Comparative Analysis of Differences of American Pharmaceutical Stocks Before and After the Epidemic
Shicheng Zhao ()
Additional contact information
Shicheng Zhao: Jinan University, College of Information Science and Technology
A chapter in Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022), 2022, pp 238-244 from Springer
Abstract:
Abstract This research adopts the data of American medical stocks in the recent ten years from Yahoo Finance and compares and analyzes the data before and after the epidemic. Try to analyze whether the epidemic has had a great impact on the stock price trend of American medical stocks. The machine learning models predict the amount of price-rising days of stock in the epidemic stage, compared with the price trend before the epidemic. Judging whether the epidemic has significantly reduced the price-rising days of medicine stocks in the United States. By regressing the data of the price movement, we can judge whether the epidemic has had a great impact on the stock price trend. And try to pay attention to whether there is a significant gap between the stock prices of vaccine-producing companies and non-vaccine-producing companies under the influence of the epidemic.
Keywords: Machine learning; Stock price; Epidemic impact; Feature classification (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6463-036-7_35
Ordering information: This item can be ordered from
http://www.springer.com/9789464630367
DOI: 10.2991/978-94-6463-036-7_35
Access Statistics for this chapter
More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().