High Speed Trading

It seems like everybody nowadays is interested in Artificial Intelligence, it's everywhere, and the big guys in the tech industry such as Google and Microsoft behind openAI are pushing for AI adaptation in different aspects and industries such as entertainment, healthcare industry, arts, creativity, etc.

I see this trend also in the MQL5 community why not, with the introduction of matrices and vectors and ONNX to Metatrader5, It is now possible to make Artificial intelligence trading models of any complexity, you don't even need to be an expert in Linear algebra or a nerd enough to understand everything that goes into the system.

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For novice traders, understanding the basic principles of optimization algorithms can be a powerful tool in finding profitable trades and minimizing risks. For seasoned professionals, deep knowledge in this area can open up new horizons and help create sophisticated trading strategies that exceed expectations.

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Recurrent Neural Networks (RNNs) are artificial neural networks designed to recognize patterns in sequences of data, such as time series, language, or video. Unlike traditional neural networks, which assume that inputs are independent of each other, RNNs can detect and understand patterns from a sequence of data (information).

A basic understanding of Python, ONNX in MQL5, and Python machine learning is required to understand the contents of this article fully.

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HFT trading need super computer I think, maybe not all brokers allows high speed trading because could make their server slowing down. HFT trading is carried out by automating into a trading robot, it is very aggressive and can open and close positions very quickly

When applying AI to any task, we must try our best to give the model as much useful information about the real world as we can. To describe different properties of the market to our AI models, we must manipulate and transform the input data, this process is referred to as feature engineering. This series of articles will teach you how to transform your market data, to reduce the error levels of your models. Today, I will focus on how to use moving averages to increase the forecasting range of your AI models in a fashion that gives complete control and a reasonable understanding of the global effectiveness of the strategy.

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