- Update: This repository is actively updated.
2025/01/14 - Collection: We've compiled a comprehensive list of awesome financial time series forecasting papers and codes.
- Collaborate: If there’s anything missing or if you'd like to contribute, please don't hesitate to get in touch!
- Awesome Financial Time Series Forecasting Papers and Codes
- Contents
- A. LLM-based Financial Time Series Forecasting Models
- B. LLM-based Financial Models
- C. Graph Neural Network-based Models
- D. Reinforcement Learning-based Models
- E. Transformer-based Models
- F. Generative Methods based Models
- G. Classical Time Series Models
- H. Quantitative Open Sourced Framework
- I. Survey
- All Thanks to Our Contributors :
AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
Yong Liu, Guo Qin, Xiangdong Huang, Jianmin Wang, Mingsheng Long
NeurIPS 2024. [Paper] | [Codes]
Are Language Models Actually Useful for Time Series Forecasting?
Mingtian Tan, Mike A. Merrill, Vinayak Gupta, Tim Althoff, Thomas Hartvigsen
NeurIPS 2024. [Paper] | [Codes]
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
Qingxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang
NeurIPS 2024. [Paper]
TEMPO: PROMPT-BASED GENERATIVE PRE-TRAINED TRANSFORMER FOR TIME SERIES FORECASTING
Defu Cao, Furong Jia, Sercan O. Arık, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu
ICLR 2024. [Paper] | [Codes]
GPT4MTS: Prompt-based Large Language Model for Multimodal Time-series Forecasting
Furong Jia, Kevin Wang, Yixiang Zheng, Defu Cao, Yan Liu
AAAI 2024. [Paper]
Multi-Patch Prediction: Adapting Language Models for Time Series Representation Learning
Qingxiang Liu, Xu Liu, Chenghao Liu, Qingsong Wen, Yuxuan Liang
ICML 2024. [Paper] | [Codes]
MOMENT: A Family of Open Time-series Foundation Models
Mononito Goswami, Konrad Szafer, Arjun Choudhry, Yifu Cai, Shuo Li, Artur Dubrawski
ICML 2024. [Paper] | [Codes]
TIME-LLM: TIME SERIES FORECASTING BY REPROGRAMMING LARGE LANGUAGE MODELS
Ming Jin, Shiyu Wang, Lintao Ma, Zhixuan Chu, James Y. Zhang, Xiaoming Shi, et.al.
ICLR 2024. [Paper] | [Codes]
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li, Xiangdong Huang, Jianmin Wang, Mingsheng Long
ICML 2024. [Paper] | [Codes]
Unified Training of Universal Time Series Forecasting Transformers
Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo
ICML 2024. [Paper]
TradingAgents: Multi-Agents LLM Financial Trading Framework
Yijia Xiao, Edward Sun, Di Luo, Wei Wang
Automate Strategy Finding with LLM in Quant investment
Zhizhuo Kou, Holam Yu, Jingshu Peng, Lei Chen
FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making
Yangyang Yu, Zhiyuan Yao, Haohang Li, Zhiyang Deng, Yupeng Cao, Qianqian Xie, et.al
NeurIPS 2024. [Paper] | [Codes]
FinRobot: AI Agent for Equity Research and Valuation with Large Language Models
Tianyu Zhou, Pinqiao Wang, Yilin Wu, Hongyang Yang
ICAIF 2024. [Paper] | [Codes]
A Multimodal Foundation Agent for Financial Trading: Tool-Augmented, Diversified, and Generalist
Wentao Zhang, Lingxuan Zhao, Haochong Xia, Shuo Sun, Jiaze Sun, Molei Qin, Bo An, et.al
KDD 2024. [Paper]
StockMixer: A Simple yet Strong MLP-based Architecture for Stock Price Forecasting
Jinyong Fan, Yanyan Shen
AAAI 2024. [Paper] | [Codes]
From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection
Xinlei Wang, Maike Feng, Jing Qiu, Jinjin Gu, Junhua Zhao
NeurIPS 2024. [Paper] | [Codes]
LLMFactor: Extracting Profitable Factors through Prompts for Explainable Stock Movement Prediction
Meiyun Wang, Kiyoshi Izumi, Hiroki Sakaji
ACL 2024. [Paper]
Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models
Kelvin J.L. Koa, Yunshan Ma,Ritchie Ng, Tat-Seng Chua
