An Empirical Analysis of Portfolio Management

Yuyan Luo

doi:10.54254/2754-1169/24/20230413

Research Article

Open access

Published on 13 September 2023

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Luo,Y. (2023). An Empirical Analysis of Portfolio Management. Advances in Economics, Management and Political Sciences,24,43-49.

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An Empirical Analysis of Portfolio Management

Yuyan Luo *^,1,

¹ The University of Sydney

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2754-1169/24/20230413

Abstract

In the modern era, finance is a tool that anyone is able to use to manage their wealth. People are eager to invest their extra money, and this piece is written with individual investors in mind who can utilize it as a resource when building a portfolio. In this study, the CAPM model and Markowitz model are used to determine the efficient frontier, capital allocation line, minimum risk portfolio, and optimal portfolio using three stocks chosen from various exchange markets and the SPX index. The data was analyzed to demonstrate that higher risk carries a higher expected return, and that the stock price also adheres to the normal distribution theory. Additionally, it covers the pertinent risk factors and how to diversify the risks. This paper offers guidance regarding the management of wealth for individual investors.

Keywords

portfolio management, capital allocation, expectations

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Cite this article

Luo,Y. (2023). An Empirical Analysis of Portfolio Management. Advances in Economics, Management and Political Sciences,24,43-49.

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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About volume

Volume title: Proceedings of the 2023 International Conference on Management Research and Economic Development

Conference website: https://2023.icmred.org/

ISBN：978-1-915371-91-1(Print) / 978-1-915371-92-8(Online)

Conference date: 28 April 2023

Editor：Canh Thien Dang, Javier Cifuentes-Faura

Series: Advances in Economics, Management and Political Sciences

Volume number: Vol.24

ISSN：2754-1169(Print) / 2754-1177(Online)

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