5 papers
AlphaEval: A Comprehensive and Efficient Evaluation Framework for Formula Alpha Mining
Hongjun Ding, Binqi Chen, Jinsheng Huang +6
Formula alpha mining, which generates predictive signals from financial data, is critical for quantitative investment. Although various algorithmic approaches-such as genetic progr…
AlphaSAGE: Structure-Aware Alpha Mining via GFlowNets for Robust Exploration
Binqi Chen, Hongjun Ding, Ning Shen +4
The automated mining of predictive signals, or alphas, is a central challenge in quantitative finance. While Reinforcement Learning (RL) has emerged as a promising paradigm for gen…
MEME: Modeling the Evolutionary Modes of Financial Markets
Taian Guo, Haiyang Shen, Junyu Luo +7
LLMs have demonstrated significant potential in quantitative finance by processing vast unstructured data to emulate human-like analytical workflows. However, current LLM-based met…
AlphaPROBE: Alpha Mining via Principled Retrieval and On-graph biased evolution
Taian Guo, Haiyang Shen, Junyu Luo +6
Extracting signals through alpha factor mining is a fundamental challenge in quantitative finance. Existing automated methods primarily follow two paradigms: Decoupled Factor Gener…
Large Language Model Agent: A Survey on Methodology, Applications and Challenges
Junyu Luo, Weizhi Zhang, Ye Yuan +23
The era of intelligent agents is upon us, driven by revolutionary advancements in large language models. Large Language Model (LLM) agents, with goal-driven behaviors and dynamic a…