mlsanityData to 14 Oct 2026

QRAFTI: An Agentic Framework for Empirical Research in Quantitative Finance

arXiv 2604.18500 ↗First posted 20 Apr 2026cs.MA q-fin.GNcited by 2

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

We introduce a multi-agent framework intended to emulate parts of a quantitative research team and support equity factor research on large financial panel datasets. QRAFTI integrates a research toolkit for panel data with MCP servers that expose data access, factor construction, and custom coding operations as callable tools. It can help replicate established factors, formulate and test new signals, and generate standardized research reports accompanied by narrative analysis and computational traces. On multi-step empirical tasks, using chained tool calls and reflection-based planning may offer better performance and explainability than dynamic code generation alone.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 12 of its 57 references that are in the map. First posted on arXiv 20 Apr 2026.

Builds on

12 of 57 references.

References · 12

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  2. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,276
  3. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  4. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,455
  5. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
  6. 2023BloombergGPT: A Large Language Model for Financecited by 939
  7. 2025LLMs Get Lost In Multi-Turn Conversationcited by 429
  8. 2023Auto-GPT for Online Decision Making: Benchmarks and Additional Opinionscited by 255
  9. 2019SPoC: Search-based Pseudocode to Codecited by 176
  10. 2024Empowering Biomedical Discovery with AI Agentscited by 118
  11. 2024A Survey of Large Language Models in Finance (FinLLMs)cited by 79
  12. 2024Self-Reflection Makes Large Language Models Safer, Less Biased, and Ideologically Neutralcited by 20

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Beyond Agent Architecture: Execution Assumptions and Reproducibility in LLM-Based Trading Systemscited by 0
  2. 2026Agentic Empirical Asset Pricing: Methodological Foundationscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
  2. 2026FaVOR: LLM-Based Agentic Framework for Factor Mining via Empirical Validation
  3. 2026AlphaCrafter: Harnessing Multi-Agent Workflows for Cross-Sectional Quantitative Trading
  4. 2026OpenFinGym: A Verifiable Multi-Task Gym Environment for Evaluating Quant Agents
  5. 2026AI Economist Agent: An Agentic Framework for Evidence-Based Economic and Financial Analysis with RAG, Knowledge Graphs, and Large Language Models
  6. 2026FinDeepForecast: A Live Multi-Agent System for Benchmarking Deep Research Agents in Financial Forecasting
  7. 2025FinResearchBench: A Logic Tree based Agent-as-a-Judge Evaluation Framework for Financial Research Agents
  8. 2026FinDeepIndicator: Benchmarking Deep Research Agents in End-to-End Financial Indicator Construction