论文标题
通过深度学习技术的股票市场预测：一项调查
Stock Market Prediction via Deep Learning Techniques: A Survey
论文作者
论文摘要
现有对股票市场预测的调查通常集中在传统的机器学习方法上，而不是深度学习方法。这激发了我们对股票市场预测研究的结构化和全面的概述。我们提出了四个详细的股票市场预测子任务，并提出了一种新颖的分类法，以总结基于深神经网络的最新模型。此外，我们还提供有关股票市场常用的数据集和评估指标的详细统计数据。最后，我们通过分享有关股票市场预测的一些新观点来指出以后的几个方向。
Existing surveys on stock market prediction often focus on traditional machine learning methods instead of deep learning methods. This motivates us to provide a structured and comprehensive overview of the research on stock market prediction. We present four elaborated subtasks of stock market prediction and propose a novel taxonomy to summarize the state-of-the-art models based on deep neural networks. In addition, we also provide detailed statistics on the datasets and evaluation metrics commonly used in the stock market. Finally, we point out several future directions by sharing some new perspectives on stock market prediction.
