We are LLMQuant, an open-source community focusing on AI, LLM (large language model) and Quantitative Finance. We aim to leverage AI to investment research with feasible collection of techniques and solutions.
Join the community and explore the latest AI use case in quantitative research with us, you will receive the event updates and access our best AI4Quant solutions.
You can contribute to our community by sharing your use case of AI in quantitative finance. We strongly appreciate the code contribution to our github project repositories.
Apply our best AI4Quant solutions in production environment, which are verified by experienced quantiative researchers and AI experts.
Structured, AI-readable financial data for LLMs.
Our flagship infrastructure project transforms how large language models consume and understand financial information.
We clean, tag, and structure financial documents such as earnings reports, filings, M&A news, and macro data into LLM-optimized formats.
Highlights:
• Real-time and historical data APIs
• Metadata-rich parsing of SEC filings, headlines, transcripts
• RAG-ready formats for chat agents and custom LLMs
• On-premise or cloud enterprise deployment
Open-source quantitative investment knowledge.
Quant-Wiki.com is our community-driven resource library of strategies, tools, and research insights. It bridges the gap between academic theory and real-world quant practices.
Highlights:
• Strategy code libraries and tutorials
• Glossaries, whitepaper reviews, and market analysis
• Open access and community contributions
• Ideal for learners, researchers, and practitioners
An intelligent knowledge extraction and retrieval framework for quantitative finance.
QuantMind is a next-generation AI platform that ingests, processes, and structures every new piece of quantitative-finance research, including papers, news, blogs, and SEC filings into a semantic knowledge graph. Institutional investors, hedge funds, and research teams can now explore the frontier of factor strategies, risk models, and market insights in seconds, unlocking alpha that would otherwise remain buried..
The Opportunity:
• Information Overload: 500 new research papers & reports published daily. Manual review takes weeks—costly, error-prone, and non-scalable
• Massive Market: Financial data & analytics market ≫ expected to grow to US$961.89 billion by 2032, with a compound annual growth rate of 13.5%. Tens of thousands of quant teams & asset managers hungry for speed
• High ROI: 1% improvement in research efficiency can translate to millions saved or earned in trading performance
Industrial-Grade Multi-Agent Based Framework for Alpha Research in Quantitative Investment.
AlphaAgent is a practical and adaptive multi-agent framework for real-world quantitative research and development. Built upon the principles of RD-Agent(Q), it emphasizes production-grade alpha discovery, market-aware modeling, and automated deployment, leveraging live data streams, evolving knowledge bases, and robust backtesting infrastructure.
Highlights:
• Continuous mining and curation of high-value factor/model ideas from domain knowledge sources
• Dynamic retrieval of strategies that align with real-time market characteristics
• Self-refinement of hypotheses using prior experiments and contextual relevance
• Automatic research documentation and decision support outputs for industrial use
Next-gen AI trading simulation and backtesting platform.
Magents.ai allows LLM-native strategy testing using natural language or Python, simulating complex market environments with multi-agent interactions.
Highlights:
• Event-driven and LLM-defined trading logic
• Modular backtesting environments with latency/slippage
• Supports stocks, crypto, and derivatives
• Designed for researchers, funds, and algo developers
AI-assisted research with agents and financial experts.
MarketPulse enables intelligent alpha discovery via co-piloted workflows between humans and AI. From macro analysis to earnings summaries, it bridges insight with automation.
Highlights:
• AI agents summarize, monitor, and analyze markets
• Merger arb and event-driven monitoring tools
• Co-published research dashboards
• Deep insights for hedge funds and analysts
