Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 7th International Conference on Economic Management and Green Development
Series Vol. 44 , 10 November 2023
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The Application of the Markowitz Model for Portfolio Optimization in High-End Companies
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Abstract
This study investigates the application of the Markowitz Model in optimizing portfolios of high-end companies. By analyzing a 20-year dataset spanning 2001 to 2021, this paper explores the construction of efficient and minimum variance frontiers and their performance compared to the index model and the naive portfolio approach. The findings highlight the limitations of relying solely on historical data, as past performance may not accurately predict future outcomes due to evolving market conditions and company-specific factors. Additionally, the study emphasizes the need for incorporating practical factors such as transaction costs and liquidity constraints into the evaluation of portfolio optimization models. Furthermore, the study acknowledges the limitations of its focus on certain companies, recognizing that findings may not be directly applicable to other regions and markets with differing economic, regulatory, and industry dynamics. While the Markowitz Model offers a sophisticated framework for portfolio optimization, it is important to consider these limitations and conduct further research to enhance its effectiveness in diverse investment contexts.
Keywords
Markowitz Model, Stock Market, portfolio optimization
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 7th International Conference on Economic Management and Green Development
- ISBN (Print)
- 978-1-83558-109-4
- ISBN (Online)
- 978-1-83558-110-0
- Published Date
- 10 November 2023
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/44/20232200
- Copyright
- 10 November 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