Articles on the MQL5 programming and use of trading robots

This article is a continuation of the series of articles about deep neural networks. Here we will consider selecting samples (removing noise), reducing the dimensionality of input data and dividing the data set into the train/val/test sets during data preparation for training the neural network.

The second article of the series about deep neural networks will consider the transformation and choice of predictors during the process of preparing data for training a model.

This series of articles continues exploring deep neural networks (DNN), which are used in many application areas including trading. Here new dimensions of this theme will be explored along with testing of new methods and ideas using practical experiments. The first article of the series is dedicated to preparing data for DNN.

This article discusses an implementation of stop levels in an expert advisor in order to make it compatible with the two platforms MetaTrader 4 and MetaTrader 5.

The article analyzes the application of the Bayes' formula for increasing the reliability of trading systems by means of using signals from multiple independent indicators. Theoretical calculations are verified with a simple universal EA, configured to work with arbitrary indicators.

This article discusses the implementation of various methods of time filtering a cross-platform expert advisor. The time filter classes are responsible for checking whether or not a given time falls under a certain time configuration setting.

This article discusses the implementation of money management method for a cross-platform expert advisor. The money management classes are responsible for the calculation of the lot size to be used for the next trade to be entered by the expert advisor.

The article considers the ideology and methodology of building a recommendatory system for time-efficient trading by combining the capabilities of forecasting with the singular spectrum analysis (SSA) and important machine learning method on the basis of Bayes' Theorem.

This article discusses the CSignal and CSignals classes which will be used in cross-platform expert advisors. It examines the differences between MQL4 and MQL5 on how particular data needed for evaluation of trade signals are accessed to ensure that the code written will be compatible with both compilers.

This article discusses the creation of an order manager for a cross-platform expert advisor. The order manager is responsible for the entry and exit of orders or positions entered by the expert, as well as for keeping an independent record of such trades that is usable for both versions.

The article provides a brief overview of ten trend following strategies, as well as their testing results and comparative analysis. Based on the obtained results, we draw a general conclusion about the appropriateness, advantages and disadvantages of trend following trading.

The article describes the development and implementation of a class for sending signals based on pivots — reversal levels. This class is used to form a strategy applying the Standard Library. Improving the pivot strategy by adding filters is considered.

The article offers a simple emulator of the MetaTrader 5 trading environment for MetaTrader 4. The emulator implements migration and adjustment of trade classes of the Standard Library. As a result, Expert Advisors generated in the MetaTrader 5 Wizard can be compiled and executed in MetaTrader 4 without changes.

Automation of trading strategies involving graphical patterns requires the ability to search for extreme points on the charts for further processing and interpretation. Existing tools do not always provide such an ability. The algorithms described in the article allow finding all extreme points on charts. The tools discussed here are equally efficient both during trends and flat movements. The obtained results are not strongly affected by a selected timeframe and are only defined by a specified scale.

The article features formalized rules of two trading strategies 'Turtle Soup' and 'Turtle Soup Plus One' from Street Smarts: High Probability Short-Term Trading Strategies by Linda Bradford Raschke and Laurence A. Connors. The strategies described in the book are quite popular. But it is important to understand that the authors have developed them based on the 15...20 year old market behavior.

Is it possible to develop an Expert Advisor able to optimize position open and close conditions at regular intervals according to the code commands? What happens if we implement a neural network (multilayer perceptron) in the form of a module to analyze history and provide strategy? We can make the EA optimize a neural network monthly (weekly, daily or hourly) and continue its work afterwards. Thus, we can develop a self-optimizing EA.

MetaTrader 4 and MetaTrader 5 uses different conventions in processing trade requests. This article discusses the possibility of using a class object that can be used to represent the trades processed by the server, in order for a cross-platform expert advisor to further work on them, regardless of the version of the trading platform and mode being used.

The article describes the process of developing and implementing a class for sending signals based on the moving channels. Each of the signal version is followed by a trading strategy with testing results. Classes of the Standard Library are used for creating derived classes.

When you subscribe to signals, such situation may occur: your trade account has a leverage of 1:100, the provider has a leverage of 1:500 and trades using the minimal lot, and your trade balances are virtually equal — but the copy ratio will comprise only 10% to 15%. This article describes how to increase the copy rate in such cases.

Profitability of trading systems is defined not only by logic and precision of analyzing the financial instrument dynamics, but also by the quality of the performance algorithm of this logic. False trigger is typical for low quality performance of the main logic of a trading robot. Ways of solving the specified problem are considered in this article.

