Metatrader 5 Overview

Custom signal classes for wizard assembled Expert Advisors can take on various roles, that are worth exploring, and we continue this quest by examining how the Q-Learning algorithm when paired with Markov Chains can help refine the learning process of a multi-layer-perceptron network. Q-Learning is one of the several (approximately 12) algorithms of reinforcement-learning, so essentially this is also a look at how this subject can be implemented as a custom signal and tested within a wizard assembled Expert Advisor.

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The Average True Range is a common and popular volatility indicator, which arguably, for forex traders, is the ‘closest-thing’ to volume data. Developed as an indicator which was meant to track price bar range without skimping on intra-bar price changes, it has become a bit of a stalwart in the industry not just for filtering entry signals but also in guiding on position sizing. We look at this indicator by decomposing it into possible patterns as we have been doing with the previous indicator’s articles with perhaps the main difference being we look into patterns outside of the custom signal class by also considering the custom money management class for wizard assembled Expert Advisors.

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The Alligator indicator, that was developed by Bill Williams with the premise that markets tend to trend strongly in any set direction for only about 15 – 30% of the time. It inherently is a trend following tool that helps traders identify market direction and potential fractals or turning points. This it achieves by using a set of three smoothed moving averages (SMAs) that are not only set at different averaging periods, but are also shifted forward by varying amounts.

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In this article I will cover three global topics:

• Data arrays, which complete the main part about the data inside the program.
• Global terminal variables, allowing the exchange of simple data between different MQL5 programs.
• Some of the feature of functions and their interactions with variables.

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