Fetching the paper…
Reading the bibliography…
Alpha mining, a critical component in quantitative investment, focuses on discovering predictive signals for future asset returns in increasingly complex financial markets.
When do systematic strategies decay?
Antoine Falck, Adam Rej, and David Thesmar. 2022 · 1969
Earlier work this paper cites.
The cross-section of expected stock returns
Eugene F Fama and Kenneth R French. 1992 · 1992
Earlier work this paper cites.
Tianping Zhang, Yuanqi Li, Yifei Jin, and Jian Li. 2020 · 2002
Earlier work this paper cites.
Mathematical statistics and data analysis . Vol. 371
John A Rice and John A Rice. 2007 · 2007
Earlier work this paper cites.
Qlib: An AI-oriented Quantitative Investment Platform
Xiao Yang, Weiqing Liu, Dong Zhou, Jiang Bian, and Tie-Yan Liu. 2020 · 2009
Earlier work this paper cites.
Age-fitness pareto optimization. In Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation (Portland, Oregon, USA) (GECCO ’10) . Association for Computing Machinery, New York, NY, USA, 543–544
Michael D. Schmidt and Hod Lipson. 2010 · 2010
Earlier work this paper cites.
Training language models to follow instructions with human feedback. In Proceedings of the 36th International Conference on Neural Information Processing Systems (New Orleans, LA, USA) (NIPS ’22) . Curran Associates Inc., Red Hook, NY, USA, Article 2011, 15 pages
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, and Carroll L. et al. Wainwright. 2022 · 2011
Earlier work this paper cites.
The relative strength index revisited
Adrian Ţăran-Moroşan. 2011 · 2011
Earlier work this paper cites.
Long short-term memory
Alex Graves and Alex Graves. 2012 · 2012
Earlier work this paper cites.
Value and momentum everywhere
Clifford S Asness, Tobias J Moskowitz, and Lasse Heje Pedersen. 2013 · 2013
Earlier work this paper cites.
Zura Kakushadze. 2016 · 2016
Earlier work this paper cites.
LightGBM: A Highly Efficient Gradient Boosting Decision Tree. In Advances in Neural Information Processing Systems , Vol. 30. Curran Associates, Inc
Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, and Tie-Yan Liu. 2017 · 2017
Earlier work this paper cites.
Proximal Policy Optimization Algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
Earlier work this paper cites.
Attention is all you need. In Proceedings of the 31st International Conference on Neural Information Processing Systems (Long Beach, California, USA) (NIPS’17) . Curran Associates Inc., Red Hook, NY, USA, 6000–6010
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Revisiting Stock Alpha Mining Based On Genetic Algorithm
X. Lin, Y. Chen, Z. Li, and K. He. 2019 · 2019
Earlier work this paper cites.
AlphaEvolve: A Learning Framework to Discover Novel Alphas in Quantitative Investment. In Proceedings of the 2021 International Conference on Management of Data (Virtual Event, China) (SIGMOD ’21) . ACM, New York, NY, USA, 2208–2216
Can Cui, Wei Wang, Meihui Zhang, Gang Chen, Zhaojing Luo, and Beng Chin Ooi. 2021 · 2021
Cited alongside, same era.
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD ’21) . ACM
Hengxu Lin, Dong Zhou, Weiqing Liu, and Jiang Bian. 2021 · 2021
Cited alongside, same era.
FinRL: deep reinforcement learning framework to automate trading in quantitative finance. In Proceedings of the Second ACM International Conference on AI in Finance (Virtual Event) (ICAIF ’21) . Association for Computing Machinery, New York, NY, USA, Article 1, 9 pages
Xiao-Yang Liu, Hongyang Yang, Jiechao Gao, and Christina Dan Wang. 2022 · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
On the creativity of large language models
Giovanni Franceschelli and Mirco Musolesi. 2024 · 2024
Later among the works it cites.
Can Large Language Models Unlock Novel Scientific Research Ideas?
Sandeep Kumar, Tirthankar Ghosal, Vinayak Goyal, and Asif Ekbal. 2024 · 2024
Later among the works it cites.