There exists some components in the MQL5 Standard Library that may prove to be useful in the MQL4 version of cross-platform expert advisors. This article deals with a method of making certain components of the MQL5 Standard Library compatible with the MQL4 compiler.

This article details a method by which cross-platform expert advisors can be developed faster and easier. The proposed method consolidates the features shared by both versions into a single class, and splits the implementation on derived classes for incompatible features.

Before any product is published in the Market, it must undergo compulsory preliminary checks in order to ensure a uniform quality standard. This article considers the most frequent errors made by developers in their technical indicators and trading robots. An also shows how to self-test a product before sending it to the Market.

The article describes the application of text files for storing dynamic objects, arrays and other variables used as properties of Expert Advisors, indicators and scripts. The files serve as a convenient addition to the functionality of standard tools offered by MQL languages.

Many traders on Moscow Exchange would like to automate their trading algorithms, but they do not know where to start. The MQL5 language offers a huge range of trading functions, and it additionally provides ready classes that help users to make their first steps in algo trading.

The number of trading robots used on the currency markets has significantly increased recently. They employ various concepts and strategies, however, none of them has yet succeeded to create a win-win sample of artificial intelligence. Therefore, many traders remain committed to manual trading. But even for such specialists, robotic assistants or, so called, trading panels, are created. This article is yet another example of creating a trading panel from scratch.

This article covers the main principles set fourth in evolutionary algorithms, their variety and features. We will conduct an experiment with a simple Expert Advisor used as an example to show how our trading system benefits from optimization. We will consider software programs that implement genetic, evolutionary and other types of optimization, and provide examples of application when optimizing a predictor set and parameters of the trading system.

This article is a continuation of previous articles on deep neural network and predictor selection. Here we will cover features of a neural network initiated by Stacked RBM, and its implementation in the "darch" package.

It is essential to detect whether a market is flat or not for many strategies. Using the well known ADX we demonstrate how we can use the Strategy Tester not only to optimize this indicator for our specific purpose, but as well we can decide whether this indicator will meet our needs and get to know the average range of the flat and trend markets which might be quite important to determine stops and targets of the markets.

This article presents a method of programming the equidistant channel system. Certain details of building such channels are being considered here. Channel typification is provided, and a universal type of moving channels' method is suggested. Object-oriented programming (OOP) is used for code implementation.

The article details TD points and TD lines discovered by Thomas DeMark. Their practical implementation is revealed. In addition to that, a process of writing three indicators and two Expert Advisors using the concepts of Thomas DeMark is demonstrated.

The article describes the rules of the trading system by Bill Williams, the procedure of application for a developed MQL5 module to search and mark patterns of this system on the chart, automated trading with found patterns, and also presents the results of testing on various trading instruments.

A logically complete market theory that would cover all types and varieties of markets for goods and services, micro and macro markets like Forex, hasn't been available until now. This article covers the essence of a new market theory based on the profit analysis, reveals patterns of the current price change and the principle of the mechanism operation that allows the price to find its most optimal value by forming a chain of virtual prices that can develop the controlling influence on the actual price. Mechanisms of formation and change of market trends are also identified here.

What should your program do, if graphic control panels have been removed or modified by someone else? In this article we will show you how not to have "ownerless" objects on the chart, and how not to lose control over them in cases of renaming or deleting programmatically created objects after the application is deleted.

This article focuses on specifics of choice, preconditioning and evaluation of the input variables (predictors) for use in machine learning models. New approaches and opportunities of deep predictor analysis and their influence on possible overfitting of models will be considered. The overall result of using models largely depends on the result of this stage. We will analyze two packages offering new and original approaches to the selection of predictors.

This article describes a process of creating an Expert Advisor for MetaTrader 4 based on the Engulfing pattern, as well as the pattern recognition principle, rules of setting pending orders and stop orders. The results of testing and optimization are provided for your information.

This article presents an alternative method of GUI creation based on layouts and containers, using one layout manager — the CGrid class. The CGrid class is an auxiliary control that acts as a container for other containers and controls using a grid layout.

The article describes the development of a MetaTrader 4 Expert Advisor based on the Inside Bar strategy, including Inside Bar detection principles, as well as pending and stop order setting rules. Test and optimization results are provided as well.

This article shows how price action and the monitoring of support and resistance levels can be used for well-timed market entry. It discusses a trading system that effectively combines the two for the determination of trade setups. Corresponding MQL4 code is explained that can be utilized in the EAs based on these trading concepts.

This step-by-step guide provides tips and tricks for better understanding and searching for a required product. The article makes an attempt to puzzle out different methods of searching for an appropriate product, sorting out unwanted products, determining product efficiency and essentiality for you.