Algorithmic Trading Articles for Trading systems

Can Heiken-Ashi Combined With Moving Averages Provide Good Signals Together?

Combinations of strategies may offer better opportunities. We can combine indicators or patterns together, or even better, indicators with patterns, so that we get an extra confirmation factor. Moving averages help us confirm and ride the trend. They are the most known technical indicators and this is because of their simplicity and their proven track record of adding value to analyses.

Improve Your Trading Charts With Interactive GUI's in MQL5 (Part II): Movable GUI (II)

Unlock the potential of dynamic data representation in your trading strategies and utilities with our in-depth guide to creating movable GUIs in MQL5. Delve into the fundamental principles of object-oriented programming and discover how to design and implement single or multiple movable GUIs on the same chart with ease and efficiency.

Creating Graphical Panels Became Easy in MQL5

In this article, we will provide a simple and easy guide to anyone who needs to create one of the most valuable and helpful tools in trading which is the graphical panel to simplify and ease doing tasks around trading which helps to save time and focus more on your trading process itself without any distractions.

Category Theory in MQL5 (Part 12): Orders

This article which is part of a series that follows Category Theory implementation of Graphs in MQL5, delves in Orders. We examine how concepts of Order-Theory can support monoid sets in informing trade decisions by considering two major ordering types.

Rebuy algorithm: Multicurrency trading simulation

In this article, we will create a mathematical model for simulating multicurrency pricing and complete the study of the diversification principle as part of the search for mechanisms to increase the trading efficiency, which I started in the previous article with theoretical calculations.

Understanding MQL5 Object-Oriented Programming (OOP)

As developers, we need to learn how to create and develop software that can be reusable and flexible without duplicated code especially if we have different objects with different behaviors. This can be smoothly done by using object-oriented programming techniques and principles. In this article, we will present the basics of MQL5 Object-Oriented programming to understand how we can use principles and practices of this critical topic in our software.

Category Theory in MQL5 (Part 11): Graphs

This article is a continuation in a series that look at Category Theory implementation in MQL5. In here we examine how Graph-Theory could be integrated with monoids and other data structures when developing a close-out strategy to a trading system.

Creating an EA that works automatically (Part 15): Automation (VII)

To complete this series of articles on automation, we will continue discussing the topic of the previous article. We will see how everything will fit together, making the EA run like clockwork.

In this article we continue the development of the CArima class for building ARIMA models by adding intuitive methods that enable forecasting.

In this article, I will create the signal collection class of the MQL5.com Signals service with the functions for managing signals. Besides, I will improve the Depth of Market snapshot object class for displaying the total DOM buy and sell volumes.

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.

In this article, I will create two classes (the class of DOM snapshot object and the class of DOM snapshot series object) and test creation of the DOM data series.

Creating an EA that works automatically (Part 14): Automation (VI)

In this article, we will put into practice all the knowledge from this series. We will finally build a 100% automated and functional system. But before that, we still have to learn one last detail.

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.

In this article, I will implement updating tick data in real time and prepare the symbol object class for working with Depth of Market (DOM itself is to be implemented in the next article).

Since a program may use different symbols in its work, a separate list should be created for each of them. In this article, I will combine such lists into a tick data collection. In fact, this will be a regular list based on the class of dynamic array of pointers to instances of CObject class and its descendants of the Standard library.

Multilayer perceptron and backpropagation algorithm (Part 3): Integration with the Strategy Tester - Overview (I).

The multilayer perceptron is an evolution of the simple perceptron which can solve non-linear separable problems. Together with the backpropagation algorithm, this neural network can be effectively trained. In Part 3 of the Multilayer Perceptron and Backpropagation series, we'll see how to integrate this technique into the Strategy Tester. This integration will allow the use of complex data analysis aimed at making better decisions to optimize your trading strategies. In this article, we will discuss the advantages and problems of this technique.

From this article on, start creating library functionality to work with price data. Today, create an object class which will store all price data which arrived with yet another tick.

Automated exchange grid trading using stop pending orders on Moscow Exchange (MOEX)

The article considers the grid trading approach based on stop pending orders and implemented in an MQL5 Expert Advisor on the Moscow Exchange (MOEX). When trading in the market, one of the simplest strategies is a grid of orders designed to "catch" the market price.

Timeseries in DoEasy library (part 56): Custom indicator object, get data from indicator objects in the collection

The article considers creation of the custom indicator object for the use in EAs. Let’s slightly improve library classes and add methods to get data from indicator objects in EAs.

Timeseries in DoEasy library (part 55): Indicator collection class

The article continues developing indicator object classes and their collections. For each indicator object create its description and correct collection class for error-free storage and getting indicator objects from the collection list.

Timeseries in DoEasy library (part 54): Descendant classes of abstract base indicator

The article considers creation of classes of descendant objects of base abstract indicator. Such objects will provide access to features of creating indicator EAs, collecting and getting data value statistics of various indicators and prices. Also, create indicator object collection from which getting access to properties and data of each indicator created in the program will be possible.

Timeseries in DoEasy library (part 53): Abstract base indicator class

The article considers creation of an abstract indicator which further will be used as the base class to create objects of library’s standard and custom indicators.

Timeseries in DoEasy library (part 52): Cross-platform nature of multi-period multi-symbol single-buffer standard indicators

In the article, consider creation of multi-symbol multi-period standard indicator Accumulation/Distribution. Slightly improve library classes with respect to indicators so that, the programs developed for outdated platform MetaTrader 4 based on this library could work normally when switching over to MetaTrader 5.

How to detect trends and chart patterns using MQL5

In this article, we will provide a method to detect price actions patterns automatically by MQL5, like trends (Uptrend, Downtrend, Sideways), Chart patterns (Double Tops, Double Bottoms).

