Application of Mean-Variance Model in the U.S. Capital Market
- DOI
- 10.2991/978-94-6463-052-7_86How to use a DOI?
- Keywords
- Mean-variance; capital market; FF3F; sharpe ratio
- Abstract
Portfolio optimization is a popular procedure that is widely used in the financial industry. This paper conducts asset allocation analysis for diversified assets, including iron and steel industry, technology, healthcare, information industry and energy areas. There are five assets selected from the different areas which perform well in recent years. This paper uses three methods, namely Mean-variance analysis, CAPM and FF3F model, to find the portfolio optimization. Also, this paper uses the weights to analyse the performance of portfolio in different methods. The result shows that, in the FF3F model, ‘LMBEX’ contains the largest weight in both maximum sharpe ratio portfolio and minimum variance portfolio, while in the CAPM, ‘ADX’ and ‘LMBEX’ account for the largest weight in maximum sharpe ratio portfolio and minimum variance portfolio, respectively. This research may be useful to the potential investors who interested in steel, technology, healthcare, information, and energy industries.
- Copyright
- © 2022 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Keke Lin PY - 2022 DA - 2022/12/27 TI - Application of Mean-Variance Model in the U.S. Capital Market BT - Proceedings of the 2022 International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2022) PB - Atlantis Press SP - 749 EP - 757 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-052-7_86 DO - 10.2991/978-94-6463-052-7_86 ID - Lin2022 ER -