Curated list of LLM-driven trading agents, MCP servers, and agent skills for market research, strategy, and execution.
🔥[NeurIPS'25] DeepFund: Pilot for Your Next Fund Investment
Production-grade multimodal RAG for financial document intelligence. Chart understanding · hybrid retrieval · numeric guardrails · multi-tenancy · full observability.
[NeurIPS 2025] A multi-agent framework that leverages LLMs to simulate socio-economic systems
💹 StockSim: Multi-Agent LLM Financial Market Simulator — A realistic trading simulation platform for evaluating large language models in dynamic financial environments.
📈 Kronos Chinese Guide | Financial K-Line Foundation Model | A 股 K 线预测中文实战指南 — 数据获取 · 预测实战 · 微调教程 · 回测集成 | AAAI 2026 | Zero-shot RankIC +93%
Marketplace of domain-specific plugins for AI agents (Cowork, Claude Code, OpenClaw). Build autonomous business workflows for finance, banking, legal operations, and sales using modular agent skills and commands.
This repository provides implementation of EDiffusion-QL: a diffusion-based reinforcement learning framework for multimodal stock trading.
Simple Finance Forecasting Ai. This Ai Model uses historical price data to forecast future prices. The model is trained on data downloaded from Yahoo Finance using the yfinance library, and predictions are made using a linear regression Ai model from sklearn. The model supports all the symbols supported by Yahoo Finance.
PHD Research Focus
RL Forex Bot with PPO AI-powered trading bot using PPO, dynamic position sizing, AMD GPU acceleration (DirectML/OpenCL), and MetaTrader 5 integration.
K.I.T. - Knight Industries Trading: Autonomous AI Agent Framework for Financial Markets. Full autopilot trading across Crypto, Forex, Stocks, ETFs, DeFi.
Production-ready RLAIF trading system with multi-agent Claude AI that learns from market outcomes. Features 60+ indicators, foundation models, and serverless deployment.
Open-source, evidence-first financial research platform. Local Llama 3.1 70B via Ollama; signals trace to verifiable SEC filings and are hash-anchored in a public verification ledger. Research and education only — not investment advice. MIT.
RL reward modeling + episodic trade memory + LoRA fine-tuning pipeline built on top of a multi-agent LLM trading system — LangGraph, LangChain, PEFT
Multi-agent LLM trading framework: hard-discipline (code) + soft-judgment (LLM) hybrid. Best risk-adjusted performance on NVDA 6-month benchmark — +43.9% / -3.2% MDD, beating RSI, Momentum, Buy & Hold, and single-agent LLM. Raw returns top all baselines once the position cap is lifted. Adapted from TauricResearch/TradingAgents, built on LangGraph.
A股量化智能体 - 10个AI分析师协同决策，LangGraph多智能体工作流，本地模型零成本运行
Agent-native pipeline for converting multimodal financial KOL timelines into evidence-linked investment intents, trade actions, and backtestable performance.
End-to-End Python implementation of CompactPrompt (Choi et al., 2025): a unified pipeline for LLM prompt and data compression. Features modular compression pipeline with dependency-driven phrase pruning, reversible n-gram encoding, K-means quantization, and embedding-based exemplar selection. Achieves 2-4x token reduction while preserving accuracy.
GDSC Solution Challenge - Innovatrix
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