fintech

基于Python的开源量化交易平台开发框架

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.

FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

TuShare is a utility for crawling historical data of China stocks

[🔥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

FinRL®: Financial Reinforcement Learning. 🔥

Online Accounting Software

Open Source Metering and Usage Based Billing API ⭐️ Consumption tracking, Subscription management, Pricing iterations, Payment orchestration & Revenue analytics

Introduce blockchain related technologies, from theory to practice with bitcoin, ethereum and hyperledger.

Open Source Wealth Management Software. Angular + NestJS + Prisma + Nx + TypeScript 🤍

WonderTrader——量化研发交易一站式框架

This repository contains opportunities for you to apply to more than 400 product base companies(NOT JUST FAANGM) & good start-ups.

modular quant framework.

Hikyuu Quant Framework 基于C++/Python的极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。

FISCO BCOS（发音为/ˈfɪskl bi:ˈkɒz/）是一个稳定、高效、安全的许可区块链平台，已被广泛应用于现实的行业应用。截至目前，已拥有5000多家企事业单位，400多个产业数字化标杆应用，涵盖文化版权、司法服务、政府服务、物联网、金融、智慧社区、房地产建设、社区治理、乡村振兴等领域。FISCO BCOS (pronounced /ˈfɪskl bi:ˈkɒz/) is a stable, efficient, and secure permissioned blockchain platform that has been widely used in real-world industry applications.

Common financial technical indicators implemented in Pandas.

TradeMaster is an open-source platform for quantitative trading empowered by reinforcement learning 🔥 ⚡ 🌈

dj-stripe automatically syncs your Stripe Data to your local database as pre-implemented Django Models allowing you to use the Django ORM, in your code, to work with the data making it easier and faster.

Apache Fineract

List of awesome resources for machine learning-based algorithmic trading