Download pdf
Mean-Variance Application of Portfolio Management in Hong Kong Stock Market
- 1 Economy and Finance, Hong Kong Shue Yan University, Hong Kong Island, Hong Kong SAR, China
* Author to whom correspondence should be addressed.
Abstract
The Hong Kong stock market is one of the world's top financial markets, and some investors want to gain benefits by investing in the Hong Kong stock mar-ket. Some studies have found that reasonable asset management can effectively reduce risks and increase returns. Therefore, the research topic of this paper is the importance of investment portfolio for investors to profit in Hong Kong stock as a financial market. The research methodology of this paper is as follows: firstly, we collect the data of Hong Kong stock market, secondly, we organize and combine the data, and use the mean variance model to calculate the maximum return and risk under the asset portfolio. The results show that the portfolio can effectively improve the return and risk value of investments. The E Commerce and Internet Services sector has always been a large part of the portfolio and can be a prime target for investors.
Keywords
Hong Kong Stock., Mean-Variance Model, R, Portfolio Management
[1]. Qin Dian Star - International Financial Centre - How did Hong Kong develop?, https://www.qindianstar.com/34915/.html, last accessed 2022/06/18.
[2]. Cooper R G, F., Edgett S J, S., Kleinschmidt E J, T.: Portfolio Management. Pegasus, New York (2001).
[3]. DÍAZ, R., F., SOLARES, E., S., DE-LEÓN-GÓMEZ, V.,T., etal.: Stock Portfolio Management in the Presence of Downtrends using Computational Intelligence. Journal 12(8), 4067, (2022).
[4]. LIU, J., F., CHENG, Y., S., LI, X., T., etal.: The Role of Risk Forecast and Risk Tolerance in Portfolio Management: A Case Study of the Chinese Financial Sector. Journal 11(3), 134 (2022).
[5]. PUSHPA, N.R., F., Luan Carlos de Sena, S., Monteiro Ozelim, T., etal.: Portfolio Management of Copula-Dependent Assets Based on Reliability Models: Revisiting Frank Copula and Dagum Distributions. Journal 4(4), 1027 (2021).
[6]. MITTAL, S.K., F., and NAMITA, S., S.: Mean-Variance-Skewness Portfolio Optimization Under Uncertain Environment using Improved Genetic Algorithm. Journal 54(8), 6011-6032 (2021).
[7]. HUANG, X., F., and GUOWEI, J., S.: Portfolio Management with Background Risk Under Uncertain Mean-Variance Utility. Journal 20 (3), 315-330 (2021).
[8]. All Industry Classifications, http://www.aastocks.com/sc/stocks/market/industry/industry-performance.aspx?&s=4&o=0, last accessed 2022/06/18.
[9]. Yahoo Finance Home Page, https://hk.finance.yahoo.com/, last accessed 2022/06/18.[9] Yahoo Finance Home Page, https://hk.finance.yahoo.com/, last accessed 2022/06/18.[9] Yahoo Finance Home Page, https://hk.finance.yahoo.com/, last accessed 2022/06/18.
[10]. Markowitz, H.M., F.: Portfolio Selection. Journal 7(1), 77-91, (1952).
[11]. Financial Time, https://www.ft.com/content/be68aac6-3d13-11e8-b9f9-de94fa33a81e, last accessed 2022/06/18
Cite this article
Li,Q. (2023). Mean-Variance Application of Portfolio Management in Hong Kong Stock Market. Advances in Economics, Management and Political Sciences,3,729-735.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
Disclaimer/Publisher's Note
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
About volume
Volume title: Proceedings of the 6th International Conference on Economic Management and Green Development (ICEMGD 2022), Part Ⅰ
© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license. Authors who
publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons
Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this
series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published
version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial
publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and
during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See
Open access policy for details).