more...In this article, we will see how we can use an autoencoder neural network in the financial space to help us remove noise in the market so that we can discover trading opportunities.
This article is an easy read if you have a basic understanding of ONNX, PCA, and Neural Networks in general.
ONNX (Open Neural Network Exchange) revolutionizes the way we make sophisticated AI-based mql5 programs. This new technology to MetaTrader 5 is the way forward to machine learning as it shows a lot of promise like no other for its purpose however, ONNX comes with a couple of challenges that can give you headaches if you have no clue how to solve them whatsoever.
This article assumes you have a basic understanding of machine learning and AI theory, and that you have at least tried
more...The Multi-currency Expert Advisor is a automated trading that can open, close, and manage orders for more than one symbol pair from a single symbol chart.
This article focuses on the Expert Advisor trading for 30 pairs and using the ZigZag indicator, which is filtered with the Awesome Oscillator or filters each other's signals.
In the first article I introduced programming paradigms and focused on how to implement procedural programming in MQL5. I also explored functional programming. After gaining a deeper understanding of how procedural programming works, we created a basic price action expert advisor using the exponential moving average indicator (EMA) and candlestick price data.
This article will take a deeper dive into the object-oriented programming paradigm. We'll then apply this knowledge
This algorithm is based on a self-learning method, where the agent uses information obtained during interaction with the environment to generate "intrinsic" rewards and update its strategy. The algorithm is based on the use of several agent models that interact with the environment and generate various predictions. If the models disagree, it is considered an "interesting" event and the agent is incentivized to explore that space of the environment. In this way, the algorithm incentivizes the agent
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