Research on the Investment Strategy of Private Equity Investment Fund Targeted Increase in NEEQ - An Empirical Analysis Based on BP and Hopfield Neural Network Model

被引：0
|
作者：
Yajuan, Liu [1 ]
Wenbin, Xu [1 ]
机构：
[1] Beijing Informat Sci & Technol Univ, Sch Econ & Management, Beijing 100192, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS | 2023年
关键词：
Private equity investment fund; National Equities Exchange and Quotations; BP neural network model; Hopfield neural network model;
D O I：
10.1142/S1469026823420014
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Private equity investment funds targeted increase in NEEQ has become a new strategy for PE investment. However, the currently adopted Logit regression and one-factor ANOVA models are not suitable for analyzing nonlinear investment activities, and the investment appraisal does not work well. In this paper, all NEEQ companies that implemented private placement in 2017 are used as the study sample. This paper also empirically analyzes the current situation of domestic private equity investment funds based on BP and Hopfield neural network models, then the results of the two models are compared. It is concluded that the accuracy of the BP neural network model can be more than 90%. So, the BP neural network can be used as the optimal model of private equity investment funds investment strategy in NEEQ.
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页数：20
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