Research paper / RESOURCE PROFILE

Multi-Graph Convolutional Network for Stock Movement

Multi-graph convolution exploiting sector and supply-chain relations for stock prediction.

arxiv.orgPublished May 11, 2020
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Overview

Multi-graph convolution exploiting sector and supply-chain relations for stock prediction.

Topics & capabilities

graph-neural-networkpaperstock-prediction

Publication information

Publication title
Multi-Graph Convolutional Network for Relationship-Driven Stock Movement Prediction
Authors
Jiexia Ye, Juanjuan Zhao, Kejiang Ye, Chengzhong Xu
Published
May 11, 2020
Last publication revision
Oct 26, 2020
Venue / journal
2020 25th International Conference on Pattern Recognition (ICPR)
Subject areas
q-fin.ST, cs.LG
DOI
10.1109/ICPR48806.2021.9412695 ↗
Publication source
arxiv.org · abs/2005.04955v3 ↗

Source: arXiv API · observed Oct 11, 2026.

Source links & provenance

https://arxiv.org/abs/2005.04955 ↗

Discovery references

References explain how this resource entered the collection. They do not represent an endorsement.

Explore related resources

Screenshot unavailableResource information and source links remain available. DeepIntoStreams/TSFM_Finance — reviewed source website screenshot
RepositoryChecked capture

DeepIntoStreams/TSFM_Finance

github.com

the official implementation of the paper “Re(visiting) Time Series Foundation Models in Finance”.

GitHub stars
31
Language
Jupyter Notebook
Code license
Apache-2.0
foundation-modeltime-seriesresearch-lab
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