Temporal Relational Ranking for Stock Prediction

Feng, Fuli, He, Xiangnan, Wang, Xiang, Luo, Cheng, Liu, Yiqun, Chua, Tat-Seng·2019·ACM Transactions on Information Systems
DOI 10.1145/3309547

Cited by (562)

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  3. TGNS: A transformer-based graph neural network for stock trend forecasting
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  4. Causal-LLM: A Hybrid Framework for Automated Budgetary Variance Diagnosis and Reasoning
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  6. Portfolio Management Framework for Autonomous Stock Selection and Allocation
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  7. SMPDF: stock movement prediction based on stock prices and text
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  8. RAGIC: Risk-Aware Generative Framework for Stock Interval Construction
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  9. Constructing long-short stock portfolio with a new listwise learn-to-rank algorithm
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  10. SSAR-GNN: Self-Supervised Artist Recommendation from spatio-temporal perspectives in art history with Graph Neural Networks
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  11. Financial risk analysis of real estate bubble based on machine learning and factor analysis model
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  12. Hybrid Learning to Rank for Financial Event Ranking
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  13. Conducting stock market index prediction via the localized spatial–temporal convolutional network
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  14. MTMD: Multi-Scale Temporal Memory Learning and Efficient Debiasing Framework for Stock Trend Forecasting
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  15. Symmetry-Aware Transformers for Asymmetric Causal Discovery in Financial Time Series
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  16. A Generalized Model for Crowd Violence Detection Focusing on Human Contour and Dynamic Features
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  17. Financial Market Correlation Analysis and Stock Selection Application Based on TCN-Deep Clustering
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  18. Retracted: Prediction of stock market movement via technical analysis of stock data stored on blockchain using novel History Bits based machine learning algorithm
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  19. Conceptual-temporal graph convolutional neural network model for stock price movement prediction and application
    Fu-ping Zhang · 2023 · Soft Computing
  20. Deep Learning techniques for stock market forecasting: Recent trends and challenges
    Manali Patel, Krupa N. Jariwala, Chiranjoy Chattopadhyay · 2023 · International Conference on Software Engineering and Information Management (ICSIM)
  21. Stock Recommendations for Individual Investors: A Temporal Graph Network Approach with Mean-Variance Efficient Sampling
    Youngbin Lee, Y. Han Kim, Javier Sanz-Cruzado, Richard McCreadie, Yongjae Lee · 2024 · ACM International Conference on AI in Finance (ICAIF)
  22. Stock Trend Prediction using SV-kNNC and SOM
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  23. Implicit-Causality-Exploration-Enabled Graph Neural Network for Stock Prediction
    Ying Li, Xiaosha Xue, Zhipeng Liu, Peibo Duan, Bin Zhang · 2024 · Information
  24. MILLION: A General Multi-Objective Framework with Controllable Risk for Portfolio Management
    Liwei Deng, Tianfu Wang, Yan Chun Zhao, Kai Zheng · 2024 · Proceedings of the VLDB Endowment
  25. Unraveling asset pricing with AI: A systematic literature review
    Yan Chen, Lin Zhang, Zhilong Xie, Wenjie Zhang, Qing Li · 2025 · Applied Soft Computing
  26. A partially separable model for dynamic valued networks
    Yik Lun Kei, Yanzhen Chen, Oscar Hernán Madrid Padilla · 2023 · Computational Statistics & Data Analysis
  27. FollowAKOInvestor: Stock recommendation by hearing voices from all kinds of investors with machine learning
    Chuan Qin, Jun Chang, Wenting Tu, Changrui Yu · 2024 · Expert Systems with Applications
  28. Relational Fusion-based Stock Selection with Neural Recursive Ordinary Differential Equation Networks
    Qiang Gao, Xinzhu Zhou, Li Huang, Kunpeng Zhang, Siyuan Liu, Fan Zhou · 2024 · Information Fusion
  29. Multiple stocks recommendation: a spatio-temporal hypergraph learning approach
    Kong Xin, Chao Luo, Baozhong Gao · 2024 · Applied Intelligence
  30. A Stock Prediction Method Based on Multidimensional and Multilevel Feature Dynamic Fusion
    Yuxin Dong, Yongtao Hao · 2024 · Electronics
  31. Question Tagging via Graph-guided Ranking
    Xiao Zhang, Meng Liu, Jianhua Yin, Zhaochun Ren, Liqiang Nie · 2021 · ACM Transactions on Information Systems
