Data-Driven Classification of Pharmaceutical and Biotechnology Companies
Name
xu-angelx15-meng-eecs-2024-thesis.pdf
Description
Thesis PDF
Size
550 KB
Format
Adobe PDF
Checksum (MD5)
c511c41cd67cc570f22246423284ddd3
Author(s)
Xu, Angelina
Advisor(s)
Lo, Andrew
Date Issued
May 2024
Publisher
Massachusetts Institute of Technology
Abstract
This study presents a novel approach for classifying biopharmaceutical companies from 2000 to 2023. We use fundamental financial data, 10-K filings, and company drug development data to develop this new classification scheme. Return correlations are used to measure the similarity of companies within a cluster, and our analysis demonstrates that this data-driven improves upon industry standards. Additionally, we evaluate the risk-return characteristics of the clusters developed from this classification scheme as consideration for investment opportunities in these industries.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
In Copyright - Educational Use Permitted
Copyright retained by author(s)
Persistent DSpace Link
