Is Innovation Priced? Pharmaceutical Evidence from the Stock Market
DOI:
https://doi.org/10.47611/jsrhs.v13i3.6935Keywords:
pharmaceutical industry, FinCloud, innovation, intervention analysis, forecasting, event studyAbstract
Recent advances in bioinformatic and public health research have been noteworthy specifically in the cross-sectional and longitudinal analyses of microbiome data. We can naturally extend the latest microbiome analytics to the time series dimension of the pharmaceutical industry in the stock market. Following Gu et al. (2022), we introduce FinCloud, a web-based application for the intervention analysis and forecasting of stock prices. The abnormal returns around the U.S. Food and Drug Administration’s drug approvals show that innovation efforts are priced in the firm value of pharmaceutical companies listed on U.S. stock exchanges.
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Kim, J., Jang, H., & Koh, H. (2024). MiMultiCat: A Unified Cloud Platform for the Analysis of Microbiome Data with Multi-Categorical Responses. Bioengineering, 11(1), 60. https://doi.org/10.3390/bioengineering11010060
Koh, H. (2023). Subgroup identification using virtual twins for human microbiome studies. IEEE/ACM Transactions on Computational Biology and Bioinformatics. https://doi.org/10.1109/TCBB.2023.3324139
Jang, H., Park, S., & Koh, H. (2023). Comprehensive microbiome causal mediation analysis using MiMed on user-friendly web interfaces. Biology Methods and Protocols, 8(1), bpad023. https://doi.org/10.1093/biomethods/bpad023
Gu, W., Koh, H., Jang, H., Lee, B., & Kang, B. (2023). MiSurv: an integrative web cloud platform for user-friendly microbiome data analysis with survival responses. Microbiology Spectrum, 11(3), e05059-05022. https://doi.org/10.1128/spectrum.05059-22
Jang, H., Koh, H., Gu, W., & Kang, B. (2022). Integrative web cloud computing and analytics using MiPair for design-based comparative analysis with paired microbiome data. Scientific Reports, 12(1), 20465. https://doi.org/10.1038/s41598-022-25093-6
Gu, W., Moon, J., Chisina, C., Kang, B., Park, T., & Koh, H. (2022). MiCloud: a unified web platform for comprehensive microbiome data analysis. PLoS One, 17(8), e0272354. https://doi.org/10.1371/journal.pone.0272354
Choi, D. M. (2023). MiCloud: A biostatistical platform applied to financial data. International Journal of STEAM, 13(1), 82–86.
Chen, H., Choi, P. M. S., & Hong, Y. (2013). How smooth is price discovery? Evidence from cross-listed stock trading. Journal of International Money and Finance, 32, 668-699. https://doi.org/10.1016/j.jimonfin.2012.06.005
Box, G. E., & Tiao, G. C. (1975). Intervention analysis with applications to economic and environmental problems. Journal of the American Statistical association, 70(349), 70-79. https://doi.org/10.1080/01621459.1975.10480264
Tsay, R. S. (2013). Multivariate time series analysis: with R and financial applications. John Wiley & Sons.
Regenstein Jr, J. K. (2018). Reproducible finance with R: Code flows and shiny apps for portfolio analysis. Chapman and Hall/CRC. https://doi.org/10.1201/9781351052627
Grabowski, H. G., & Vernon, J. M. (1994). Returns to R&D on new drug introductions in the 1980s. Journal of Health Economics, 13(4), 383-406. https://doi.org/10.1016/0167-6296(94)90010-8
Aggarwal, C. C. (2018). Neural networks and deep learning (Vol. 10). Springer. https://doi.org/10.1007/978-3-319-94463-0
Leisch, F., Trapletti, A., & Hornik, K. (1998). Stationarity and stability of autoregressive neural network processes. Advances in Neural Information Processing Systems, 11. https://proceedings.neurips.cc/paper/1998/hash/aa486f25175cbdc3854151288a645c19-Abstract.html
Taskaya-Temizel, T., & Casey, M. C. (2005). A comparative study of autoregressive neural network hybrids. Neural Networks, 18(5-6), 781-789. https://doi.org/10.1016/j.neunet.2005.06.003
Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the national academy of sciences, 79(8), 2554-2558. https://doi.org/10.1073/pnas.79.8.2554
Zell, A. (1994). Simulation of neural networks (1 ed.). Addison-Wesley.
