Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
Series Vol. 62 , 28 December 2023
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Access | Article
Empirical Research on Optimizing Company Investment Strategy Based on Asset Portfolio Strategy -Taking the Pharmaceutical Industry as an Example
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Abstract
In recent years, the pharmaceutical industry has developed rapidly due to the COVID-19. At the same time, with the development of modern asset theory, a variety of asset portfolio strategies can be used by people. In the capital market, the pharmaceutical industry has also become an emerging ideal investment industry, and various related investment portfolio products and trading methods are constantly being updated and improved. This article is based on modern asset portfolio strategies, through relevant worldwide asset allocation models, sharpe theory and CPAM model, and uses the optimal selection of asset portfolios and market portfolios in Markowitz asset portfolio theory to conduct empirical research on the current stock investment portfolio products in the pharmaceutical industry. To test, use Python and Excel to process and analyze two years of stock data and group assets into groups to test the combination to verify the effectiveness of the model for fund investment portfolios in the pharmaceutical industry and better optimize the asset allocation, thereby effectively avoiding risks and increasing returns.
Keywords
modern portfolio theory, Sharpe Ratio, optimize selection, portfolio
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
- ISBN (Print)
- 978-1-83558-225-1
- ISBN (Online)
- 978-1-83558-226-8
- Published Date
- 28 December 2023
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/62/20231336
- Copyright
- 28 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited