Issue |
RAIRO-Oper. Res.
Volume 58, Number 2, March-April 2024
|
|
---|---|---|
Page(s) | 1315 - 1331 | |
DOI | https://doi.org/10.1051/ro/2024036 | |
Published online | 05 April 2024 |
Optimization of short-term stock selection based on volume and price using a non-cooperative parallel DEA model
1
School of Finance, Shandong University of Finance and Economics, Jinan, Shandong, P.R. China
2
School of Pharmaceutical Sciences, Qilu University of Technology, Shandong Academy of Sciences, Jinan 250014, P.R. China
3
School of Public Finance and Taxation, Shandong University of Finance and Economics, Jinan, Shandong, P.R. China
* Corresponding author: shixiao@sdufe.edu.cn, 6314529@qq.com
Received:
18
July
2023
Accepted:
4
February
2024
This paper presents a novel approach to portfolio optimization in the field of finance, with a specific focus on short-term yield. Existing literature has mainly utilized fundamental data to predict long-term trends in stock prices, but our proposed methodology utilizes technical indicators based on the theory of chasing up. Furthermore, we address the non-cooperative nature of volume and price fluctuation indicators and introduce non-cooperative theory into the short-term volume and price stock selection scheme for the first time. We propose an optimization of short-term stock selection based on volume and price using a non-cooperative parallel Data Envelopment Analysis (DEA) model, which we apply to Chinese main board listed companies. Our empirical results demonstrate the effectiveness of our model in selecting high-yield stocks in the short term. This paper contributes to the ongoing discussion on portfolio optimization and presents a compelling solution for investors seeking to maximize their financial gains. The proposed methodology can be utilized in practical applications and has significant implications for the financial industry.
Mathematics Subject Classification: 90B030
Key words: Portfolio optimization / short-term trading / data envelopment analysis / technical indicators / non-cooperative theory
© The authors. Published by EDP Sciences, ROADEF, SMAI 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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