add more backtest

Readme.md

@@ -63,11 +63,14 @@ Overall, I tend to pick decent or promising libraries that closely related to sy
 Note: the one marked as `Live Trading` has reasonable live trading support for at least 1 broker. Otherwise, backtest
  function only.
 
+Search page by languages you are interested in to find related libraries. For example: `Ctrl+F`, `Rust`
+
 - [aat](https://github.com/AsyncAlgoTrading/aat) | `Python`, `C++`, `Live Trading`| - an asynchronous, event-driven framework for writing algorithmic trading strategies in python with optional acceleration in C++. It is designed to be modular and extensible, with support for a wide variety of instruments and strategies, live trading across (and between) multiple exchanges.
 - [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`, `Live Trading` | - 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.
 - [finmarketpy](https://github.com/cuemacro/finmarketpy) | `Python` | - Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians) 
+- [gobacktest](https://github.com/gobacktest/gobacktest) | `Go` | - A Go implementation of event-driven backtesting framework 
 - [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`, `Rust`, `Live Trading` | - 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.