go get github.com/MatrixAINetwork/go-matrix
cd go/src/github.com/MatrixAINetwork/go-matrix
'use strict' | |
/** | |
* DISCLAIMER: this script creates an order (price: 500, symbol: BTCUSD, amount: 0.001) | |
* please run at your own risk. | |
* TO RUN: | |
* $ export API_KEY={YOUR_API_KEY} | |
* $ export API_SECRET={YOUR_API_SECRET} | |
* $ npm install bitfinex-api-node | |
* $ node rest_open_cancel_order.js |
I hereby claim:
To claim this, I am signing this object:
Download linux node binaries
wget https://s3.us-east-2.amazonaws.com/consensus-ai-releases/sentient-network-tools/sentient-network-tools-linux-amd64.zip
Unzip:
sudo apt-get install unzip
Our Golang client is one of our most popular open source projects with over 350 forks/stars on Github. But why Go? Well, it is a seriously quick compiled programming language with great support for concurrency making it perfect for trading.
So what does the Bitfinex Golang client do? Well its a library created by the bitfinex team to help programmers interact with the Bitfinex websocket and rest interface. The lib offers tons of functionaity including creating new trades, managing existing orders, retrieving historical data and a lot more. You can find the client on girhub here: https://github.com/bitfinexcom/bitfinex-api-go
In this tutorial we are going to pull the bitfinex-api-go library, subscribe to new price updates and then begin making trades on the BTC/USD trading pair using the client websocket. We will also explore historical data using the rest interface.
Algorithmic trading has gained a lot of popularity in the world of crypto currencies and now with the all new Python edition of the Honey Framework it is a easy as ever to create your own alo strategy.
So what is the HoneyFramework? Its a Python/NodeJs library which is the scaffolding to your algo trading strategy. The framework provides many features such as the ability to add pre-made/custom indicators, complex position management, real-time data feeds, multiple back-testing modes and a lot more.
In this tutorial we are going to use the Python HoneyFramework to create a simple trading strategy and perform both an offline and a live back-test. Brief disclaimer, this trading strategy is purely for educational purposes and is not advice on how to create a live profitable strategy.