ai-agent

awesome-quant-ai: AI‑Driven Resources for Quantitative Finance

Name: awesome-quant-ai: AI‑Driven Resources for Quantitative Finance
Author: leoncuhk

A founder seeking cutting‑edge quant strategies gets a hand‑picked list of AI and ML tools for finance. Ideal for startups building algorithmic trading products.

625 stars129 forksJupyter NotebookGuide quality 8/10 · reviewed Oct 11Updated 9/27/2026100% free · open source

What it does

Awesome-quant-ai provides a curated list of resources for quantitative investment and trading strategies using artificial intelligence and machine learning in finance.

When to use it

•When looking for inspiration or references for building AI-powered trading strategies
•When seeking to learn from existing quantitative finance projects using AI and ML
•When searching for a community-driven collection of resources on AI applications in finance

Ready-to-paste prompt

Search for 'AI-powered trading strategies' in the repository to find relevant resources, using the command `grep -r 'AI-powered trading strategies' .`

Heads up: Note that some resources listed may require specific programming languages or libraries, such as Python or TensorFlow, so ensure you have the necessary dependencies installed before exploring

Saves to your device

Use with Claude

New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

⚡ Runs out of the box

A prompt/skill package — nothing to install beyond adding it to your AI tool.

Try it instantly — no install

Claude Code

mkdir -p ~/.claude/skills/awesome-quant-ai && curl -fsSL https://workflowstacks.com/api/skills/awesome-quant-ai/claude-skill -o ~/.claude/skills/awesome-quant-ai/SKILL.md

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How awesome-quant-ai: AI‑Driven Resources for Quantitative Finance works

Codeflow

Free to inspect

Awesome-quant-ai: AI‑Driven Resources for Quantitative Finance is a documents-only repository (22 doc files) — something you read, not something you run. There is nothing to install. Last commit a month ago, Apache-2.0 license.

Size

Documents only

22 documents · ~2 h to skim

Setup

Nothing to install

A course / notebook collection. Read it; run cells if you like.

Runs on

Nowhere — you read it

A reading resource, not a program.

Jupyter Notebook 100%

Where to start reading

1
README.md
Start here — what it does and how to install it
2
CLAUDE.md
The instructions the AI actually follows

What's in each folder

book/Folder13 files

think/Folder5 files

paper/Research & notebooks2 files

tools/Helper scripts1 files

assets/Images & static assets4 files

.github/CI / automation (GitHub Actions)2 files

READMEDocumentedCI checksApache-2.0 licenseUpdated this month

Use with Claude

New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

⚡ Runs out of the box

A prompt/skill package — nothing to install beyond adding it to your AI tool.

Try it instantly — no install

Claude Code

mkdir -p ~/.claude/skills/awesome-quant-ai && curl -fsSL https://workflowstacks.com/api/skills/awesome-quant-ai/claude-skill -o ~/.claude/skills/awesome-quant-ai/SKILL.md

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

Quick Actions

Details

Creator

leoncuhk

Language

Jupyter Notebook

Do this with a working workflow

Pages we wrote and tested that put a skill like this to work — importable n8n templates, outcome guides and Claude Desktop configs.

Outcome guide

Score your leads by ideal-customer fit

You describe your ideal customer once and keep leads in a Google Sheet. The workflow scores each 1–5 for fit with a one-line reason, so you sort and work the best first.