Video Tutorial | How to Interface Python/R Algorithmic Trading Strategies with MetaTrader 4|2021
This webinar follows on from our blog post (http://blog.darwinex.com/zeromq-interface-python-r-metatrader4/).
Brought to you by Darwinex: UK FCA Regulated Broker, Asset Manager & Trader Exchange where Traders can legally attract Investor Capital and charge Performance Fees: https://www.darwinex.com/?utm_source=youtube&utm_medium=video-description-above-fold&utm_content=how-to-interface-python-r-zeromq-metatrader
** Get the latest updates to the DWX-ZeroMQ-Connector project, troubleshoot your applications, give and get help from fellow algorithmic traders and more, over at the Darwinex Collective Slack Workspace:
Associated GitHub repo:
In this presentation, we demonstrate how to build a communications bridge between trading strategies written in non-MQL programming languages (e.g. Python, R, Java, C++, etc), using ZeroMQ.
ZeroMQ is a distributed messaging and concurrency framework, using which traders can create sophisticated distributed trading architecture otherwise difficult to implement in MQL.
It also therefore allows traders to send instructions to MetaTrader 4 from outside the platform, and leverage the features of non-MQL environments (e.g. Machine Learning toolkits in Python/R) to create more sophisticated trading strategies for execution via MetaTrader 4.
Interested in deepening your algorithmic trading knowlegde?
If you consider yourself a talented trader, we’d love to have your strategy listed on our Exchange, enabling you to earn performance fees on investor profits.
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