  32. Learning knowledge-enriched company embeddings for investment management
    Gary Ang, Ee‐Peng Lim · 2021 · ACM International Conference on AI in Finance (ICAIF)
  33. Temporal knowledge graph reasoning triggered by memories
    Mengnan Zhao, Lihe Zhang, Yuqiu Kong, Baocai Yin · 2023 · Applied Intelligence
  34. Graph Neural Networks for Asset Management
    Grégoire Pacreau, Edmond Lezmi, Jiali Xu · 2022 · SSRN Electronic Journal
  35. ComNC: A unified framework for trends prediction integrating node and concept effects
    Sanchuan Xiao, Qing Li, Xiaoyue Gong, Jingmei Zhao, Lingyun Gu, Long Peng · 2025 · Neurocomputing
  36. Progressive Dependency Representation Learning for Stock Ranking in Uncertain Risk Contrasting
    Li Huang, Yanzhe Xie, Qiang Gao, Kunpeng Zhang, Guisong Liu, Xueqin Chen · 2025 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
  37. A temporal graph-based contrastive approach for financial time series forecasting
    Iman Barazandeh, Saman Haratizadeh, Georgios Sermpinis · 2025 · Engineering Applications of Artificial Intelligence
  38. An attributed multiplex network enabled GNN-based stock predictor with observable and non-observable information
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  39. GCN-KAN: A model to extract autocorrelation graph features and fuse Kolmogorov-Arnold networks for stock price trend prediction
    Ting Wang, Xudong Liu, Yi Liu, Xingjia Li, Xing Fan · 2025 · Applied Soft Computing
  40. SSTP: Stock Sector Trend Prediction with Temporal-Spatial Network
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  41. The Network of Mutual Funds: A Dynamic Heterogeneous Graph Neural Network for Estimating Mutual Funds Performance
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  43. Firm connection and equity return predictability – Graph-based machine learning methods
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  44. How can we predict transportation stock prices using artificial intelligence? Findings from experiments with Long Short-Term Memory based algorithms
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  45. Relational Stock Selection via Probabilistic State Space Learning
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  46. Stock Price Forecasting With Integration of Sectoral Behavior: A Deep Auto‐Optimized Multimodal Framework
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  47. Conflict or cooperation?
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  48. A Hierarchical Reinforcement Learning Framework for Stock Selection and Portfolio
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  55. Multiobjective portfolio management based on dynamic link prediction
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  56. Exploring financial sentiment analysis via fine-tuning large language model and attributed graph neural network
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  58. Ultimate Prediction of Stock Market Price Movement
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  59. Multi-scale Time Based Stock Appreciation Ranking Prediction via Price Co-movement Discrimination
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  60. Graph Representation Learning for Similarity Stocks Analysis
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  62. Diversified Adaptive Stock Selection Using Continual Graph Learning and Ensemble Approach
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  63. DeepFolio: Convolutional Neural Networks for Portfolios with Limit Order Book Data
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  64. Wizard of Search Engine: Access to Information Through Conversations with Search Engines
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  65. AI-powered Energy Internet Towards Carbon Neutrality: Challenges and Opportunities
    Chaojie Li · 2021
  66. Coherence mode: Characterizing local graph structural information for temporal knowledge graph
    Yuehang Si, Xingchen Hu, Qing Cheng, Xinwang Liu, Shixuan Liu, Jincai Huang · 2024 · Information Sciences
  67. Learning across modalities: a systematic survey of multimodal models for financial analysis
    Simone D’Amico, Fabio Mercorio, Navid Nobani, Giancarlo Sperlí, Carmine Ventre · 2026 · Information Fusion
  68. Neural Ranking Strategy for Portfolio Construction Using Transformers
    Shosuke Sakagawa, Naoki Mori · 2022 · IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)
  69. ALERTA-Net: A Temporal Distance-Aware Recurrent Networks for Stock Movement and Volatility Prediction
    Shengkun Wang, YangXiao Bai, Kaiqun Fu, Linhan Wang, Chang‐Tien Lu, Taoran Ji · 2023 · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
  70. Return prediction by machine learning for the Korean stock market