Can Large Language Models Mine Interpretable Financial Factors More Effectively? A Neural-Symbolic Factor Mining Agent Model. In Findings of the Association for Computational Linguistics: ACL 2024 , Lun-Wei Ku, Andre Martins, and Vivek Srikumar (Eds.). Association for Computational Linguistics, Bangkok, Thailand, 3891–3902
Zhiwei Li, Ran Song, Caihong Sun, Wei Xu, Zhengtao Yu, and Ji-Rong Wen. 2024 · 2024
Later among the works it cites.
AlphaForge: A Framework to Mine and Dynamically Combine Formulaic Alpha Factors
Hao Shi, Weili Song, Xinting Zhang, Jiahe Shi, Cuicui Luo, Xiang Ao, Hamid Arian, and Luis Seco. 2024 · 2024
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Genetic algorithm based quantitative factors construction. In 2022 IEEE 20th International Conference on Industrial Informatics (INDIN) . IEEE, 650–655
Su Zhaofan, Lin Jianwu, and Zhang Chengshan. 2022 · 2022
Cited alongside, same era.
Language Models Can Teach Themselves to Program Better. In The Eleventh International Conference on Learning Representations
Patrick Haluptzok, Matthew Bowers, and Adam Tauman Kalai. 2023 · 2023
Cited alongside, same era.
AI-Infused algorithmic trading: genetic algorithms and machine learning in high-frequency trading
RR Patil. 2023 · 2023
Cited alongside, same era.
Mining profitable alpha factors via convolution kernel learning
Zhenyi Shen, Xiahong Mao, Xiaohu Yang, and Dan Zhao. 2023 · 2023
Cited alongside, same era.
Aligning Large Language Models with Human: A Survey
Yufei Wang, Wanjun Zhong, Liangyou Li, Fei Mi, Xingshan Zeng, Wenyong Huang, Lifeng Shang, Xin Jiang, and Qun Liu. 2023 · 2023
Cited alongside, same era.
LLM-powered Autonomous Agents
Lilian Weng. 2023 · 2023
Cited alongside, same era.
Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (Long Beach, CA, USA) (KDD ’23) . Association for Computing Machinery, New York, NY, USA, 5476–5486
Shuo Yu, Hongyan Xue, Xiang Ao, Feiyang Pan, Jia He, Dandan Tu, and Qing He. 2023 · 2023
Cited alongside, same era.
Towards Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Wenjun Feng, Haoxue Wang, Xiao Yang, Xu Yang, Weiqing Liu, and Jiang Bian. 2024 · 2024
Cited alongside, same era.
Theodore R. Sumers, Shunyu Yao, Karthik Narasimhan, and Thomas L. Griffiths. 2024 · 2024
Later among the works it cites.
Ziyi Tang, Ruilin Wang, Weixing Chen, Keze Wang, Yang Liu, Tianshui Chen, and Liang Lin. 2024 · 2024
Later among the works it cites.
LLMFactor: Extracting Profitable Factors through Prompts for Explainable Stock Movement Prediction
Meiyun Wang, Kiyoshi Izumi, and Hiroki Sakaji. 2024 · 2024
Later among the works it cites.
China A-shares Q1 2024 Factor Review
Phillip Wool. 2024 · 2024
Later among the works it cites.
Collaborative Evolving Strategy for Automatic Data-Centric Development
Xu Yang, Haotian Chen, Wenjun Feng, Haoxue Wang, Zeqi Ye, Xinjie Shen, Xiao Yang, Shizhao Sun, Weiqing Liu, and Jiang Bian. 2024 · 2024
Later among the works it cites.
QuantFactor REINFORCE: Mining Steady Formulaic Alpha Factors with Variance-bounded REINFORCE
Junjie Zhao, Chengxi Zhang, Min Qin, and Peng Yang. 2024 · 2024
Later among the works it cites.
yfinance: Download market data from Yahoo! Finance’s API
Ran Aroussi. 2024 · 2025
Closest in time.
A tool for obtaining historical data of China stock market
BaoStock. 2024 · 2025
Closest in time.
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
DeepSeek-AI, Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, and Ruoyu Zhang et al. 2025 · 2025
Closest in time.
Qwen, An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, and Bo Zheng et al. 2025 · 2025
Closest in time.