Articles on trading system automation in MQL5

The article is devoted to the practical application of the fuzzy logic concept for financial markets analysis. We propose the example of the indicator generating signals based on two fuzzy rules based on Envelopes indicator. The developed indicator uses several indicator buffers: 7 buffers for calculations, 5 buffers for the charts display and 2 color buffers.

Surfing the Internet, it is easy to find many strategies, which will give you a number of various recommendations. Let’s take an insider’s approach and look into the process of strategy creation, based on the differences in timezones on different continents.

In this article, we will continue our series about designing a trading system using the most popular indicators and we will talk about the average directional index (ADX) indicator. We will learn this indicator in detail to understand it well and we will learn how we to use it through a simple strategy. By learning something deeply we can get more insights and we can use it better.

In the previous articles, we started creating a large cross-platform library simplifying the development of programs for MetaTrader 5 and MetaTrader 4 platforms. We already have collections of historical orders and deals, market orders and positions, as well as the class for convenient selection and sorting of orders. In this part, we will continue the development of the base object and teach the Engine Library to track trading events on the account.

Expert Advisor Visual Wizard for MetaTrader 5 provides a highly intuitive graphical environment with a comprehensive set of predefined trading blocks that let you design Expert Advisors in minutes. The click, drag and drop approach of Expert Advisor Visual Wizard allows you to create visual representations of forex trading strategies and signals as you would with pencil and paper. These trading diagrams are analyzed automatically by Molanis’ MQL5 code generator that transforms them into ready to use Expert Advisors. The interactive graphical environment simplifies the design process and eliminates the need to write MQL5 code.

Genetic (evolutionary) algorithms are used for optimization purposes. An example of such purpose can be neuronet learning, i.e., selection of such weight values that allow reaching the minimum error. At this, the genetic algorithm is based on the random search method.

The article gives formulas and the calculation order for data shown in the Tester report.

In this new article from our series for learning how to design trading systems, I will present the Commodities Channel Index (CCI), explain its specifics, and share with you how to create a trading system based on this indicator.

In this article, we will consider the class of displaying text messages. Currently, we have a sufficient number of different text messages. It is time to re-arrange the methods of their storage, display and translation of Russian or English messages to other languages. Besides, it would be good to introduce convenient ways of adding new languages to the library and quickly switching between them.

It is impossible to get a truly stable algorithm if we use optimization based on historical data to select parameters. A stable algorithm should be aware of what parameters are needed when working on any trading instrument at any time. It should not forecast or guess, it should know for sure.

In this article, we continue to dwell on reversing techniques. We will try to reduce the maximum balance drawdown till an acceptable level for the instruments considered earlier. We will see if the measures will reduce the profit. We will also check how the reversing method performs on other markets, including stock, commodity, index, ETF and agricultural markets. Attention, the article contains a lot of images!

This article suggests a variant of an adaptive system that consists of many strategies, each of which performs its own "virtual" trade operations. Real trading is performed in accordance with the signals of a most profitable strategy at the moment. Thanks to using of the object-oriented approach, classes for working with data and trade classes of the Standard library, the architecture of the system appeared to be simple and scalable; now you can easily create and analyze the adaptive systems that include hundreds of trade strategies.

There is no trouble finding the Holy Grail of testing, it is however much more difficult to get rid of it. This article addresses the selection of the Expert Advisor operating parameters with automated group processing of optimisation and testing results upon maximum utilisation of the Terminal performance capabilities and minimum end user load.

The article demonstrates the capabilities and potential of a well-known mathematical method coupled with visual thinking and an "out of the box" market outlook. On the one hand, it serves to attract the attention of a wide audience as it can get the creative minds to reconsider the trading paradigm as such. And on the other, it can give rise to alternative developments and program code implementations regarding a wide range of tools for analysis and forecasting.

We continue the development of the library functionality featuring trading using pending requests. We have already implemented sending conditional trading requests for opening positions and placing pending orders. In the current article, we will implement conditional position closure – full, partial and closing by an opposite position.

The problem of calculation of the total position volume of the specified symbol and magic number is considered in this article. The proposed method requests only the minimum necessary part of the history of deals, finds the closest time when the total position was equal to zero, and performs the calculations with the recent deals. Working with global variables of the client terminal is also considered.

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.

The article will help newbies in trading to create flexibly adjustable Expert Advisors.

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

In previous articles, we used stochastic gradient descent to train a neural network using the same learning rate for all neurons within the network. In this article, I propose to look towards adaptive learning methods which enable changing of the learning rate for each neuron. We will also consider the pros and cons of this approach.

In this article, we continue our learning series — this time we will learn how to design a trading system using one of the most popular and useful indicators, which is the Stochastic Oscillator indicator, to build a new block in our knowledge of basics.

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.

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.

This is the last article within the series devoted to the Reversing trading strategy. Here we will try to solve the problem, which caused the testing results instability in previous articles. We will also develop and test our own algorithm for manual trading in any market using the reversing strategy.

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.

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.

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.

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.

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!

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.

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 my previous article, I mentioned the importance of identifying the trend which is the direction of prices. In this article I will share one of the most important concepts and indicators which is the Momentum indicator. I will share how to design a trading system based on this Momentum indicator.

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.

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.