    Wonwoo Choi, Seong‐Ho Jang, Sanghee Kim, Chayoung Park, Sunyoung Park, Seongjoo Song · 2023 · Journal of the Korean Statistical Society
  71. Can Perturbations Help Reduce Investment Risks? Risk-aware Stock Recommendation via Split Variational Adversarial Training
    Jiezhu Cheng, Kaizhu Huang, Zibin Zheng · 2024 · ACM Transactions on Information Systems
  72. Portfolio optimization in the stock market under disruptions: Real case studies of COVID-19 pandemic and currency risk
    Amir Hossein Kamali, Seyed Hossein Iranmanesh, Fariba Goodarzian · 2024 · Engineering Applications of Artificial Intelligence
  73. A model based LSTM and graph convolutional network for stock trend prediction
    Xiangdong Ran, Zhiguang Shan, Yukang Fan, Lei Gao · 2024 · PeerJ Computer Science
  74. Analyzing the impact of investor sentiment on S&P 500 prices using deep learning models
    Danielle Khalife, Jad Yammine, Tatiana El Bazi, Chamseddine Zaki, Nada Jabbour Al Maalouf · 2024 · Journal of financial reporting & accounting
  75. A Distillation-based Future-aware Graph Neural Network for Stock Trend Prediction
    Zhipeng Liu, Peibo Duan, Mingyang Geng, Bin Zhang · 2025 · IEEE International Conference on Acoustics Speech and Signal Processing
  76. Robust stock trend prediction via volatility detection and hierarchical multi-relational hypergraph attention
    Suochao Yi, Jing Chi, Yandi Shi, Caiming Zhang · 2025 · Knowledge-Based Systems
  77. Beyond Complements and Substitutes: A Graph Neural Network Approach for Collaborative Retail Sales Forecasting
    Jing Liu, Gang Wang, Huimin Zhao, Mingfeng Lu, Lihua Huang, Gang Chen · 2025 · Information Systems Research
  78. T-FinKB: A Platform of Temporal Financial Knowledge Base Construction
    Xinyi Zhu, Liping Wang, Hao Xin, Xiaohan Wang, Jia Zhifeng, Jiyao Wang, Chunming Ma, Yuxiang Zengt · 2023 · IEEE International Conference on Data Engineering (ICDE)
  79. Efficiently Sampling and Estimating Hypergraphs By Hybrid Random Walk
    Lingling Zhang, Zhiwei Zhang, Guoren Wang, Ye Yuan · 2023 · IEEE International Conference on Data Engineering (ICDE)
  80. Multi-temporal Sequential Recommendation Model Based on the Fused Learning Preferences
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  81. An efficient loss function and deep learning approach for ranking stock returns in the absence of prior knowledge
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  82. A Static-Dynamic Hypergraph Neural Network Framework Based on Residual Learning for Stock Recommendation
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  83. Ensemble Learning with an Adversarial Hypergraph Model and a Convolutional Neural Network to Forecast Stock Price Variations
    Harmanjeet Singh, Preeti Sharma, Chander Prabha, Meenakshi, Supreet Singh · 2024 · Ingénierie des systèmes d information
  84. Prismatic: Interactive Multi-View Cluster Analysis of Concept Stocks
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  85. FinIR 2020: The First Workshop on Information Retrieval in Finance
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  86. Risk Forecasting from Earnings Calls Acoustics and Network Correlations
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  87. Multi-Channel Temporal Graph Convolutional Network for Stock Return Prediction
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  88. Mapping Investment Decision Studies: A Bibliometric Review
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  89. Deep Portfolio Optimization Modeling based on Conv-Transformers with Graph Attention Mechanism
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  90. Portfolio Selection via Graph-Aware Gaussian Processes With Generalized Gaussian Likelihood
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  91. MHieR-encoder: Modelling the high-frequency changes across stocks
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  92. MSGraph: Modeling multi-scale K-line sequences with graph attention network for profitable indices recommendation
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  93. Enhanced Temporal Knowledge Graph Completion via Learning High-Order Connectivity and Attribute Information
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  94. Dyn-GWN: Time-Series Forecasting using Time-varying Graphs with Applications to Finance and Traffic Prediction
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  95. Big portfolio selection by graph-based conditional moments method
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  97. TD-HCN: A trend-driven hypergraph convolutional network for stock return prediction
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  98. Reinforcement learning with temporal and variable dependency-aware transformer for stock trading optimization
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