mql5
Senior Member

Contents

• Introduction
• 1. Creating features
  
  • 1.1. Feature transformation
    
    • 1.1.1. Transformation
    • 1.1.2. Normalization
    • 1.1.3. Discretization
    
    
  • 1.2. Creating new features
  
  
• 2. Choosing predictors
  
  • 2.1. Visual evaluation
  • 2.2. Analytical evaluation
  • 2.3. Neural network
  
  
• Conclusion
• Application

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Algorithmic trading consists not only of planning and development of trading robots but also (to a greater extent) testing and verifying the survivability of ideas and algorithms implemented in them. MetaTrader 5 provides the built-in tester for optimizing Expert Advisors on historical data.

This tool is often indispensable in everyday activity. However, its main issue is the search for parameters that remain steadily profitable over time

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In this article we will continue exploring deep neural networks (DNN) which I started in the previous articles (1, 2, 3).DNN are widely used and intensely developed in many areas. The most common examples of everyday use of neural networks are speech and image recognition and automatic translation from one language into another. DNN are also used in trading. Given the fast development of algorithmic trading, in-depth studying of DNN seems to be useful.

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Whether we like it or not, statistics plays a significant role in trading. Starting with the fundamental news full of figures and ending with trade reports or test reports, we cannot do away without statistical indicators. At the same time, the thesis on applicability of statistics in making trade decisions remains one of the most controversial topics. Is the market random, are the quotes stationary, is the probabilistic approach to their analysis applicable?

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MetaTrader 4 for Android devices updated: New Design, Financial News and System Log. Mobile Trading should be convenient.