Tootfinder

An Efficient deep learning model to Predict Stock Price Movement Based on Limit Order Book
Jiahao Yang, Ran Fang, Ming Zhang, Jun Zhou
https://arxiv.org/abs/2505.22678

An Efficient deep learning model to Predict Stock Price Movement Based on Limit Order Book
In high-frequency trading (HFT), leveraging limit order books (LOB) to model stock price movements is crucial for achieving profitable outcomes. However, this task is challenging due to the high-dimensional and volatile nature of the original data. Even recent deep learning models often struggle to capture price movement patterns effectively, particularly without well-designed features. We observed that raw LOB data exhibits inherent symmetry between the ask and bid sides, and the bid-ask diffe…