Introduction to MQL5 (Part 1): A Beginner's Guide into Algorithmic Trading
Without any prior programming experience, learning MQL5 can be difficult but not impossible. Understanding MQL5, a specialized language created for algorithmic trading, necessitates having both programming and financial market expertise.
In this article, we will cover the following topics:
- Introduction to Programming
- Types of MQL5 Programs
- MetaEditor IDE
- MQL5 Language Basics
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Introduction to MQL5 (Part 3): Mastering the Core Elements of MQL5
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Welcome back, fellow traders and aspiring algorithmic enthusiasts! As we step into the third chapter of our MQL5 journey, we stand at the crossroads of theory and practice, poised to unravel the secrets behind arrays, custom functions, preprocessors, and event handling. Our mission is to empower every reader, regardless of their programming background, with a profound understanding of these fundamental MQL5 elements.
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Bill Williams Strategy with and without other Indicators and Predictions
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Bill Williams has a doctorate in Psychology, this is important because some traders use markets sentiment. This is very used and can be done with a sentiment script with an IA to score the sentiment of traders feelings with web markets scrapping in a for example social web. At the end of the article, there will be an example of Sentiment Analysis of market news.
Bill Williams psychology formation helped him adapt psychological concepts to trading. He studied market from a human perspective and how emotions deal with traders and its trading. Hi had a holistic view of the market, and he thought the market was chaotic and markets must be studied and traded taking this into account for our benefit. This will be discussed with the Indicators.
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Population optimization algorithms: Resistance to getting stuck in local extrema (Part I)
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This is a unique research, the idea for which came to me while answering questions that arose during the discussion of one of my articles. I am hopeful that readers will appreciate the value and originality of this work.
To carry out the experiment, we need to first initialize the coordinates of the agents forcibly outside the algorithm, using the coordinates of the global minimum, before measuring the fitness function at the first epoch.
Such an experiment will allow us to evaluate resistance to extremely difficult conditions and the ability to overcome limitations.
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How to Implement Auto Optimization in MQL5 Expert Advisors
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Get ready to be introduced into the wonderful world of auto-optimizing forex trading algorithms. It can allow your Expert Advisor (EA) to adjust itself for the next iteration of trading based on how the market conditions are after a trade is done.
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Introduction to MQL5 (Part 11): A Beginner's Guide to Working with Built-in Indicators in MQL5 (II)
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Welcome back to our MQL5 series! We'll discuss a fascinating subject in this chapter that I believe you'll find very useful and fascinating. We looked at how to use MQL5's built-in indicators in the last chapter, paying particular attention to the RSI. Not only that, but we even worked on a practical project that showed you how to incorporate the RSI into your trading approach with ease. We're going one step further this time by including not one but three potent indications in our project (RSI, the Stochastic Oscillator, and the Moving Average). That's not all; you’ll also learn about the intriguing idea of hidden divergence detection through our project. We will specifically discuss how to spot hidden bullish and bearish divergences.
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Overcoming The Limitation of Machine Learning (Part 1): Lack of Interoperable Metrics
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In our related series of articles, like Self-Optimizing Expert Advisors, we discussed an unsettling truth: even when you follow all the “best practices” in algorithmic trading development, things can still go horribly wrong. Briefly, we observed that practitioners using the RSI according to its standardized rules, may wait several months without the indicator generating any of the expected results. Resulting in trading accounts that are exposed to more market risk than what was intended.
In this series of articles, we shall explore critical problems that algorithmic traders are exposed to every day, by the very guidelines and practices intended to keep them safe when using machine learning models.
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Overcoming The Limitation of Machine Learning (Part 2): Lack of Reproducibility
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Consequently, if you compare the EURUSD performance across two brokers-let’s call them Broker A and Broker B, you may find the same pair moving in opposite directions at the same moment. For instance, Broker A might report the EURUSD appreciating by 0.12% in a day, while Broker B records a depreciation of -0.65% for that same day.
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Trading with the MQL5 Economic Calendar (Part 10): Draggable Dashboard and Interactive Hover Effects for Seamless News Navigation
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In this article, we advance the
MQL5 Economic Calendar series by introducing a draggable dashboard and interactive hover effects to enhance trader control and navigation of news events, ensuring a flexible and intuitive user experience. Building on
Part 9’s dynamic scrollbar and polished display, we now focus on a responsive
User Interface (UI) that allows repositioning the calendar on the chart and provides visual feedback for button interactions, optimizing access to economic news in live and backtesting environments.
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