#1
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
20K starsJun 1, 2026 pushfinanceJupyter NotebookFinance
$ npx skills add AI4Finance-Foundation/FinGPTAlternatives
Factor Research alternatives for AI agents.
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
Factor Research
Advanced Quantitative Factor Research: ML-powered stock return prediction with 72% performance improvement. Features comprehensive alpha factor library, systematic feature selection, and deep learning models (LSTM+ResNet achieving IC=0.06476).
60
Quality
77
Trust
406
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#2
Code for Machine Learning for Algorithmic Trading, 2nd edition.
19K starsJun 12, 2026 pushfinanceJupyter NotebookFinance
$ npx skills add stefan-jansen/machine-learning-for-trading#3
[🔥updating ...] AI 自动量化交易机器人(完全本地部署) AI-powered Quantitative Investment Research Platform. 📃 online docs: https://ufund-me.github.io/Qbot ✨ :news: qbot-mini: https://github.com/Charmve/iQuant
18K starsMar 11, 2026 pushfinanceJupyter NotebookFinance
$ npx skills add UFund-Me/Qbot#4
Hikyuu Quant Framework 基于C++/Python的超高速开源量化交易研究框架，同时可基于策略部件进行资产重用，快速累积策略资产。
3.3K starsJun 13, 2026 pushfinanceC++Backtesting
$ npx skills add fasiondog/hikyuu#5
Python Backtesting library for trading strategies
22K starsAug 19, 2024 pushfinancePythonBacktesting
$ npx skills add mementum/backtrader#6
Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting
680 starsDec 28, 2025 pushfinanceJupyter NotebookFinance
$ npx skills add JordiCorbilla/stock-prediction-deep-neural-learning#7
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
44K starsApr 22, 2026 pushfinancePythonFinance
$ npx skills add microsoft/qlib#8
Roboquant is a fast, flexible, user-friendly and completely free algorithmic trading platform
457 starsJan 2, 2026 pushfinanceJavaScriptBacktesting
$ npx skills add neurallayer/roboquant#9
📈This repo contains detailed notes and multiple projects implemented in Python related to AI and Finance. Follow the blog here: https://purvasingh.medium.com
405 starsDec 25, 2020 pushfinanceJupyter NotebookBacktesting
$ npx skills add purvasingh96/AI-for-Trading#10
The backtesting engine that gives you an unfair advantage. Run thousands of trading ideas before others finish one.
7.9K starsJun 10, 2026 pushfinancePythonFinance
$ npx skills add polakowo/vectorbt#11
中国的Quant相关资源索引
5.4K starsMay 17, 2026 pushfinanceQuantClaude Code
$ npx skills add thuquant/awesome-quant#12
modular quant framework.
4.2K starsApr 13, 2026 pushfinancePythonFinance
$ npx skills add zvtvz/zvt#13
FinRobot: An Open-Source AI Agent Platform for Financial Analysis using LLMs 🚀 🚀 🚀
7.3K starsMay 10, 2026 pushfinanceJupyter NotebookFinance
$ npx skills add AI4Finance-Foundation/FinRobot#14
TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning :fire: :zap: :rainbow:
2.8K starsJun 4, 2025 pushfinanceJupyter NotebookMarket Data
$ npx skills add TradeMaster-NTU/TradeMaster#15
股票AI操盘手：从学习、模拟到实盘，一站式平台。包含股票知识、策略实例、大模型、因子挖掘、传统策略、机器学习、深度学习、强化学习、图网络、高频交易、C++部署和聚宽实例代码等，可以方便学习、模拟及实盘交易
5.8K starsJun 7, 2026 pushfinanceJupyter NotebookTrading Bot
$ npx skills add charliedream1/ai_quant_trade#16
Portfolio optimization with deep learning.
1.1K starsJan 24, 2024 pushfinancePythonPortfolio Analysis
$ npx skills add jankrepl/deepdowHow to choose
When should you switch?
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Factor Research if it already passes your workflow test and repository review.
Next step
Compare top candidates side by side
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.