GCNET: graph-based prediction of stock price movement using graph convolutional network. (arXiv:2203.11091v2 [q-fin.TR] UPDATED)

The importance of considering related stocks data for the prediction of stock
price movement has been shown in many studies, however, advanced graphical
techniques for modeling, embedding and analyzing the behavior of interrelated
stocks have not been widely exploited for the prediction of stocks price
movements yet. The main challenges in this domain are to find a way for
modeling the existing relations among an arbitrary set of stocks and to exploit
such a model for improving the prediction performance …

arxiv graph graph-based network prediction price stock