Articles on trading system automation in MQL5

The article continues developing indicator object classes and their collections. For each indicator object create its description and correct collection class for error-free storage and getting indicator objects from the collection list.

We will begin the journey to explore the steps and workflow on how to base development for MetaTrader 5 platform solely on Linux system in which the final product works seamlessly on both Windows and Linux system. We will get to know Wine, and Mingw; both are the essential tools to make cross-platform development works. Especially Mingw for its threading implementations (POSIX, and Win32) that we need to consider in choosing which one to go with. We then build a proof-of-concept DLL and consume it in MQL5 code, finally compare the performance of both threading implementations. All for your foundation to expand further on your own. You should be comfortable building MT related tools on Linux after reading this article.

A trading strategy using hedging system created for trading the intra-day style of GBPJPY / EURJPY and for daily trading.

To complete this series of articles on automation, we will continue discussing the topic of the previous article. We will see how everything will fit together, making the EA run like clockwork.

This article, the 16th in our series, continues with a look at Functors and how they can be implemented using artificial neural networks. We depart from our approach so far in the series, that has involved forecasting volatility and try to implement a custom signal class for setting position entry and exit signals.

In this article, we will use the rebuy algorithm for a deeper understanding of the efficiency of trading systems and start working on the general principles of improving trading efficiency using mathematics and logic, as well as apply the most non-standard methods of increasing efficiency in terms of using absolutely any trading system.

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode.

The article considers creation of the custom indicator object for the use in EAs. Let’s slightly improve library classes and add methods to get data from indicator objects in EAs.

In this article, we consider encryption/decryption of objects in MetaTrader and in external applications. Our purpose is to determine the conditions under which the same results will be obtained with the same initial data.

Time based pattern analysis can be used in the currency market to determine a better time to enter a trade or time in which trading should be avoided at all. Here we use MetaTrader 4 to analyze history market data and produce optimization results that can be useful for application in mechanical trading systems.

Functions are critical things in any programming language, it helps developers apply the concept of (DRY) which means do not repeat yourself, and many other benefits. In this article, you will find much more information about functions and how we can create our own functions in MQL5 with simple applications that can be used or called in any system you have to enrich your trading system without complicating things.

Two years ago in "The Last Crusade" we reviewed quite an interesting yet currently not widely used method for displaying market information - point and figure charts. Now I suggest you try to write a trading robot based on the patterns detected on the point and figure chart.

Successful and comfortable trading using MT4 platform without detailed market analysis - is it possible? Can such trading be implemented in practice? I suppose, yes. Especially in terms of the automated trading!

These series of articles will proposition that the MQL5 Wizard should be a mainstay for traders. Why? Because not only does the trader save time by assembling his new ideas with the MQL5 Wizard, and greatly reduce mistakes from duplicate coding; he is ultimately set-up to channel his energy on the few critical areas of his trading philosophy.

In this article, we will put into practice all the knowledge from this series. We will finally build a 100% automated and functional system. But before that, we still have to learn one last detail.

We continue to study reinforcement learning methods. In the previous article, we got acquainted with the Deep Q-Learning method. In this method, the model is trained to predict the upcoming reward depending on the action taken in a particular situation. Then, an action is performed in accordance with the policy and the expected reward. But it is not always possible to approximate the Q-function. Sometimes its approximation does not generate the desired result. In such cases, approximation methods are applied not to utility functions, but to a direct policy (strategy) of actions. One of such methods is Policy Gradient.

The article deals with the outlook of using MQL4 for more productive work at FOREX markets.

As developers, we need to learn how to create and develop software that can be reusable and flexible without duplicated code especially if we have different objects with different behaviors. This can be smoothly done by using object-oriented programming techniques and principles. In this article, we will present the basics of MQL5 Object-Oriented programming to understand how we can use principles and practices of this critical topic in our software.