mlsanityData to 7 Oct 2026

QuantAgent: Seeking Holy Grail in Trading by Self-Improving Large Language Model

arXiv 2402.03755 ↗First posted 6 Feb 2024cs.AI q-fin.CPcited by 30

On the map: Synthetic data and self-improvement for LLMs → Self-evolving LLM agents

Abstract (arXiv)

Autonomous agents based on Large Language Models (LLMs) that devise plans and tackle real-world challenges have gained prominence.However, tailoring these agents for specialized domains like quantitative investment remains a formidable task. The core challenge involves efficiently building and integrating a domain-specific knowledge base for the agent's learning process. This paper introduces a principled framework to address this challenge, comprising a two-layer loop.In the inner loop, the agent refines its responses by drawing from its knowledge base, while in the outer loop, these responses are tested in real-world scenarios to automatically enhance the knowledge base with new insights.We demonstrate that our approach enables the agent to progressively approximate optimal behavior with provable efficiency.Furthermore, we instantiate this framework through an autonomous agent for mining trading signals named QuantAgent. Empirical results showcase QuantAgent's capability in uncovering viable financial signals and enhancing the accuracy of financial forecasts.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Placed in Self-evolving LLM agents, one of 13 directions in Synthetic data and self-improvement for LLMs. Builds on 13 of its 24 references that are in the map. First posted on arXiv 6 Feb 2024.

Builds on

13 of 24 references.

References · 13

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  3. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
  4. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
  5. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,317
  6. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  7. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
  8. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
  9. 2021An Explanation of In-context Learning as Implicit Bayesian Inferencecited by 915
  10. 2020Is Pessimism Provably Efficient for Offline RL?cited by 362
  11. 2022Language Models Can Teach Themselves to Program Bettercited by 75
  12. 2023Alpha-GPT: Human-AI Interactive Alpha Mining for Quantitative Investmentcited by 54
1 more
  1. 2023A Principled Framework for Knowledge-enhanced Large Language Modelcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 16; 2026: 10.

30 papers.

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  1. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 622
  2. 2024TradingAgents: Multi-Agents LLM Financial Trading Frameworkcited by 182
  3. 2025A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligencecited by 155
  4. 2024A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challengescited by 86
  5. 2025Fin-R1: A Large Language Model for Financial Reasoning through Reinforcement Learningcited by 82
  6. 2026A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agentscited by 40
  7. 2025LLM-Powered AI Agent Systems and Their Applications in Industrycited by 22
  8. 2025Time Travel is Cheating: Going Live with DeepFund for Real-Time Fund Investment Benchmarkingcited by 21
  9. 2025Navigating the Alpha Jungle: An LLM-Powered MCTS Framework for Formulaic Factor Miningcited by 13
  10. 2025Profit Mirage: Revisiting Information Leakage in LLM-based Financial Agentscited by 13
  11. 2025Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crewscited by 12
  12. 2024AI in Investment Analysis: LLMs for Equity Stock Ratingscited by 10
18 more
  1. 2025ContestTrade: A Multi-Agent Trading System Based on Internal Contest Mechanismcited by 8
  2. 2026Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Applicationcited by 8
  3. 2025Exposing Product Bias in LLM Investment Recommendationcited by 6
  4. 2025Agentar-Fin-R1: Enhancing Financial Intelligence through Domain Expertise, Training Efficiency, and Advanced Reasoningcited by 5
  5. 2025Will LLMs be Professional at Fund Investment? DeepFund: A Live Arena Perspectivecited by 4
  6. 2025Bridging Language Models and Financial Analysiscited by 4
  7. 2025Trade in Minutes! Rationality-Driven Agentic System for Quantitative Financial Tradingcited by 4
  8. 2026From Feedback Loops to Policy Updates: Reinforcement Fine-Tuning for LLM-Based Alpha Factor Discoverycited by 4
  9. 2025Language Model Guided Reinforcement Learning in Quantitative Tradingcited by 3
  10. 2026Moira: Language-driven Hierarchical Reinforcement Learning for Pair Tradingcited by 1
  11. 2026AlphaCrafter: Harnessing Multi-Agent Workflows for Cross-Sectional Quantitative Tradingcited by 1
  12. 2026Agent Bazaar: Enabling Economic Alignment in Multi-Agent Marketplacescited by 1
  13. 2025Market-Dependent Communication in Multi-Agent Alpha Generationcited by 0
  14. 2025Orchestration Framework for Financial Agents: From Algorithmic Trading to Agentic Tradingcited by 0
  15. 2026WebCryptoAgent: Agentic Crypto Trading with Web Informaticscited by 0
  16. 2026BizFinBench.v2: Towards Reliable LLMs in Finance via Real-User Data and Offline/Online Bilingual Evaluationcited by 0
  17. 2026Beyond Agent Architecture: Execution Assumptions and Reproducibility in LLM-Based Trading Systemscited by 0
  18. 2026FaVOR: LLM-Based Agentic Framework for Factor Mining via Empirical Validationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Learning to Trade Like an Expert: Cognitive Fine-Tuning for Stable Financial Reasoning in Language Models
  2. 2026QuantCode-Bench: A Benchmark for Evaluating the Ability of Large Language Models to Generate Executable Algorithmic Trading Strategies
  3. 2025QuantAgents: Towards Multi-agent Financial System via Simulated Trading
  4. 2026OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents
  5. 2025Agent Trading Arena: A Study on Numerical Understanding in LLM-Based Agents
  6. 2026QuantEval: A Benchmark for Financial Quantitative Tasks in Large Language Models
  7. 2026AQuA: Recursively Self-Improving Quantitative Trading Research Agents
  8. 2024Simulating Financial Market via Large Language Model based Agents