MQL5 Programming Articles

In this article, I will continue the development of the ScrollBar control and start implementing the mouse interaction functionality. In addition, I will expand the lists of mouse state flags and events.

Machine learning has become a popular method for strategy development. Whilst there has been more emphasis on maximizing profitability and prediction accuracy , the importance of processing the data used to build predictive models has not received a lot of attention. In this article we consider using the concept of entropy to evaluate the appropriateness of indicators to be used in predictive model building as documented in the book Testing and Tuning Market Trading Systems by Timothy Masters.

In this article, I will start developing the ScrollBar auxiliary control element and its derivative objects — vertical and horizontal scrollbars. A scrollbar is used to scroll the content of the form if it goes beyond the container. Scrollbars are usually located at the bottom and to the right of the form. The horizontal one at the bottom scrolls content left and right, while the vertical one scrolls up and down.

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.

In this article, I will develop display styles and description text for the progress bar of the ProgressBar control.

In this article, we will study the algorithm of an artificial bee colony and supplement our knowledge with new principles of studying functional spaces. In this article, I will showcase my interpretation of the classic version of the algorithm.

In this article, I will continue the development of the ProgressBar control. In particular, I will create the functionality for managing the progress bar and visual effects.

In this article, I will complete the development of the ToolTip control and start the development of the ProgressBar WinForms object. While working on objects, I will develop universal functionality for animating controls and their components.

We got acquainted with the Q-learning method in one of the earlier articles within this series. This method averages rewards for each action. Two works were presented in 2017, which show greater success when studying the reward distribution function. Let's consider the possibility of using such technology to solve our problems.

How do you like the idea of adding a new chart type to the MetaTrader 5 platform? Some people say it lacks a few things that other platforms offer. But the truth is, MetaTrader 5 is a very practical platform as it allows you to do things that can't be done (or at least can't be done easily) in many other platforms.

In this article, I will start developing the Tooltip control, as well as new graphical primitives for the library. Naturally, not every element has a tooltip, but every graphical object has the ability to set it.

In this article, I will revise the logic of specifying the base and main objects for all WinForms library objects, develop a new Hint base object and several of its derived classes to indicate the possible direction of moving the separator.

In this article, I will add new mouse events relative to the boundaries of the working areas of WinForms objects and fix some shortcomings in the functioning of the TabControl and SplitContainer controls.

In the current article, I will implement the ability to change the properties and appearance of the newly created SplitContainer control.

In the previous articles of this series, we have seen two reinforced learning algorithms. Each of them has its own advantages and disadvantages. As often happens in such cases, next comes the idea to combine both methods into an algorithm, using the best of the two. This would compensate for the shortcomings of each of them. One of such methods will be discussed in this article.

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.

In this article, I will create the class of an auxiliary panel separator object for the SplitContainer control.

In the current article, I will start developing the SplitContainer control from the MS Visual Studio toolkit. This control consists of two panels separated by a vertical or horizontal movable separator.