Metatrader 5 / Metatrader 4 for MQL5 / MQL4 articles preview

This article was created as a development of ideas from the earlier published article related to DLL creation with Visual Studio 2005/2008. The original basic article has not lost its relevance and thus if you are interested in this topic, be sure to read the first article. However much time has passed since then, so the current Visual Studio 2017 features an updated interface. The MetaTrader 5 platform has also acquired new features. Obviously, there is a need to update the information and consider some new features. In this article, we will pass all steps from the development of the DLL project in Visual Studio 2017 to connection of a ready DLL to the terminal and its use.

The article is intended for beginners who want to learn how to create and connect C++ libraries to the terminal.

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Since its introduction, MetaTrader 5 provides multicurrency testing options. This possibility is often used by traders. However the function is not universal. In particular, after running a test, the user can open a chart with performed trading operations. But this is only a chart of one traded symbol selected in the strategy tester settings. The entire trading history of all used symbols cannot be viewed after testing, while visual examination is not always efficient. Additional analysis may be required after some time after testing. Also, a report can be provided by another person. Therefore, a tool for visualizing trading on multiple working symbols based on the HTML testing report would be very useful.

The previous article provided a description of the HTML parser based on CSS selectors[1]. The parser extracts the list of deals from the HTML report, based on which we can trades can be formed (graphical objects). Parsing of CSV files from the Signals section is a bit easier, while the file format for the MetaTrader 4 (*.history.csv) and MetaTrader 5 (*.positions.csv) signals is supported by the built-in MQL functions.

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Traders often have to analyze huge amounts of data. These often include numbers, quotes, indicator values and trading reports. Due to the large number of parameters and conditions, on which these numbers depend, let us consider them in parts and view the entire process from different angles. The entire amount of information forms kind of a virtual hypercube, in which each parameter defines its own dimension, which is perpendicular to the rest. Such hypercubes can be processed and analyzed using the popular OLAP ( Online Analytical Processing) technology.

The "online" word in the approach name does not refer to the Internet, but means promptness of results. The operation principle implies the preliminary calculation of the hypercube cells, after which you can quickly extract and view any cross section of the cube in a visual form. This can be compared to the optimization process in MetaTrader: the tester first calculates trading variants (which may take quite a long time, i.e. it is not prompt), and then outputs a report, which features the results linked to input parameters. Starting from build 1860, the MetaTrader 5 platform supports dynamic changes of viewed optimization results by switching various optimization criteria. This is close to OLAP idea. But for a complete analysis, we need the possibility to select many other slices of the hypercube.

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Since October 2018, MetaTrader 5 supports integration with Net Famework libraries. This set of libraries is actually much more than a framework or a specialized system for performing a specific range of tasks, like drawing graphical windows or implementing a network interaction. Net Framework has literally everything. It allows developing websites (Net Core, MVC), creating system applications having a unified professional interface (Windows Forms), building complex distributed systems with data exchange between nodes and working with databases (Entity Framework). Besides, Net Framework is a huge community of programmers and companies with thousands of various open source projects. If the interaction is organized properly, all this can be available in MQL today.

In this article, we will continue to develop the functionality of GuiController created in the first part. This functionality is aimed at interacting with the graphical functionality of the Net Framework based on the Windows Forms technology. Currently, plenty of info is available on MQL graphical features. There are a lot of various libraries that do more or less the same by means of MQL. Therefore, I do not want this material to be perceived by readers as "another library for working with forms". In fact, this material is only a part of a large series of articles describing interaction with Net Framework and gradually revealing boundless features of this software platform. Windows Forms is only one of the building blocks within this platform, although a very convenient and comprehensive one, just like any part of the Net technology. The Windows Forms graphical subsystem is a great starting point for exploring this framework. After proper studying, it can be applied in other interactions with Net Framework. Besides, it also allows creating quite efficient and, most importantly, easy-to-implement trading panels, EA configuring windows, advanced graphical indicators, robot control systems and other things related to interaction between users and the trading platform.

Contents

• Introduction
• Arranging the test of new elements
• MessageBox
• TabControl
• CheckBox
• Radio Button
• Combo Box
• NumericUpDown (numerical listing window)
• DataTimePicker (date selection window)
• ElementHide and ElementEnable - hiding and disabling an arbitrary element
• AddItem - adding subelements
• Exception - event of receiving exceptions
• Summary tables of available graphical elements and events
• Conclusion

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Contents

• Similarities and differences of the account types
• Implementing event handling on a netting account
• Testing the performance on hedging and netting accounts
• What's next?

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Previous articles within the series:
Part 1. Concept, data management.
Part 2. Collection of historical orders and deals.
Part 3. Collection of market orders and positions, arranging the search.
Part 4. Trading events. Concept.
Part 5. Classes and collection of trading events. Sending events to the program.

In the first article related to the use of OLAP techniques in trading, we considered the general multidimensional data processing principles and provided ready-to-use MQL classes, which enable the practical application of OLAP for account history or trading report processing. However we implemented a simplified output of results as a text in the Experts logs. For a more efficient visual representation, you need to create a new class, a child of the Display interface, which can visualize OLAP data using graphics. This task requires a lot of preparatory work and concerns many different aspects which are not related to the OLAP. So let's put aside data processing and let's focus on the graphical interface of the MQL program.

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The modern financial market is an example of a "natural" complexly balanced system. On the one hand, the market is pretty chaotic, because it is influenced by a large number of participants. On the other hand, the market is characterized by definite stable processes, which are determined by the market participants' actions. One of econophysics tasks concerns the description of social interaction processes, which form the price dynamics observed on the exchange. Therefore, it is highly desirable to define and present specific properties of financial time series, which will distinguish such data from other natural processes. In modern theories, price series are defined as different-scale fractals (from several minutes to dozens of years).

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Contents

• Introduction
• Perception issue
• Price velocity measurement methods
• Developing trading strategies based on measurement methods
• Testing price velocity measurement methods
• Summary
• Conclusion

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As you probably know, following of money management rules is highly recommended for any trading. It means that one is not recommended to enter a trade in which more than N% of deposit can be lost.

N is chosen by the trader. In order to comply with this rule, one should correctly calculate the trading lot value.

At relevant master classes, presenters usually show a ready Excel file, which includes relevant lot calculation formulas for each symbol. And thus they obtain the required lot value by "simply entering" their stop loss value.

Is this really that "simple"? The lot calculation operation can take a minute or more. So when you finally determine the lot size, the price can move very far from the intended entry point. Moreover, this requires from you performing of extra operations. Another disadvantage of this method, is that manual calculations often increase the chance of making an error.
So let's try make this process really simple. To do this, we will create an Expert Advisor for setting the opening and Stop Loss prices in the visual mode. Based on these parameters and your risk value, the EA will set the appropriate lot value and will open a position in the relevant direction.

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This article covers one of algo trading approaches. It is not directly related to MetaQuotes platforms and is intended for broad masses. If any of the terms is not clear for you, please use search options. The purpose of this article is to find a profitable trading system (or a trading robot).

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