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Transformers in High-Frequency Trading

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Published under licence by IOP Publishing Ltd
, , Citation Konstantinos T. Kantoutsis et al 2024 J. Phys.: Conf. Ser. 2701 012134 DOI 10.1088/1742-6596/2701/1/012134

1742-6596/2701/1/012134

Abstract

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.

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10.1088/1742-6596/2701/1/012134