledged.

Author information

Affiliations

  1. Carlson School of Management, University of Minnesota, Minneapolis, Minnesota, USA.

    • Richard T Thakor
  2. MIT Sloan School of Management and Laboratory for Financial Engineering, Cambridge, Massachusetts, USA.

    • Nicholas Anaya
    • , Yuwei Zhang
    • , Christian Vilanilam
    • , Kien Wei Siah
    • , Chi Heem Wong
    •  & Andrew W Lo
  3. MIT Department of Electrical Engineering and Computer Science, Cambridge, Massachusetts, USA.

    • Kien Wei Siah
    •  & Andrew W Lo
  4. MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, Massachusetts, USA.

    • Chi Heem Wong
    •  & Andrew W Lo
  5. AlphaSimplex Group, LLC, Cambridge, Massachusetts, USA.

    • Andrew W Lo

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Contributions

A.W.L. first conceived of the idea of analyzing the financial risks and return of the biotech and pharmaceutical industries, proposed the basic design of the empirical and statistical analysis, assembled key members of the project team, provided funding through the MIT Laboratory for Financial Engineering, and was responsible for overall project management, manuscript preparation, and journal submission. Initial data collection, data cleaning, and preliminary analysis of company-specific stock returns were performed by N.A., Y.Z., and C.V., and reviewed by A.W.L. and R.T.T. More comprehensive data collection, data cleaning, financial modeling, and detailed analysis of stock returns and accounting data were performed by R.T.T., who was involved in every aspect of the design of the project and the data analysis, with input from A.W.L. All aspects of the financial modeling and data analysis were reviewed by A.W.L. A.W.L. conceived of using an algorithmic approach to perform industrial classification on a rolling-window basis, and K.W.S. and C.H.W. developed the algorithms for classifying companies into biotech and pharma industries with input from and review by R.T.T. and A.W.L. All authors participated in preparing the first draft of the main manuscript, and A.W.L. reviewed and edited this draft to produce the final version. K.W.S. and C.H.W. prepared the initial draft of Supplementary Methods with input from R.T.T. and A.W.L., and R.T.T. and A.W.L. edited this draft to produce the final version. R.T.T. prepared the initial draft of Supplementary Notes and Supplementary Results with input from A.W.L., and A.W.L. edited this draft to produce the final version.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Andrew W Lo.

Supplementary information

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    Supplementary Text and Figures

    Supplementary Figures 1–3, Supplementary Tables 1–6, Supplementary Methods, Supplementary Notes, and Supplementary Results

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DOI

https://doi.org/10.1038/nbt.4023

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