Stock Portfolio Decision Based on Cluster Analysis and Principal Component Analysis

DOI

10.2991/msmi-19.2019.25How to use a DOI?

Keywords

Portfolio theory, Diversification, Cluster analysis, Sharpe Ratio, Principal component analysis, Linear regression analysis.

Abstract

When determining the stock portfolio, it is necessary to consider factors such as the company's financial indicators, stock price trends, and macroeconomic conditions. In order to simplify the process, the clustering method is used to classify the company according to the financial indicator data, so as to select stocks when diversifying the investment, and then Sharp Ratio is calculated to conduct risk assessment on the selected targets. Finally, the principal component analysis method is used to simplify the obtained data, and then predict the future trend of the stock price by linear regression, and finally an ideal investment portfolio is determined.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yue Duan
PY  - 2019/06
DA  - 2019/06
TI  - Stock Portfolio Decision Based on Cluster Analysis and Principal Component Analysis
BT  - Proceedings of the 6th International Conference on Management Science and Management Innovation (MSMI 2019)
PB  - Atlantis Press
SP  - 135
EP  - 140
SN  - 2352-5428
UR  - https://doi.org/10.2991/msmi-19.2019.25
DO  - 10.2991/msmi-19.2019.25
ID  - Duan2019/06
ER  -