WWW 2024. [Paper] | [Codes]
S2IP-LLM: Semantic Space Informed Prompt Learning with LLM forTime Series Forecasting
Zijie Pan, Yushan Jiang, Sahil Garg, Anderson Schneider, Yuriy Nevmyvaka, Dongjin Song
ICML 2024. [Paper] | [Codes]
CFGPT: Chinese Financial Assistant with Large Language Model
Jiangtong Li, Yuxuan Bian, Guoxuan Wang, Yang Lei, Dawei Cheng, Zhijun Ding, Changjun Jiang
RA-CFGPT: Chinese financial assistant with retrieval-augmented large language model
Jiangtong Li, Yang Lei, Yuxuan Bian, Dawei Cheng, Zhijun Ding, Changjun Jiang
FCS 2024. [Paper]
CSPRD: A Financial Policy Retrieval Dataset for Chinese Stock Market
Jinyuan Wang, Zhong Wang, Zeyang Zhu, Jinhao Xie, Yong Yu, Yongjian Fei, Yue Huang, Dawei Cheng, Hai Zhao
DEXA 2024. [Paper] | [Codes]
FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets
Neng Wang, Hongyang Yang, Christina Dan Wang
NeurIPS 2023. [Paper] | [Codes]
FinGPT: Democratizing Internet-scale Data for Financial Large Language Models
Xiao-Yang Liu, Guoxuan Wang, Hongyang Yang, Daochen Zha
NeurIPS 2023. [Paper] | [Codes]
BloombergGPT: A Large Language Model for Finance
Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Gideon Mann, et.al
LSR-IGRU: Stock Trend Prediction Based on Long Short-Term Relationships and Improved GRU
Peng Zhu, Yuante Li, Yifan Hu, Qinyuan Liu, Dawei Cheng, Yuqi Liang
CIKM 2024. [Paper] | [Codes]
Automatic De-Biased Temporal-Relational Modeling for Stock Investment Recommendation
Weijun Chen, Shun Li, Xipu Yu, Heyuan Wang, Wei Chen, Tengjiao Wang
IJCAI 2024. [Paper]
MDGNN: Multi-Relational Dynamic Graph Neural Network for Comprehensive and Dynamic Stock Investment Prediction
Hao Qian, Hongting Zhou, Qian Zhao, Hao Chen, Hongxiang Yao, Jingwei Wang, Ziqi Liu, Fei Yu, Zhiqiang Zhang, Jun Zhou
AAAI 2024. [Paper]
ECHO-GL: Earnings Calls-Driven Heterogeneous Graph Learning for Stock Movement Prediction
Mengpu Liu, Mengying Zhu, Xiuyuan Wang, Guofang Ma, Jianwei Yin, Xiaolin Zheng
AAAI 2024. [Paper] | [Codes]
TCGPN: Temporal-Correlation Graph Pre-trained Network for Stock Forecasting
Wenbo Yan, Ying Tan
[Paper]
Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction
Sheng Xiang, Dawei Cheng, Chencheng Shang, Ying Zhang, Yuqi Liang
CIKM 2022. [Paper] | [Codes]
Relational Temporal Graph Convolutional Networks for Ranking-Based Stock Prediction
Zetao Zheng, Jie Shao, Jia Zhu, Heng Tao Shen
ICDE 2023. [Paper] | [Codes]
Temporal-Relational hypergraph tri-Attention networks for stock trend prediction
Chaoran Cui, Xiaojie Li, Chunyun Zhang, Weili Guan, Meng Wang
Pattern Recognition 2023. [Paper] | [Codes]
Financial time series forecasting with multi-modality graph neural network
Dawei Cheng, Fangzhou Yang, Sheng Xiang, Jin Liu
Pattern Recognition 2022. [Paper] | [Codes]
Hierarchical Adaptive Temporal-Relational Modeling for Stock Trend Prediction
Heyuan Wang, Shun Li, Tengjiao Wang, Jiayi Zheng
IJCAI 2021. [Paper] | [Codes]
REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
WWW 2021. [Paper]
Knowledge Graph-based Event Embedding Framework for Financial Quantitative Investments
Dawei Cheng, Fangzhou Yang, Xiaoyang Wang, Ying Zhang, Liqing Zhang
SIGIR 2020. [Paper]
MacMic: Executing Iceberg Orders via Hierarchical Reinforcement Learning
Hui Niu, Siyuan Li, Jian Li
IJCAI 2024. [Paper]
Cross-contextual Sequential Optimization via Deep Reinforcement Learning for Algorithmic Trading
Kaiming Pan, Yifan Hu, Li Han, Haoyu Sun, Dawei Cheng, Yuqi Liang
CIKM 2024. [Paper]
Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools
Wentao Zhang, Yilei Zhao, Shuo Sun, Jie Ying, Yonggang Xie, Zitao Song, Xinrun Wang, Bo An
