Abstract: Most existing graph neural networks (GNNs) learn node embeddings using the framework of message passing and aggregation. Such GNNs are incapable of learning relative positions between graph ...
Abstract: This study aims to address the challenges of financial price prediction in high-frequency trading (HFT) by introducing a novel continual learning framework based on factor predictors via ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback