Stock Price Trend Prediction Model Based on Deep Residual Network and Stock Price Graph
2018 11th International Symposium on Computational Intelligence and Design (ISCID)(2018)
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.
更多查看译文
关键词
Stock price time series,ResNet,Stock price graph
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要