Key papers

• Reproducing the first and second moments of empirical degree distributions (2025)
  Mattia Marzi et al.
  2.85
• Bi-Level Chaotic Fusion Based Graph Convolutional Network for Stock Market Prediction Interval (2026)
  Eshwar Sai Kandimalla et al.
  1.83
• Aligning Language Models with Investor and Market Behavior for Financial Recommendations (2025)
  Fernando Spadea and Oshani Seneviratne
  1.44
• From Headlines to Holdings: Deep Learning for Smarter Portfolio Decisions (2025)
  Yun Lin et al.
  1.39
• Detecting Fraud in Financial Networks: A Semi-Supervised GNN Approach with Granger-Causal Explanations (2025)
  Linh Nguyen et al.
  1.28
• NGAT: A Node-level Graph Attention Network for Long-term Stock Prediction (2025)
  Yingjie Niu et al.
  1.28
• Stock Price Prediction Using a Hybrid LSTM-GNN Model: Integrating Time-Series and Graph-Based Analysis (2025)
  Meet Satishbhai Sonani et al.
  1.00
• Corporate Fraud Detection in Rich-yet-Noisy Financial Graph (2025)
  Shiqi Wang et al.
  1.00
• Connecting actuarial judgment to probabilistic learning techniques with graph theory (2020)
  Roland R. Ramsahai
  —
• A Blockchain Transaction Graph based Machine Learning Method for Bitcoin Price Prediction (2020)
  Xiao Li and Weili Wu
  —
• Event-Driven Learning of Systematic Behaviours in Stock Markets (2020)
  Xianchao Wu
  —
• Algorithms for Learning Graphs in Financial Markets (2020)
  Jos\'e Vin\'icius de Miranda Cardoso and Jiaxi Ying and Daniel Perez Palomar
  —
• Loss of structural balance in stock markets (2021)
  E. Ferreira (1) et al.
  —
• Price graphs: Utilizing the structural information of financial time series for stock prediction (2021)
  Junran Wu et al.
  —
• Fund2Vec: Mutual Funds Similarity using Graph Learning (2021)
  Vipul Satone et al.
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• Temporal-Relational Hypergraph Tri-Attention Networks for Stock Trend Prediction (2021)
  Chaoran Cui et al.
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• Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling (2021)
  Liang Zhao et al.
  —
• HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information (2021)
  Wentao Xu et al.
  —
• A Review on Graph Neural Network Methods in Financial Applications (2021)
  Jianian Wang et al.
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• Stock Movement Prediction Based on Bi-typed Hybrid-relational Market Knowledge Graph via Dual Attention Networks (2022)
  Yu Zhao et al.
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• DAMNETS: A Deep Autoregressive Model for Generating Markovian Network Time Series (2022)
  Jase Clarkson et al.
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• Graph similarity learning for change-point detection in dynamic networks (2022)
  Deborah Sulem et al.
  —
• Monitoring the Dynamic Networks of Stock Returns (2022)
  Elena Farahbakhsh Touli et al.
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• Sequential Graph Attention Learning for Predicting Dynamic Stock Trends (Student Abstract) (2023)
  Tzu-Ya Lai et al.
  —
• Exploiting Supply Chain Interdependencies for Stock Return Prediction: A Full-State Graph Convolutional LSTM (2023)
  Chang Liu
  —
• Futures Quantitative Investment with Heterogeneous Continual Graph Neural Network (2023)
  Min Hu et al.
  —
• Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction (2023)
  Sheng Xiang et al.
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• Stock and market index prediction using Informer network (2023)
  Yuze Lu et al.
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• ChatGPT Informed Graph Neural Network for Stock Movement Prediction (2023)
  Zihan Chen et al.
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• Higher-order Graph Attention Network for Stock Selection with Joint Analysis (2023)
  Yang Qiao et al.
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• Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects (2023)
  Chao Zhang et al.
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• Multi-relational Graph Diffusion Neural Network with Parallel Retention for Stock Trends Classification (2024)
  Zinuo You et al.
  —
• MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction (2024)
  Hao Qian et al.
  —
• CaT-GNN: Enhancing Credit Card Fraud Detection via Causal Temporal Graph Neural Networks (2024)
  Yifan Duan et al.
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• Detecting Anomalous Events in Object-centric Business Processes via Graph Neural Networks (2024)
  Alessandro Niro and Michael Werner
  —
• Investigating Similarities Across Decentralized Financial (DeFi) Services (2024)
  Junliang Luo et al.
  —
• Temporal Graph Networks for Graph Anomaly Detection in Financial Networks (2024)
  Yejin Kim et al.
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• Exploiting the geometry of heterogeneous networks: A case study of the Indian stock market (2024)
  Pawanesh Pawanesh et al.
  —
• Stock Recommendations for Individual Investors: A Temporal Graph Network Approach with Mean-Variance Efficient Sampling (2024)
  Youngbin Lee et al.
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• A Deep Learning Method for Predicting Mergers and Acquisitions: Temporal Dynamic Industry Networks (2024)
  Dayu Yang
  —
• Advanced Financial Fraud Detection Using GNN-CL Model (2024)
  Yu Cheng et al.
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• TCGPN: Temporal-Correlation Graph Pre-trained Network for Stock Forecasting (2024)
  Wenbo Yan et al.
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• LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRU (2024)
  Peng Zhu et al.
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• Evaluating Financial Relational Graphs: Interpretation Before Prediction (2024)
  Yingjie Niu et al.
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• Dynamic graph neural networks for enhanced volatility prediction in financial markets (2024)
  Pulikandala Nithish Kumar et al.
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• MCI-GRU: Stock Prediction Model Based on Multi-Head Cross-Attention and Improved GRU (2024)
  Peng Zhu et al.
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• Graph Neural Networks for Financial Fraud Detection: A Review (2024)
  Dawei Cheng et al.
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• Robust Graph Neural Networks for Stability Analysis in Dynamic Networks (2024)
  Xin Zhang et al.
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