Graves, A., Liwicki, M., Fernández, S., Bertolami, R., Bunke, H., & Schmidhuber, J. (2008). A novel connectionist system for unconstrained handwriting recognition. IEEE transactions on pattern analysis and machine intelligence, 31(5), 855-868. https://doi.org/10.1109/TPAMI.2008.137
Sak, H., Senior, A. W., & Beaufays, F. (2014). Long short-term memory recurrent neural network architectures for large scale acoustic modeling.
Li, X., & Wu, X. (2015). Constructing long short-term memory based deep recurrent neural networks for large vocabulary speech recognition. 2015 ieee international conference on acoustics, speech and signal processing (icassp),
Summers, T. X., Huang, S. H., & Choi, P. M. S. (2021). Can we predict tropical storms? Evidence from artificial intelligence. In Blockchain Technology for IoT Applications (pp. 65-84). Springer. https://doi.org/10.1007/978-981-33-4122-7_4
Sorescu, A. B., Chandy, R. K., & Prabhu, J. C. (2003). Sources and financial consequences of radical innovation: Insights from pharmaceuticals. Journal of Marketing, 67(4), 82-102. https://doi.org/10.1509/jmkg.67.4.82.18687
Wuyts, S., Dutta, S., & Stremersch, S. (2004). Portfolios of interfirm agreements in technology-intensive markets: Consequences for innovation and profitability. Journal of Marketing, 68(2), 88-100. https://doi.org/10.1509/jmkg.68.2.88.27787
FDA. (2010). Drug approvals list. U.S. Food and Drug Administration. http://www.accessdata.fda.gov/scripts/cder/drugsatfda/index.cfm?fuseaction=Reports.NewOriginalNDA
Malerba, F., & Orsenigo, L. (2015). The evolution of the pharmaceutical industry. Business history, 57(5), 664-687. https://doi.org/10.1080/00076791.2014.975119
Goodman, J. (2020). Pharmaceutical industry. In Medicine in the twentieth century (pp. 141-154). Taylor & Francis.
Zeileis, A., Leisch, F., Kleiber, C., & Hornik, K. (2005). Monitoring structural change in dynamic econometric models. Journal of Applied Econometrics, 20(1), 99-121. https://doi.org/10.1002/jae.776
Eddy, A. R., & Saunders, G. B. (1980). New product announcements and stock prices. Decision sciences, 11(1), 90-97. https://doi.org/10.1111/j.1540-5915.1980.tb01127.x
Fama, E. F., Fisher, L., Jensen, M. C., & Roll, R. (1969). The adjustment of stock prices to new information. International economic review, 10(1), 1-21. https://doi.org/10.2307/2525569
Ljung, G. M., & Box, G. E. (1978). On a measure of lack of fit in time series models. Biometrika, 65(2), 297-303. https://doi.org/10.1093/biomet/65.2.297
Klimberg, R. K., Sillup, G. P., Boyle, K. J., & Tavva, V. (2010). Forecasting performance measures–what are their practical meaning? In Advances in business and management forecasting (pp. 137-147). Emerald Group Publishing Limited. https://doi.org/10.1108/S1477-4070(2010)0000007012
Makridakis, S. (1993). Accuracy measures: theoretical and practical concerns. International journal of forecasting, 9(4), 527-529. https://doi.org/10.1016/0169-2070(93)90079-3
John, G., Weiss, A. M., & Dutta, S. (1999). Marketing in technology-intensive markets: Toward a conceptual framework. Journal of Marketing, 63(4_suppl1), 78-91. https://doi.org/10.1177/00222429990634s109
Chandy, R. K., & Tellis, G. J. (2000). The incumbent's curse? Incumbency, size, and radical product innovation. Journal of Marketing, 64(3), 1-17. https://doi.org/10.1509/jmkg.64.3.1.18033
Carpenter, G. S., & Nakamoto, K. (1989). Consumer preference formation and pioneering advantage. Journal of Marketing research, 26(3), 285-298. https://doi.org/10.1177/002224378902600303
Hoch, S. J., & Deighton, J. (1989). Managing what consumers learn from experience. Journal of Marketing, 53(2), 1-20. https://doi.org/10.1177/002224298905300201
Wernerfelt, B. (1985). Brand loyalty and user skills. Journal of Economic Behavior & Organization, 6(4), 381-385. https://doi.org/10.1016/0167-2681(85)90005-8
Sorescu, A. B., Chandy, R. K., & Prabhu, J. C. (2003). Sources and financial consequences of radical innovation: Insights from pharmaceuticals. Journal of Marketing, 67(4), 82-102. https://doi.org/10.1509/jmkg.67.4.82.18687
Golder, P. N., & Tellis, G. J. (1993). Pioneer advantage: Marketing logic or marketing legend? Journal of Marketing research, 30(2), 158-170. https://doi.org/10.1177/002224379303000203
Lieberman, M. B., & Montgomery, D. B. (1998). First‐mover (dis) advantages: retrospective and link with the resource‐based view. Strategic management journal, 19(12), 1111-1125. https://doi.org/10.1002/(SICI)1097-0266(1998120)19:12<1111::AID-SMJ21>3.0.CO;2-W
Sivadas, E., & Dwyer, F. R. (2000). An examination of organizational factors influencing new product success in internal and alliance-based processes. Journal of Marketing, 64(1), 31-49. https://doi.org/10.1509/jmkg.64.1.31.17985
Chaney, P. K., Devinney, T. M., & Winer, R. S. (1991). The impact of new product introductions on the market value of firms. Journal of business, 573-610.
