ai-agent

ai_quant_trade: AI Trading

Get AI-powered trading strategies with ai_quant_trade., 6.0k+ GitHub stars, a one-stop platform for learning, simulating, and live trading.
6,503 stars1,221 forksJupyter NotebookGuide quality 8/10Updated 9/6/2026100% free · open source
What it does

Ai_quant_trade is a one-stop platform for learning, simulating, and executing stock trading strategies using AI, including traditional strategies, machine learning, and deep learning.

When to use it
  • When you need to automate stock trading decisions with data-driven insights
  • When you want to experiment with different trading strategies and models
  • When you need to deploy and execute trading strategies in a production-ready environment
Ready-to-paste prompt
Run the `traditional_strategy.ipynb` example with a specific stock symbol: `python traditional_strategy.py --stock-symbol AAPL`
Heads up: Make sure you have the necessary dependencies installed, including `pandas`, `numpy`, and `jupyter`, and that you have a compatible version of Python (3.8 or later) to run the Jupyter Notebook
Saves to your device
Use with Claude
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Claude Code
mkdir -p ~/.claude/skills/ai-quant-trade && curl -fsSL https://workflowstacks.com/api/skills/ai-quant-trade/claude-skill -o ~/.claude/skills/ai-quant-trade/SKILL.md
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Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

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What's inside — free to inspect

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15
top-level files
21
folders
86.5M
source size
Apache-2.0
license
Key files
.pre-commit-config.yaml
README_EN.md
README.md
requirements.txt
File tree
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ai_notes/
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docs/
egs_aide/
egs_alpha/
egs_courses/
egs_data/
egs_fin_nlp/
egs_llm/
egs_online_platform/
egs_skill/
egs_trade/
quant_brain/
runtime/
src/
tools/
unit_test/
.clang-format
.flake8
.gitignore
Quick Actions
Details
Creator
charliedream1
Language
Jupyter Notebook
Category
ai-agent
Published
6/9/2022

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