• Title/Summary/Keyword: 제약 및 바이오.헬스케어 기업

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The Information Effect of FDA Approval Announcements on Pharmaceutical and Bio-Health Companies' Stock Prices (FDA 승인 공시가 제약 및 바이오·헬스케어 기업의 주가에 미치는 정보효과)

  • Yu Jeong Song;Sang-Gun Lee;So Ra Park
    • Information Systems Review
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    • v.26 no.1
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    • pp.289-313
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    • 2024
  • Korean pharmaceutical and bio-health companies began applying for FDA approval in 2000. However, drug companies in South Korea are not required to obtain FDA approval to market their products on the South Korean market, and the approval process is highly resource-intensive. This study utilizes event study methodology to examine the information effect of US FDA approval announcements on the stock prices of pharmaceutical and bio-health companies listed on South Korean stock markets. The study's results show that FDA approval announcements caused abnormal increases in corporate stock prices, indicating that these announcements have a transnational information effect on South Korean companies' value. Furthermore, the results show that the impact of FDA approval announcements on stock prices is greater for small companies than mid-sized and large companies and in bio and healthcare industries than in the traditional pharmaceutical industry. This impact is also more significant on the KOSDAQ (Korea Securities Dealers Automated Quotation) companies than the KOSPI (Korean Composite Stock Price Index) companies and after the expansion of stock price limits. These findings signal that the information effect is more significant when regulatory controls are weaker. The results also indicate that obtaining FDA approval brings above-normal returns for companies and that FDA application is a high-risk, high-return investment.

Big Data News Analysis in Healthcare Using Topic Modeling and Time Series Regression Analysis (토픽모델링과 시계열 회귀분석을 활용한 헬스케어 분야의 뉴스 빅데이터 분석 연구)

  • Eun-Jung Kim;Suk-Gwon Chang;Sang-Yong Tom Lee
    • Information Systems Review
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    • v.25 no.3
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    • pp.163-177
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    • 2023
  • This research aims to identify key initiatives and a policy approach to support the industrialization of the sector. The research collected a total of 91,873 news data points relating to healthcare between 2013 to 2022. A total of 20 topics were derived through topic modeling analysis, and as a result of time series regression analysis, 4 hot topics (Healthcare, Biopharmaceuticals, Corporate outlook·Sales, Government·Policy), 3 cold topics (Smart devices, Stocks·Investment, Urban development·Construction) derived a significant topic. The research findings will serve as an important data source for government institutions that are engaged in the formulation and implementation of Korea's policies.