Geroski, P., Machin, S., & Van Reenen, J. (1993). The profitability of innovating firms. The Rand journal of economics, 198-211. https://doi.org/10.2307/2555757
Booz, Allen & Hamilton. (1982). New product development in the 1980s. Booz, Allen & Hamilton.
Binder, J. (1998). The event study methodology since 1969. Review of quantitative Finance and Accounting, 11, 111-137. https://doi.org/10.1023/A:1008295500105
Kothari, S. P., & Warner, J. B. (1997). Measuring long-horizon security price performance. Journal of financial economics, 43(3), 301-339. https://doi.org/10.1016/S0304-405X(96)00899-9
Hendricks, K. B., & Singhal, V. R. (2001). The long-run stock price performance of firms with effective TQM programs. Management science, 47(3), 359-368. https://doi.org/10.1287/mnsc.47.3.359.9773
Aksoy, L., Cooil, B., Groening, C., Keiningham, T. L., & Yalçın, A. (2008). The long-term stock market valuation of customer satisfaction. Journal of Marketing, 72(4), 105-122. https://doi.org/10.1509/jmkg.72.4.105
Jacobson, R., & Mizik, N. (2009). The financial markets and customer satisfaction: Reexamining possible financial market mispricing of customer satisfaction. Marketing Science, 28(5), 810-819. https://doi.org/10.1287/mksc.1090.0495
Barber, B. M., & Lyon, J. D. (1997). Detecting long-run abnormal stock returns: The empirical power and specification of test statistics. Journal of financial economics, 43(3), 341-372. https://doi.org/10.1016/S0304-405X(96)00890-2
Ikenberry, D., Lakonishok, J., & Vermaelen, T. (1995). Market underreaction to open market share repurchases. Journal of financial economics, 39(2-3), 181-208. https://doi.org/10.1016/0304-405X(95)00826-Z
Lyon, J. D., Barber, B. M., & Tsai, C. L. (1999). Improved methods for tests of long‐run abnormal stock returns. The Journal of Finance, 54(1), 165-201. https://doi.org/10.1111/0022-1082.00101
Brav, A., Geczy, C., & Gompers, P. A. (2000). Is the abnormal return following equity issuances anomalous? Journal of financial economics, 56(2), 209-249. https://doi.org/10.1016/S0304-405X(00)00040-4
Lintner, J. (1965). Security prices, risk, and maximal gains from diversification. The Journal of Finance, 20(4), 587-615. https://doi.org/10.2307/2977249
Lintner, J. (1975). The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. In Stochastic optimization models in finance (pp. 131-155). Elsevier. https://doi.org/10.1016/B978-0-12-780850-5.50018-6
Markowitz, H. M. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.2307/2975974
Mossin, J. (1966). Equilibrium in a capital asset market. Econometrica: Journal of the econometric society, 768-783. https://doi.org/10.2307/1910098
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425-442. https://doi.org/10.1111/j.1540-6261.1964.tb02865.x
Treynor, J. L. (1962). Toward a theory of market value of risky assets. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=628187
Sim, J., & Kirk, B. (2023). Generalized deep reinforcement learning for trading. Journal of Student Research, 12(1). https://doi.org/10.47611/jsrhs.v12i1.4316
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