Articles on trading system automation in MQL5

Studies related to search for the fractal behavior of financial data suggest that behind the seemingly chaotic behavior of economic time series there are hidden stable mechanisms of participants' collective behavior. These mechanisms can lead to the emergence of price dynamics on the exchange, which can define and describe specific properties of price series. When applied to trading, one could benefit from the indicators which can efficiently and reliably estimate the fractal parameters in the scale and time frame, which are relevant in practice.

This article explores the effectiveness of complex trading systems by analyzing the efficiency of its individual components. Any analysis, whether it is graphic, based on indicators, or any other, is one of the key components of successful trading in financial markets. This article is to some extent a research of few simple and independent trading systems for analyzing their effectiveness and usefulness of the joint application.

This is the next article within the series, in which I show how I created a convenient library for manual application of chart graphics by utilizing keyboard shortcuts. The tools used include straight lines and their combinations. In this part, we will view how the drawing tools are applied using the functions described in the first part. The library can be connected to any Expert Advisor or indicator which will greatly simplify the charting tasks. This solution DOES NOT use external dlls, while all the commands are implemented using built-in MQL tools.

In this article, we will continue the development of trading requests, implement placing pending orders and eliminate detected shortcomings of the trading class operation.

We continue studying the world of neural networks. In this article, we will consider another type of neural networks, recurrent networks. This type is proposed for use with time series, which are represented in the MetaTrader 5 trading platform by price charts.

Today it is difficult to find a computer that does not have an installed web-browser. For a long time browsers have been evolving and improving. This article discusses the simple and safe way to create of charts and diagrams, based on the the information, obtained from MetaTrader 5 client terminal for displaying them in the browser.

The article deals with the development of the timeseries collection of specified timeframes for all symbols used in the program. We are going to develop the timeseries collection, the methods of setting collection's timeseries parameters and the initial filling of developed timeseries with historical data.

Determing the broker offset and GMT automatically. Instead of asking the support of your broker, from whom you will probably receive an insufficient answer (who would be willing to explain a missing hour), we simply look ourselves how they time their prices in the weeks of the time changes — but not cumbersome by hand, we let a program do it — why do we have a PC after all.

In this second article, we will continue to study neural networks and will consider an example of using our created CNet class in Expert Advisors. We will work with two neural network models, which show similar results both in terms of training time and prediction accuracy.

In this article, we will have a look at the handler of invalid trading order parameters and improve the trading event class. Now all trading events (both single ones and the ones occurred simultaneously within one tick) will be defined in programs correctly.

In this article, we build an MQL5 Expert Advisor for Fibonacci retracement trading, using either daily candle ranges or lookback arrays to calculate custom levels like 50% and 61.8% for entries, determining bullish or bearish setups based on close vs. open. The system triggers buys or sells on price crossings of levels with max trades per level, optional closure on new Fib calcs, points-based trailing stops after a min profit threshold, and SL/TP buffers as percentages of the range.

The article describes the method of fast visual testing of trading ideas. The method is based on the combination of a price chart, a signal indicator and a balance calculation indicator. I would like to share my method of searching for trading ideas, as well as the method I use for fast testing of these ideas.

In this article, we are going to finish the development of the base object of all library objects, so that any library object based on it is able to interact with a user. For example, users will be able to set the maximum acceptable size of a spread for opening a position and a price level, upon reaching which an event from a symbol object is sent to the program with the spread or price level-based signal.

Surely, a fey thought to trade closely to extremums visited every apprentice trader when he/she saw "enigmatic" polyline for the first time. It's so simple, indeed. Here is the maximum. And there is the minimum. A beautiful picture on the history. And what is in practice? A ray is drawn. It should seem, that is it, the peak! It is time to sell. And now we go down. But hell no! The price is treacherously moving upwards. Haw! It's a trifle, not an indicator. And you throw it out!

The article considers several methods of applying the Moving Average indicator. Each method involving a curve analysis is accompanied by indicators visualizing the idea. In most cases, the ideas shown here belong to their respected authors. My sole task was to bring them together to let you see the main approaches and, hopefully, make more reasonable trading decisions. MQL5 proficiency level — basic.

