文章基本信息

标题：Predicting S&P 500 Market Price by Deep Neural Network and Enemble Model
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作者：Feiyu Wang
期刊名称：E3S Web of Conferences
印刷版ISSN：2267-1242
电子版ISSN：2267-1242
出版年度：2020
卷号：214
页码：1-4
DOI：10.1051/e3sconf/202021402040
出版社：EDP Sciences
摘要：The method to predict the movement of stock market has appealed to scientists for decades. In this article, we use three different models to tackle that problem. In particular, we propose a Deep Neural Network (DNN) to predict the intraday direction of SP500 index and compare the DNN with two conventional machine learning models, i.e. linear regression, support vector machine. We demonstrate that DNN is able to predict SP500 index with relatively highest accuracy.