Transformer is a deep learning model that, having an innovative performance in many tasks, has uniquely and significantly modified all the cast of mind of the AI scientific community. In this paper, we introduce a Transformer model that is applied to 1-minute timescale in the EURUSD and GBPUSD instruments of forex trading. We use the classical Transformer architecture without the Decoder since the Encoder is enough. Moreover, the Exponential Moving Average (EMA) model is applied to the input, while different values of its smoothing factor α are tested. With cross-entropy training loss less than 0.2, it is exclamatory that Transformers are a promising tool for lucrative strategies in high-frequency trading.

中文翻译：

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高频交易中的变压器

Transformer 是一种深度学习模型，在许多任务中具有创新性能，独特且显着地改变了人工智能科学界的所有思维方式。在本文中，我们介绍了一种应用于 EURUSD 和 GBPUSD 外汇交易工具中 1 分钟时间尺度的 Transformer 模型。我们使用经典的 Transformer 架构，没有解码器，因为编码器就足够了。此外，将指数移动平均（EMA）模型应用于输入，同时测试其平滑因子α的不同值。交叉熵训练损失小于 0.2，令人惊叹的是 Transformers 是高频交易中利润丰厚策略的有前途的工具。