Application of Mean-Variance Model in the U.S. Capital Market

Keke Lin ()
Additional contact information
Keke Lin: The University of Melbourne, Faculty of Business and Economics

A chapter in Proceedings of the 2022 International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2022), 2022, pp 749-757 from Springer

Abstract: 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.

Keywords: Mean-variance; capital market; FF3F; sharpe ratio (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:978-94-6463-052-7_86

Ordering information: This item can be ordered from
http://www.springer.com/9789464630527

DOI: 10.2991/978-94-6463-052-7_86

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 ().