使用 CNN 和 Transformer 进行金融时间序列预测（英文版）

英文标题：Financial Time Series Forecasting using CNN and Transformer中文摘要：本文提出了通过使用卷积神经网络和 Transformers 来捕捉时间序列中的短期和长期依赖，并用于预测股票价格变化，与传统的统计和深度学习方法相比，实验结果表明该方法取得了成功。英文摘要：Time series forecasting is important across various domains fordecision-making. In particular, financial time series such as stock prices canbe hard to predict as it is difficult to model short-term and long-termtemporal dependencies between data points. Convolutional Neural Networks (CNN)are good at capturing local patterns for model