WWW 2024. [Paper] | [Codes]
FreQuant: A Reinforcement-Learning based Adaptive Portfolio Optimization with Multi-frequency Decomposition
Jeon, Jihyeong and Park, Jiwon and Park, Chanhee and Kang, U
KDD 2024. [Paper]
MacroHFT: Memory Augmented Context-aware Reinforcement Learning On High Frequency Trading
Chuqiao Zong, Chaojie Wang, Molei Qin, Lei Feng, Xinrun Wang, Bo An
KDD 2024. [Paper] | [Codes]
Asymmetric Graph-Based Deep Reinforcement Learning for Portfolio Optimization
Haoyu Sun, Xin Liu, Yuxuan Bian, Peng Zhu, Dawei Cheng, Yuqi Liang
ECML PKDD 2024. [Paper]
NGDRL: A Dynamic News Graph-Based Deep Reinforcement Learning Framework for Portfolio Optimization
Yuxuan Bian, Haoyu Sun, Yang Lei, Peng Zhu, Dawei Cheng
DASFAA 2024. [Paper]
Efficient Continuous Space Policy Optimization for High-frequency Trading
Li Han, Nan Ding, Guoxuan Wang, Dawei Cheng, Yuqi Liang
KDD 2023. [Paper]
Optimal Action Space Search: An Effective Deep Reinforcement Learning Method for Algorithmic Trading
Zhongjie Duan, Cen Chen, Dawei Cheng, Yuqi Liang, Weining Qian
CIKM 2022. [Paper] | [Codes]
MASTER: Market-Guided Stock Transformer for Stock Price Forecasting
Tong Li, Zhaoyang Liu, Yanyan Shen, Xue Wang, Haokun Chen, Sen Huang
AAAI 2024. [Paper] | [Codes]
CI-STHPAN: Pre-trained Attention Network for Stock Selection with Channel-Independent Spatio-Temporal Hypergraph
Hongjie Xia, Huijie Ao, Long Li, Yu Liu, Sen Liu, Guangnan Ye, Hongfeng Chai
AAAI 2024. [Paper] | [Codes]
Predicting stock market trends with self-supervised learning
Zelin Ying, Dawei Cheng, Cen Chen, Xiang Li, Peng Zhu, Yifeng Luo, Yuqi Liang
Neurocomputing 2024. [Paper]
Multi-scale Time Based Stock Appreciation Ranking Prediction via Price Co-movement Discrimination
Ruyao Xu, Dawei Cheng, Cen Chen, Siqiang Luo, Yifeng Luo, Weining Qian
DASFAA 2022. [Paper] | [Codes]
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021. [Paper] | [Codes]
Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts
Yoo, Jaemin and Soun, Yejun and Park, Yong-chan and Kang, U
KDD 2021. [Paper] | [Codes]
Market-GAN: Adding Control to Financial Market Data Generation with Semantic Context
Haochong Xia, Shuo Sun, Xinrun Wang, Bo An
AAAI 2024. [Paper] | [Codes]
RSAP-DFM: Regime-Shifting Adaptive Posterior Dynamic Factor Model for Stock Returns Prediction
Quanzhou Xiang, Zhan Chen, Qi Sun, Rujun Jiang
IJCAI 2024. [Paper]
Automatic De-Biased Temporal-Relational Modeling for Stock Investment Recommendation
Weijun Chen, Shun Li, Xipu Yu, Heyuan Wang, Wei Chen, Tengjiao Wang
IJCAI 2024. [Paper]
GENERATIVE LEARNING FOR FINANCIAL TIME SERIES WITH IRREGULAR AND SCALE-INVARIANT PATTERNS
Hongbin Huang, Minghua Chen, and Xiao Qiao
ICLR 2024. [Paper]
DiffsFormer: A Diffusion Transformer on Stock Factor Augmentation
Yuan Gao, Haokun Chen, Xiang Wang, Zhicai Wang, Xue Wang, Jinyang Gao, Bolin Ding
FactorVAE: A Probabilistic Dynamic Factor Model Based on Variational Autoencoder for Predicting Cross-Sectional Stock Returns
Yitong Duan, Lei Wang, Qizhong Zhang, Jian Li
AAAI 2022. [Paper] | [Codes]
Learning connections in financial time series
Ganeshapillai, Gartheeban, John Guttag, and Andrew Lo.
ICML 2013. [Paper] | [Codes]
RD-Agent: Autonomous evolving agents for industrial data-drive R&D
Microsoft Research Asia
Qlib: An AI-oriented Quantitative Investment Platform
Microsoft Research Asia
Large Language Model Agent in Financial Trading: A Survey
Han Ding, Yinheng Li, Junhao Wang, Hang Chen
Stock Market Prediction via Deep Learning Techniques: A Survey
Jinan Zou, Qingying Zhao, Yang Jiao, Haiyao Cao, Yanxi Liu, Qingsen Yan, Ehsan Abbasnejad, Lingqiao Liu, Javen Qinfeng Shi