Research Article
Portfolio Optimization and Modeling Analysis for Portfolio Return
@INPROCEEDINGS{10.4108/eai.18-11-2022.2327134, author={Jiantao Lei and Bowen Xiao and Yufei Xue}, title={Portfolio Optimization and Modeling Analysis for Portfolio Return}, proceedings={Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China}, publisher={EAI}, proceedings_a={ICEMME}, year={2023}, month={2}, keywords={portfolio optimization machine learning factor model pandemic}, doi={10.4108/eai.18-11-2022.2327134} }- Jiantao Lei
Bowen Xiao
Yufei Xue
Year: 2023
Portfolio Optimization and Modeling Analysis for Portfolio Return
ICEMME
EAI
DOI: 10.4108/eai.18-11-2022.2327134
Abstract
This paper mainly focuses on two parts – portfolio optimization and modeling. The theory of efficient frontier and Sharpe ratio are used to optimize and select the portfolio. The paper's portfolio used to do further research is the frontier portfolio with the most significant Sharpe ratio. This paper also provides an analysis and evaluation of the significance of the features in the Fama-French 5-factor model by applying a series of machine learning models and comparing the Sklearn score. Based on the conclusions of the 5-factor model analysis, this paper also quantifies the impact of the pandemic, develops a 6-factor model and a new 3-factor model, and compares them with the Fama-French 5-factor model. The result shows that the 3-factor model is better than the other two models.