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A Review on Graph Neural Network Methods in Financial Applications. (arXiv:2111.15367v2 [q-fin.ST] UPDATED)
cs.LG updates on arXiv.org arxiv.org
With multiple components and relations, financial data are often presented as
graph data, since it could represent both the individual features and the
complicated relations. Due to the complexity and volatility of the financial
market, the graph constructed on the financial data is often heterogeneous or
time-varying, which imposes challenges on modeling technology. Among the graph
modeling technologies, graph neural network (GNN) models are able to handle the
complex graph structure and achieve great performance and thus could be used …
applications arxiv financial financial applications graph graph neural network network neural network review