Optimization of short-term stock selection based on volume and price using a non-cooperative parallel DEA model

Author:

Shi XiaoORCID,Luo QinORCID,Zhang YanORCID,Zhao YishengORCID,Wang YananORCID,Shi TianshuORCID

Abstract

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.

Funder

University-Industry Collaborative Education Program of Ministry of Education

Key Projects of Shandong University of Finance and Economics Experimental Education Reform Project

National Nature Science Foundation of China

Natural Science Foundation of Shandong Province

Shandong Province Higher Educational Youth Innovation Team Development Program

The Humanities and Social Sciences Research Project of Ministry of Education of China

Publisher

EDP Sciences

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