With the rise of algorithmic and quantitative trading, using Python for finance and investing has become increasingly popular. Python provides easy access to financial data through APIs and allows building trading algorithms with its extensive libraries. This article will explore using Python open-source libraries on GitHub for free to access financial data, backtest trading strategies, and automate algorithmic trading.
Tushare provides free Chinese stock market data API in Python
The Tushare library is a leading open data platform in China that offers a Python API to retrieve Chinese stock market data for free. It covers over 25 million pieces of historical data and real-time quotes data of A-shares. Tushare makes it easy to get stock basics, daily bar, financial reports, industry classifications, fund holdings, and more. The documentation is in both English and Chinese. Tushare has been widely adopted by retail and institutional investors in China for quantitative analysis and algorithmic trading.
Zipline enables local backtesting of algorithmic trading strategies
Zipline is an open-source Python backtesting library developed by Quantopian for trading algorithm research and development. It provides event-driven system for backtesting with historical pricing data and trading logic. Zipline is easily installed through conda or pip and integrates well with pandas, SQLAlchemy, Numpy, and Matplotlib. It also has builtin fetchers to acquire pricing data and a comprehensive suite of statistics for analyzing trade performance. Zipline makes iteratively building and evaluating algorithmic trading strategies highly productive.
Ricequant API supports live trading and community strategy sharing
Ricequant API is offered by Ricequant, a leading quantitative trading platform in China. In addition to comprehensive historical Chinese stock data, it provides paper trading and live trading API access. The RESTful API enables developing and deploying algorithmic trading strategies from scratch or based on hundreds of open-source algorithms from the community. Ricequant API has detailed documentation and active developer community support. It also integrates with WeChat for mobile notifications and monitoring.
Lean Engine from QuantConnect algorithms on global markets
QuantConnect Lean Engine is an open-source algorithmic trading engine that supports trading strategies development, backtesting, and live trading across global equities, forex, options, futures, and cryptocurrencies. It offers free cloud-based IDE that integrates with common data feeds and brokerages. QuantConnect provides C#, Python, F# code samples to get started quickly. The Lean community shared over 10,000 open source algorithms. QuantConnect Lean makes it easy to turn trading strategies into productionised algo trading systems.
Python has rich open-source libraries and thriving developer communities dedicated to quantitative finance and algorithmic trading. Integrating APIs like Tushare, Zipline, Ricequant and QuantConnect Lean Engine enables retail and institutional investors to efficiently research, develop, backtest and automate trading strategies across global markets.