Predicting FX market movements using GAN with limit order event data
• GAN can predict a 5-minute FX return. • GAN with limit order events performs best. • Limit orders contribute to price discovery of FX rates. This study employs generative adversarial network (GAN) models to forecast 5-minute foreign exchange (FX) rate returns. Compared to the Long Short-Term Memory (LSTM) model, GAN demonstrates a significant economic advantage. Notably, the GAN that incorporates limit order events outperforms those that consider liquidity and market order variables. Additionally, the GAN with limit orders achieves tangible economic gains. Consequently, this study provides empirical evidence that adds to the existing literature on market structure regarding informed trading through limit orders.
Authors
- Yoshihiro Kitamura (ORCID: https://orcid.org/0000-0002-3576-9990)
- Hitoshi Iima (ORCID: https://orcid.org/0000-0001-9596-8679)
- Kexin Peng (ORCID: https://orcid.org/0000-0002-6591-6509)
Institutions
- Waseda University (JP)
- Kyoto Institute of Technology (JP)
Publication Details
- Journal
- Finance research letters
- Published
- 2024-11-29
- DOI
- https://doi.org/10.1016/j.frl.2024.106527
- Citations
- 2
- Primary Topic
- Financial Markets and Investment Strategies
- Type
- article
- Field-Weighted Citation Impact
- 1.08
Funders
- Japan Society for the Promotion of Science