Research and Analysis on Markowitz Model and Index Model of Portfolio Selection
These authors contributed equally.
- DOI
- 10.2991/assehr.k.211209.186How to use a DOI?
- Keywords
- Markowitz model; Index model; risk; optimize the portfolio
- Abstract
With the development of stock portfolio theory, the research value of risk dispersion has become increasingly prominent. How investors construct portfolios has become an important research topic. In the article, we use recent 20 years of historical daily total return data for ten stocks, which belong in groups to three-four different sectors according to Yahoo Finance, the S&P 500 equity index, which include a total of eleven risky assets and a proxy for a risk-free rate, 1-month Fed Funds rate. We calculate all proper optimization inputs for the full Markowitz model, alongside the Index model. Using these optimization inputs for Markowitz model and Index model will need to the regions of permissible portfolios for the five different cases of the additional constraints. We present the results in both the tabular and graphical form with the objective to make inferences and comparisons between the sets of constraints for each optimization problem and between the Markowitz model and Index model. We hope to get an optimal portfolio by comparing the two models under different conditions. Also, we hope that the results of this project can lay a foundation for future on data analysis and investment portfolio creation.
- Copyright
- © 2021 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Mingzhou Jin AU - Zexin Li AU - Shengkai Yuan PY - 2021 DA - 2021/12/15 TI - Research and Analysis on Markowitz Model and Index Model of Portfolio Selection BT - Proceedings of the 2021 3rd International Conference on Economic Management and Cultural Industry (ICEMCI 2021) PB - Atlantis Press SP - 1142 EP - 1150 SN - 2352-5428 UR - https://doi.org/10.2991/assehr.k.211209.186 DO - 10.2991/assehr.k.211209.186 ID - Jin2021 ER -