In this article, we will further develop the idea of drawing graphical objects on charts using keyboard shortcuts. New tools have been added to the library, including a straight line plotted through arbitrary vertices, and a set of rectangles that enable the evaluation of the reversal time and level. Also, the article shows the possibility to optimize code for improved performance. The implementation example has been rewritten, allowing the use of Shortcuts alongside other trading programs. Required code knowledge level: slightly higher than a beginner.

A proverbial wisdom often attributed to various famous people says: "He who makes no mistakes never makes anything." Unless you consider idleness itself a mistake, this statement is hard to argue with. But you can always analyze the past mistakes (your own and of others) to minimize the number of your future mistakes. We are going to attempt to review possible situations arising when executing jobs in the same-name service.

This article describes a new approach to hedging of positions and draws the line in the debates between users of MetaTrader 4 and MetaTrader 5 about this matter. It is a continuation of the first part: "Bi-Directional Trading and Hedging of Positions in MetaTrader 5 Using the HedgeTerminal Panel, Part 1". In the second part, we discuss integration of custom Expert Advisors with HedgeTerminalAPI, which is a special visualization library designed for bi-directional trading in a comfortable software environment providing tools for convenient position management.

I continue filling the algorithm with the minimum necessary functionality and testing the results. The profitability is quite low but the articles demonstrate the model of the fully automated profitable trading on completely different instruments traded on fundamentally different markets.

In this article, we will develop a grider EA for trading in a trend direction within a range. Thus, the EA is to be suited mostly for Forex and commodity markets. According to the tests, our grider showed profit since 2018. Unfortunately, this is not true for the period of 2014-2018.

Recently MetaTrader 4 and MetaTrader 5 user received an opportunity to become a Signals Provider and earn additional profit. Now, you can display your trading success on your web site, blog or social network page using the new widgets. The benefits of using widgets are obvious: they increase the Signals Providers' popularity, establish their reputation as successful traders, as well as attract new Subscribers. All traders placing widgets on other web sites can enjoy these benefits.

The project involves using Python for deep learning-based forecasting in financial markets. We will explore the intricacies of testing the model's performance using key metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R-squared (R2) and we will learn how to wrap everything into an executable. We will also make a ONNX model file with its EA.

In the first part, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. We created the COrder abstract object which is a base object for storing data on history orders and deals, as well as on market orders and positions. Now we will develop all the necessary objects for storing account history data in collections.

Traders often talk about trends and flats but very few of them really understand what a trend/flat really is and even fewer are able to clearly explain these concepts. Discussing these basic terms is often beset by a solid set of prejudices and misconceptions. However, if we want to make profit, we need to understand the mathematical and logical meaning of these concepts. In this article, I will take a closer look at the essence of trend and flat, as well as try to define whether the market structure is based on trend, flat or something else. I will also consider the most optimal strategies for making profit on trend and flat markets.

The article provides the description of the technology aimed at increasing the effectiveness of any automated trading system. It provides a brief explanation of the idea, as well as its underlying basics, possibilities and disadvantages.

In this article, I will create the collection class of Depths of Market of all symbols and start developing the functionality for working with the MQL5.com Signals service by creating the signal object class.

This article starts a new series about the creation of the DoEasy library for easy and fast program development. In the current article, we will implement the library functionality for accessing and working with symbol timeseries data. We are going to create the Bar object storing the main and extended timeseries bar data, and place bar objects to the timeseries list for convenient search and sorting of the objects.

This article continues the series of publications on a universal Expert Advisor model. This part describes in detail the original event model based on centralized data processing, and considers the structure of the CStrategy base class of the engine.

This article shows you how to build an Object-Oriented Expert Advisor from scratch, from conceiving a theoretical trading idea to programming a MQL5 EA that makes that idea real in the empirical world. Learning by doing is IMHO a solid approach to succeed, so I am showing a practical example in order for you to see how you can order your ideas to finally code your Forex robots. My goal is also to invite you to adhere the OO principles.