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  1. Introduction to MQL5 (Part 13): A Beginner's Guide to Building Custom Indicators (II)

    by , 03-11-2025 at 04:02 AM
    Welcome back to our MQL5 series! Part 12 of this series explored the fundamentals of building custom indicators in MQL5. We created a Moving Average indicator from scratch, implementing its logic manually instead of relying on built-in functions. Then, we extended this knowledge by transforming it into a Moving Average in candle format, demonstrating how to manipulate graphical elements within an indicator.

    This article will cover a strategy that is solely intended for
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  2. Data Science and ML (Part 29): Essential Tips for Selecting the Best Forex Data for AI Training Purposes

    by , 03-09-2025 at 03:19 PM
    With all the trading data and information such as indicators (there are more than 36 built-in indicators in MetaTrader 5), symbol pairs (there are more than 100 symbols) that can also be used as data for correlation strategies, there are also news which are valuable data for traders, etc. The point I'm trying to raise is that there is abundant information for traders to use in manual trading or when trying to build Artificial Intelligence models to help us make smart trading decisions in our
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  3. Price Action Analysis Toolkit Development (Part 14): Parabolic Stop and Reverse Tool

    by , 03-07-2025 at 06:32 AM
    In this article, we focus on developing an Expert Advisor (EA) using MQL5, designed to identify potential market reversals. The EA employs the Parabolic SAR for signal detection, generating trading signals by monitoring technical indicators, evaluating their validity in real time, and identifying optimal exit points when predefined levels are reached.
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  4. Deconstructing examples of trading strategies in the client terminal

    by , 03-06-2025 at 01:48 PM
    In this article, we explore a feature selection algorithm introduced in the paper 'Local Feature Selection for Data Classification' by Narges Armanfard, James P. Reilly, and Majid Komeili. This method aims to identify predictive features that are often overlooked by traditional selection techniques due to their limited global utility. We will begin with a general overview of the algorithm, followed by its implementation in Python to create classifier models suitable for export to MetaTrader
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  5. William Gann methods (Part I): Creating Gann Angles indicator

    by , 03-05-2025 at 07:07 AM
    In this article, we will dive into the world of William Gann's trading methods, starting with creating Gann Angles indicator in MQL5. We will go through the theory behind this tool and implement it step by step as a custom indicator for the MetaTrader 5 platform.
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