Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
Series Vol. 53 , 01 December 2023
Open
Access | Article
Investigation of Optimizing Portfolio for Ten Chosen Stocks
* Author to whom correspondence should be addressed.
Abstract
This article is mainly about finding the most efficient portfolio for some chosen stocks in the S&P 500. It is an application of portfolio management. The article introduced data collection and processing for 10 important S&P 500 companies’ stock data. These companies are chosen as representatives of different industries. The data processing will give sufficient material for the following calculation, such as the covariance matrix for those stocks, average return, monthly return, etc. Markowitz’s model is a model for portfolio optimization. Using this model to first minimize the standard deviation, in other words, the risk, and then, the most efficient portfolio weighting for those companies can be chosen. Solver in Excel is also used based on previous data to test the accuracy of the result calculated based on the model. Then, the article introduces possible errors during the calculation and corresponding reflection and improvement.
Keywords
portfolio management, stocks, Markowitz’s model
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 2nd International Conference on Financial Technology and Business Analysis
- ISBN (Print)
- 978-1-83558-153-7
- ISBN (Online)
- 978-1-83558-154-4
- Published Date
- 01 December 2023
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/53/20230805
- Copyright
- 01 December 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