add nautilus trader

Readme.md

@@ -57,6 +57,7 @@ Overall, I tend to pick decent or promising libraries that closely related to sy
 - [backtrader](https://github.com/mementum/backtrader) | `Python` | - Event driven Python Backtesting library for trading strategies
 - [bt](https://github.com/pmorissette/bt) | `Python` | -  Flexible backtesting for Python based on Algo and Strategy Tree
 - [FinRL](https://github.com/AI4Finance-Foundation/FinRL) | `Python` | - FinRL is the first open-source framework to demonstrate the great potential of applying deep reinforcement learning in quantitative finance.
+- [nautilus_trader](https://github.com/nautechsystems/nautilus_trader) | `Python`, `Cython` | - A high-performance algorithmic trading platform and event-driven backtester
 - [QLib (Microsoft)](https://github.com/microsoft/qlib) | `Python`, `Cython` | - Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.
 - [QuantConnect](https://github.com/QuantConnect/Lean) | `C#`, `.NET` | - Lean Algorithmic Trading Engine by QuantConnect (Python, C#)
 - [QUANTAXIS](https://github.com/QUANTAXIS/QUANTAXIS) | `Python` | - QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权/港股/虚拟货币 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案