add lumibot

Readme.md

@@ -61,6 +61,7 @@ Overall, I tend to pick decent or promising libraries that closely related to sy
 - [backtesting.py](https://github.com/kernc/backtesting.py) | `Python` | - Backtesting.py is a Python framework for inferring viability of trading strategies on historical (past) data. Improved upon the vision of Backtrader, and by all means surpassingly comparable to other accessible alternatives, Backtesting.py is lightweight, fast, user-friendly, intuitive, interactive, intelligent and, hopefully, future-proof.
 - [backtrader](https://github.com/mementum/backtrader) | `Python` | - Event driven Python Backtesting library for trading strategies
 - [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.
+- [lumibot](https://github.com/Lumiwealth/lumibot/tree/8da88cadfe9ee35399dd69c94aa5ed3cf995f417) | `Python` | - A very simple yet useful backtesting and sample based live trading framework
 - [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#)