基于Python的开源量化交易平台开发框架

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

TuShare is a utility for crawling historical data of China stocks

modular quant framework.

Common financial technical indicators implemented in Pandas.

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.

FinRL­®-Meta: Dynamic datasets and market environments for FinRL.

wtpy是基于wondertrader为底层的针对python的子框架

quant framework for stock

简单易用的量化金融数据包(easy utility for getting financial market data of China)

An Open Source Portfolio Backtesting Engine for Everyone | 面向所有人的开源投资组合回测引擎

A working example algorithm for scalping strategy trading multiple stocks concurrently using python asyncio

Python-based framework for backtesting trading strategies & analyzing financial markets [GUI ]

Futu Algorithmic Trading Solution (Python) 基於富途OpenAPI所開發量化交易程序

institutional crypto trading platforms, prime brokerage crypto, secure digital asset APIs, block-trade liquidity, OTC crypto liquidity, OTC block trading, Coinbase Prime trading, block-trade execution, institutional crypto custody, real-time P&L monitoring, deep liquidity aggregation, OTC trading privacy

Parse SEC EDGAR HTML documents into a tree of elements that correspond to the visual (semantic) structure of the document.

🚀 The production-ready subclass of `pandas.DataFrame` to support stock statistics and indicators

This is an ongoing collection of Open Banking Data APIs for Australian deposit taking institutions.

Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierarchical reinforcement learning. It includes the code for the proposed method and experimental results on real-world stock data to demonstrate its effectiveness.

A comprehensive open-source toolkit for AI-powered analysis and interpretation of SEC EDGAR filings, providing valuable insights for investors, fintech developers, and researchers.