Stock Price Trend Prediction Model Based on Deep Residual Network and Stock Price Graph

被引：5

作者：

Liu, Heng ^{[1
]}

Song, Bowen ^{[1
]}

机构：

[1] Xiamen Univ, Sch Informat Sci & Engn, Xiamen, Peoples R China

来源：

2018 11TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 2 | 2018年

关键词：

Stock price time series; ResNet; Stock price graph;

D O I：

10.1109/ISCID.2018.10176

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Consider that people often use stock price graph to make decisions, this paper introduce a deep residual network (ResNet) model for prediction, using the stock price graph as input. The results show that the ResNet model has the average accuracy of 0.40, which is higher than the stochastic indicator of 0.33.

引用

页码：328 / 331

页数：4

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