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Temporal Relational Ranking for Stock Prediction

Citations

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Cited by:

  1. Yuhui Jin, 2024. "GraphCNNpred: A stock market indices prediction using a Graph based deep learning system," Papers 2407.03760, arXiv.org, revised Jul 2024.
  2. Kelvin J. L. Koa & Yunshan Ma & Ritchie Ng & Huanhuan Zheng & Tat-Seng Chua, 2024. "Temporal Relational Reasoning of Large Language Models for Detecting Stock Portfolio Crashes," Papers 2410.17266, arXiv.org.
  3. Yang Qiao & Yiping Xia & Xiang Li & Zheng Li & Yan Ge, 2023. "Higher-order Graph Attention Network for Stock Selection with Joint Analysis," Papers 2306.15526, arXiv.org.
  4. Yao Wang & Jingmei Zhao & Qing Li & Xiangyu Wei, 2024. "Considering momentum spillover effects via graph neural network in option pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(6), pages 1069-1094, June.
  5. Wentao Zhang & Lingxuan Zhao & Haochong Xia & Shuo Sun & Jiaze Sun & Molei Qin & Xinyi Li & Yuqing Zhao & Yilei Zhao & Xinyu Cai & Longtao Zheng & Xinrun Wang & Bo An, 2024. "A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist," Papers 2402.18485, arXiv.org, revised Jun 2024.
  6. Kelvin J. L. Koa & Yunshan Ma & Ritchie Ng & Tat-Seng Chua, 2023. "Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction," Papers 2309.00073, arXiv.org, revised Oct 2023.
  7. Sheng Xiang & Dawei Cheng & Chencheng Shang & Ying Zhang & Yuqi Liang, 2023. "Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction," Papers 2305.08740, arXiv.org.
  8. Kelvin J. L. Koa & Yunshan Ma & Ritchie Ng & Tat-Seng Chua, 2024. "Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models," Papers 2402.03659, arXiv.org, revised Feb 2024.
  9. Wentao Zhang & Yilei Zhao & Shuo Sun & Jie Ying & Yonggang Xie & Zitao Song & Xinrun Wang & Bo An, 2023. "Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools," Papers 2311.10801, arXiv.org, revised Feb 2024.
  10. Wendi Zhang & Bin Li & Alan Wee-Chung Liew & Eduardo Roca & Tarlok Singh, 2023. "Predicting the returns of the US real estate investment trust market: evidence from the group method of data handling neural network," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-33, December.
  11. Engin Tas & Ayca Hatice Atli, 2024. "Stock Price Ranking by Learning Pairwise Preferences," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 513-528, February.
  12. Luke Sanborn & Matthew Sahagun, 2023. "Media Moments and Corporate Connections: A Deep Learning Approach to Stock Movement Classification," Papers 2309.06559, arXiv.org.
  13. Thanh Trung Huynh & Minh Hieu Nguyen & Thanh Tam Nguyen & Phi Le Nguyen & Matthias Weidlich & Quoc Viet Hung Nguyen & Karl Aberer, 2022. "Efficient Integration of Multi-Order Dynamics and Internal Dynamics in Stock Movement Prediction," Papers 2211.07400, arXiv.org, revised Nov 2022.
  14. Wentao Xu & Weiqing Liu & Lewen Wang & Yingce Xia & Jiang Bian & Jian Yin & Tie-Yan Liu, 2021. "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information," Papers 2110.13716, arXiv.org, revised Jan 2022.
  15. Liping Wang & Jiawei Li & Lifan Zhao & Zhizhuo Kou & Xiaohan Wang & Xinyi Zhu & Hao Wang & Yanyan Shen & Lei Chen, 2023. "Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey," Papers 2308.04947, arXiv.org.
  16. Meng Gao & Chenji Wei & Xiangguo Zhao & Ruijie Huang & Jian Yang & Baozhu Li, 2022. "Production Forecasting Based on Attribute-Augmented Spatiotemporal Graph Convolutional Network for a Typical Carbonate Reservoir in the Middle East," Energies, MDPI, vol. 16(1), pages 1-21, December.
  17. Weizhe Ren & Yichen Qin & Yang Li, 2024. "Alpha Mining and Enhancing via Warm Start Genetic Programming for Quantitative Investment," Papers 2412.00896, arXiv.org.
  18. Shuo Sun & Rundong Wang & Bo An, 2021. "Reinforcement Learning for Quantitative Trading," Papers 2109.13851, arXiv.org.
  19. Cheng Zhao & Ping Hu & Xiaohui Liu & Xuefeng Lan & Haiming Zhang, 2023. "Stock Market Analysis Using Time Series Relational Models for Stock Price Prediction," Mathematics, MDPI, vol. 11(5), pages 1-13, February.
  20. Xin Zhang & Lan Wu & Zhixue Chen, 2021. "Constructing long-short stock portfolio with a new listwise learn-to-rank algorithm," Papers 2104.12484, arXiv.org.
  21. Chang Zong & Hang Zhou, 2024. "Stock Movement Prediction with Multimodal Stable Fusion via Gated Cross-Attention Mechanism," Papers 2406.06594, arXiv.org, revised Dec 2024.
  22. Hao Qian & Hongting Zhou & Qian Zhao & Hao Chen & Hongxiang Yao & Jingwei Wang & Ziqi Liu & Fei Yu & Zhiqiang Zhang & Jun Zhou, 2024. "MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction," Papers 2402.06633, arXiv.org.
