MENDNet: Memory-Enhanced Dependency Network for Multistock Movement Prediction.
This article proposes a novel Memory-ENhanced Dependency Network, dubbed as MENDNet, for the multistock movement prediction task, and develops a well-elaborated memory structure to store selective news history for each stock, so that history embeddings can be dynamically estimated by attentively aggregating exclusive history information.