Articles with examples of trading robots developed in MQL5

Efficient extraction and integration of long-term dependencies and short-term features remain an important task in time series analysis. Their proper understanding and integration are necessary to create accurate and reliable predictive models.

We have earlier discussed some types of neural network implementations. In the considered networks, the same operations are repeated for each neuron. A logical further step is to utilize multithreaded computing capabilities provided by modern technology in an effort to speed up the neural network learning process. One of the possible implementations is described in this article.

Today's article shows intermediate MQL5 programmers how they can get more profit from their linear trading systems (Fixed Lot) by easily implementing the so-called technique of exponentiation. This is because the resulting equity curve growth is then geometric, or exponential, taking the form of a parabola. Specifically, we will implement a practical MQL5 variant of the Fixed Fractional position sizing developed by Ralph Vince.

The optimization process can require significant resources of your computer or even of the MQL5 Cloud Network test agents. This article comprises some simple ideas that I use for work facilitation and improvement of the MetaTrader 5 Strategy Tester. I got these ideas from the documentation, forum and articles.

In this article, I will show the criteria to be used when selecting a system or a signal for investing your funds, as well as describe the optimal approach to the development of trading systems and highlight the importance of this matter in Forex trading.

In the new version of the library, all controls will be drawn on separate graphical objects of the OBJ_BITMAP_LABEL type. We will also continue to describe the optimization of code: changes in the core classes of the library will be discussed.

The previous articles contain the implementation of the classes for creating constituent parts of the main menu. Now, it is time to take a close look at the event handlers in the principle base classes and in the classes of the created controls. We will also pay special attention to managing the state of the chart depending on the location of the mouse cursor.

This time we are going to create a multi-currency Expert Advisor with a trading algorithm based on work with the pending orders Buy Stop and Sell Stop. This article considers the following matters: trading in a specified time range, placing/modifying/deleting pending orders, checking if the last position was closed at Take Profit or Stop Loss and control of the deals history for each symbol.

Today we will learn how to link an MetaTrader 5 terminal with Twitter so that you can tweet your EAs' trading signals. We are developing a Social Decision Support System in PHP based on a RESTful web service. This idea comes from a particular conception of automatic trading called computer-assisted trading. We want the cognitive abilities of human traders to filter those trading signals which otherwise would be automatically placed on the market by the Expert Advisors.

This article explains the idea of multi-mode trading robot programming in MQL5. Every mode is implemented with the object-oriented approach. Instances of both mode classes hierarchy and classes for testing are provided. Multi-mode programming of trading robots is supposed to take into account all peculiarities of every operational mode of an EA written in MQL5. Functions and enumeration are created for identifying the mode.

In the article, I will start developing the functionality for working with the Depth of Market. I will also create the class of the Depth of Market abstract order object and its descendants.

The article guides in demonstrating an automated algorithm based on EMA Crossovers for MetaTrader 5. Detailed information on all aspects of demonstrating an Expert Advisor in MQL5 and testing it in MetaTrader 5 - from analyzing price range behaviors to risk management.

In order to develop an expert to participate in Automated Trading Championship 2010, let's use a template of ready expert advisor. Even novice MQL5 programmer will be capable of this task, because for your strategies the basic classes, functions, templates are already developed. It's enough to write a minimal amount of code to implement your trading idea.

An automated system will not be successful without proper security. However, security will not be ensured without a good understanding of certain things. In this article, we will explore why achieving maximum security in automated systems is such a challenge.

In the previous chapters of the eighth part of the series, our library has been reinforced by several classes for developing mouse pointers, calendars and tree views. The current article deals with the file navigator control that can also be used as part of an MQL application graphical interface.

In the article "Dr. Tradelove..." we created an Expert Advisor, which independently optimizes parameters of a pre-selected trading system. Moreover, we decided to create an Expert Advisor that can not only optimize parameters of one trading system underlying the EA, but also select the best one of several trading systems. Let's see what can come of it...

Volatility based breakout system identifies market ranges, then trades when price breaks above or below those levels, filtered by volatility measures such as ATR. This approach helps capture strong directional moves.

The article regards spindle chart plotting and its usage in trading strategies and experts. First let's discuss the chart's appearance, plotting and connection with japanese candlestick chart. Next we analyze the indicator's implementation in the source code in the MQL5 language. Let's test the expert based on indicator and formulate the trading strategy.

In this article, we develop a Trendline Breakout System in MQL5 that identifies support and resistance trendlines using swing points, validated by R-squared goodness of fit and angle constraints, to automate breakout trades. Our plan is to detect swing highs and lows within a specified lookback period, construct trendlines with a minimum number of touch points, and validate them using R-squared metrics and angle constraints to ensure reliability.

As the library grows, its code must be optimized again in order to reduce its size. The version of the library described in this article has become even more object-oriented. This made the code easier to learn. A detailed description of the latest changes will allow the readers to develop the library independently based on their own needs.

If you think automated systems are simple, then you probably don't fully understand what it takes to create them. In this article, we will talk about the problem that kills a lot of Expert Advisors. The indiscriminate triggering of orders is a possible solution to this problem.

In this article, we develop a Trendline Breakout System in MQL5 that identifies support and resistance trendlines using swing points, validated by R-squared goodness of fit and angle constraints, to automate breakout trades. Our plan is to detect swing highs and lows within a specified lookback period, construct trendlines with a minimum number of touch points, and validate them using R-squared metrics and angle constraints to ensure reliability.

The previous chapter of part VIII on graphical interfaces has focused on the elements of static and drop-down calendar. The second chapter will be dedicated to an equally complex element — a tree view, that is included in every complete library used for creating graphical interfaces. A tree view implemented in this article contains multiple flexible settings and modes, thus allowing to adjust this element of control to your needs.

Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. Our EA in its current state can work in any situation but it is not yet ready for automation. We still have to work on a few points.