  23. Yong Xie & Dakuo Wang & Pin-Yu Chen & Jinjun Xiong & Sijia Liu & Sanmi Koyejo, 2022. "A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Predictions," Papers 2205.01094, arXiv.org, revised Jul 2022.
  24. Fuli Feng & Huimin Chen & Xiangnan He & Ji Ding & Maosong Sun & Tat-Seng Chua, 2018. "Enhancing Stock Movement Prediction with Adversarial Training," Papers 1810.09936, arXiv.org, revised Jun 2019.
  25. Jian Guo & Saizhuo Wang & Lionel M. Ni & Heung-Yeung Shum, 2022. "Quant 4.0: Engineering Quantitative Investment with Automated, Explainable and Knowledge-driven Artificial Intelligence," Papers 2301.04020, arXiv.org.
  26. Aiusha Sangadiev & Rodrigo Rivera-Castro & Kirill Stepanov & Andrey Poddubny & Kirill Bubenchikov & Nikita Bekezin & Polina Pilyugina & Evgeny Burnaev, 2020. "DeepFolio: Convolutional Neural Networks for Portfolios with Limit Order Book Data," Papers 2008.12152, arXiv.org.
  27. Hu Tian & Xiaolong Zheng & Kang Zhao & Maggie Wenjing Liu & Daniel Dajun Zeng, 2022. "Inductive Representation Learning on Dynamic Stock Co-Movement Graphs for Stock Predictions," INFORMS Journal on Computing, INFORMS, vol. 34(4), pages 1940-1957, July.
  28. Daiki Matsunaga & Toyotaro Suzumura & Toshihiro Takahashi, 2019. "Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis," Papers 1909.10660, arXiv.org, revised Nov 2019.
  29. Yuefeng Cen & Mingxing Luo & Gang Cen & Cheng Zhao & Zhigang Cheng, 2022. "Financial Market Correlation Analysis and Stock Selection Application Based on TCN-Deep Clustering," Future Internet, MDPI, vol. 14(11), pages 1-14, November.
  30. Wentao Xu & Weiqing Liu & Chang Xu & Jiang Bian & Jian Yin & Tie-Yan Liu, 2021. "REST: Relational Event-driven Stock Trend Forecasting," Papers 2102.07372, arXiv.org, revised Feb 2021.
  31. Jianian Wang & Sheng Zhang & Yanghua Xiao & Rui Song, 2021. "A Review on Graph Neural Network Methods in Financial Applications," Papers 2111.15367, arXiv.org, revised Apr 2022.
  32. Jinan Zou & Qingying Zhao & Yang Jiao & Haiyao Cao & Yanxi Liu & Qingsen Yan & Ehsan Abbasnejad & Lingqiao Liu & Javen Qinfeng Shi, 2022. "Stock Market Prediction via Deep Learning Techniques: A Survey," Papers 2212.12717, arXiv.org, revised Feb 2023.
  33. Kei, Yik Lun & Chen, Yanzhen & Madrid Padilla, Oscar Hernan, 2023. "A partially separable model for dynamic valued networks," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
  34. Jianyuan Zhong & Zhijian Xu & Saizhuo Wang & Xiangyu Wen & Jian Guo & Qiang Xu, 2024. "DSPO: An End-to-End Framework for Direct Sorted Portfolio Construction," Papers 2405.15833, arXiv.org.
  35. Shuo Sun & Wanqi Xue & Rundong Wang & Xu He & Junlei Zhu & Jian Li & Bo An, 2021. "DeepScalper: A Risk-Aware Reinforcement Learning Framework to Capture Fleeting Intraday Trading Opportunities," Papers 2201.09058, arXiv.org, revised Aug 2022.
  36. Yunhua Pei & Jin Zheng & John Cartlidge, 2024. "Dynamic Graph Representation with Contrastive Learning for Financial Market Prediction: Integrating Temporal Evolution and Static Relations," Papers 2412.04034, arXiv.org.
  37. Zexin Hu & Yiqi Zhao & Matloob Khushi, 2021. "A Survey of Forex and Stock Price Prediction Using Deep Learning," Papers 2103.09750, arXiv.org.
  38. Shuo Sun & Rundong Wang & Bo An, 2022. "Quantitative Stock Investment by Routing Uncertainty-Aware Trading Experts: A Multi-Task Learning Approach," Papers 2207.07578, arXiv.org.
  39. Chaoran Cui & Xiaojie Li & Juan Du & Chunyun Zhang & Xiushan Nie & Meng Wang & Yilong Yin, 2021. "Temporal-Relational Hypergraph Tri-Attention Networks for Stock Trend Prediction," Papers 2107.14033, arXiv.org, revised Mar 2022.
  40. Uddin, Ajim & Tao, Xinyuan & Yu, Dantong, 2023. "Attention based dynamic graph neural network for asset pricing," Global Finance Journal, Elsevier, vol. 58(C).
  41. Soroush Omranpour & Guillaume Rabusseau & Reihaneh Rabbany, 2024. "Higher Order Transformers: Enhancing Stock Movement Prediction On Multimodal Time-Series Data," Papers 2412.10540, arXiv.org.
  42. Yu Zhao & Huaming Du & Ying Liu & Shaopeng Wei & Xingyan Chen & Fuzhen Zhuang & Qing Li & Ji Liu & Gang Kou, 2022. "Stock Movement Prediction Based on Bi-typed Hybrid-relational Market Knowledge Graph via Dual Attention Networks," Papers 2201.04965, arXiv.org, revised Jan 2022.
  43. Tan, Jinghua & Li, Zhixi & Zhang, Chuanhui & Shi, Long & Jiang, Yuansheng, 2024. "A multiscale time-series decomposition learning for crude oil price forecasting," Energy Economics, Elsevier, vol. 136(C).
  44. Raehyun Kim & Chan Ho So & Minbyul Jeong & Sanghoon Lee & Jinkyu Kim & Jaewoo Kang, 2019. "HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction," Papers 1908.07999, arXiv.org, revised Nov 2019.
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