Corpus ID: 231942649

Deep Learning for Market by Order Data

@article{Zhang2021DeepLF,
  title={Deep Learning for Market by Order Data},
  author={Zihao Zhang and Bryan Lim and S. Zohren},
  journal={ArXiv},
  year={2021},
  volume={abs/2102.08811}
}
Market by order (MBO) data – a detailed feed of individual trade instructions for a given stock on an exchange – is arguably one of the most granular sources of microstructure information. While limit order books (LOBs) are implicitly derived from it, MBO data is largely neglected by current academic literature which focuses primarily on LOB modelling. In this paper, we demonstrate the utility of MBO data for forecasting high-frequency price movements, providing an orthogonal source of… Expand

Figures and Tables from this paper

References

SHOWING 1-10 OF 41 REFERENCES
Deep Learning
  • 26,382
  • Highly Influential
  • PDF
Enhancing Time-Series Momentum
  • 2019
Universal Features of Price Formation in Financial Markets: Perspectives From Deep Learning
  • 95
  • Highly Influential
  • PDF
The Kolmogorov-Smirnov Test for Goodness of Fit
  • 3,950
  • Highly Influential
NASDAQ, OUCH.
  • http://www.nasdaqtrader.com/content/
  • 2020
DeepLOB: Deep Convolutional Neural Networks for Limit Order Books
  • 51
  • PDF
Deep Reinforcement Learning for Active High Frequency Trading
  • 1
  • PDF
Time-series forecasting with deep learning: a survey
  • Bryan Lim, S. Zohren
  • Mathematics, Computer Science
  • Philosophical Transactions of the Royal Society A
  • 2021
  • 21
  • PDF
2020a. “Deep learning for portfolio
  • 2020
Deep Learning Modeling of the Limit Order Book: A Comparative Perspective
  • 2
  • PDF
...
1
2
3
4
5
...