Trading Graph Neural Network

• URL: http://arxiv.org/abs/2504.07923v1
• Date: Thu, 10 Apr 2025 17:40:31 GMT
• Title: Trading Graph Neural Network
• Authors: Xian Wu,
• Abstract summary: This paper proposes a new algorithm -- Trading Graph Neural Network (TGNN)<n>TGNN can structurally estimate the impact of asset features, dealer features and relationship features on asset prices in trading networks.
• Score: 37.61581005113347
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper proposes a new algorithm -- Trading Graph Neural Network (TGNN) that can structurally estimate the impact of asset features, dealer features and relationship features on asset prices in trading networks. It combines the strength of the traditional simulated method of moments (SMM) and recent machine learning techniques -- Graph Neural Network (GNN). It outperforms existing reduced-form methods with network centrality measures in prediction accuracy. The method can be used on networks with any structure, allowing for heterogeneity among both traders and assets.

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