Rebuy algorithm: Math model for increasing efficiency

In this article, we will use the rebuy algorithm for a deeper understanding of the efficiency of trading systems and start working on the general principles of improving trading efficiency using mathematics and logic, as well as apply the most non-standard methods of increasing efficiency in terms of using absolutely any trading system.

Timeseries in DoEasy library (part 51): Composite multi-period multi-symbol standard indicators

In the article, complete development of objects of multi-period multi-symbol standard indicators. Using Ichimoku Kinko Hyo standard indicator example, analyze creation of compound custom indicators which have auxiliary drawn buffers for displaying data on the chart.

In this article, I will start developing the methods of working with standard indicators, which will ultimately allow creating multi-symbol multi-period standard indicators based on library classes. Besides, I will add the "Skipped bars" event to the timeseries classes and eliminate excessive load from the main program code by moving the library preparation functions to CEngine class.

In this article, I am going to improve the classes of indicator buffer objects to work in the multi-symbol mode. This will pave the way for creating multi-symbol multi-period indicators in custom programs. I will add the missing functionality to the calculated buffer objects allowing us to create multi-symbol multi-period standard indicators.

In this article, I will start the improvement of the indicator buffer objects and collection class for working in multi-period and multi-symbol modes. I am going to consider the operation of buffer objects for receiving and displaying data from any timeframe on the current symbol chart.

In this article, we start the development of the indicator buffer classes for the DoEasy library. We will create the base class of the abstract buffer which is to be used as a foundation for the development of different class types of indicator buffers.

The article deals with applying DoEasy library for creating multi-symbol multi-period indicators. We are going to prepare the library classes to work within indicators and test creating timeseries to be used as data sources in indicators. We will also implement creating and sending timeseries events.

How to create a custom Donchian Channel indicator using MQL5

There are many technical tools that can be used to visualize a channel surrounding prices, One of these tools is the Donchian Channel indicator. In this article, we will learn how to create the Donchian Channel indicator and how we can trade it as a custom indicator using EA.

Experiments with neural networks (Part 6): Perceptron as a self-sufficient tool for price forecast

The article provides an example of using a perceptron as a self-sufficient price prediction tool by showcasing general concepts and the simplest ready-made Expert Advisor followed by the results of its optimization.

How to use MQL5 to detect candlesticks patterns

A new article to learn how to detect candlesticks patterns on prices automatically by MQL5.

Learn how to design a trading system by Fibonacci

In this article, we will continue our series of creating a trading system based on the most popular technical indicator. Here is a new technical tool which is the Fibonacci and we will learn how to design a trading system based on this technical indicator.

Experiments with neural networks (Part 5): Normalizing inputs for passing to a neural network

Neural networks are an ultimate tool in traders' toolkit. Let's check if this assumption is true. MetaTrader 5 is approached as a self-sufficient medium for using neural networks in trading. A simple explanation is provided.

Creating an EA that works automatically (Part 11): Automation (III)

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.

Category Theory in MQL5 (Part 6): Monomorphic Pull-Backs and Epimorphic Push-Outs

Category Theory is a diverse and expanding branch of Mathematics which is only recently getting some coverage in the MQL5 community. These series of articles look to explore and examine some of its concepts & axioms with the overall goal of establishing an open library that provides insight while also hopefully furthering the use of this remarkable field in Traders' strategy development.

Creating an EA that works automatically (Part 12): Automation (IV)

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.

Can Heiken-Ashi Combined With Moving Averages Provide Good Signals Together?

Improve Your Trading Charts With Interactive GUI's in MQL5 (Part II): Movable GUI (II)

Creating Graphical Panels Became Easy in MQL5

Category Theory in MQL5 (Part 12): Orders

Rebuy algorithm: Multicurrency trading simulation

Understanding MQL5 Object-Oriented Programming (OOP)

Category Theory in MQL5 (Part 11): Graphs

Creating an EA that works automatically (Part 15): Automation (VII)

Forecasting with ARIMA models in MQL5

Other classes in DoEasy library (Part 66): MQL5.com Signals collection class

Prices and Signals in DoEasy library (Part 65): Depth of Market collection and the class for working with MQL5.com Signals

Prices in DoEasy library (Part 64): Depth of Market, classes of DOM snapshot and snapshot series objects

Creating an EA that works automatically (Part 14): Automation (VI)

Prices in DoEasy library (part 63): Depth of Market and its abstract request class

Prices in DoEasy library (part 62): Updating tick series in real time, preparation for working with Depth of Market

Prices in DoEasy library (part 61): Collection of symbol tick series

Multilayer perceptron and backpropagation algorithm (Part 3): Integration with the Strategy Tester - Overview (I).

Prices in DoEasy library (part 59): Object to store data of one tick

Automated exchange grid trading using stop pending orders on Moscow Exchange (MOEX)

Timeseries in DoEasy library (part 56): Custom indicator object, get data from indicator objects in the collection

Timeseries in DoEasy library (part 55): Indicator collection class

Timeseries in DoEasy library (part 54): Descendant classes of abstract base indicator

Timeseries in DoEasy library (part 53): Abstract base indicator class

Timeseries in DoEasy library (part 52): Cross-platform nature of multi-period multi-symbol single-buffer standard indicators

How to detect trends and chart patterns using MQL5

Rebuy algorithm: Math model for increasing efficiency

Timeseries in DoEasy library (part 51): Composite multi-period multi-symbol standard indicators

Timeseries in DoEasy library (part 47): Multi-period multi-symbol standard indicators

Timeseries in DoEasy library (part 46): Multi-period multi-symbol indicator buffers

Timeseries in DoEasy library (part 45): Multi-period indicator buffers

Timeseries in DoEasy library (part 42): Abstract indicator buffer object class

Timeseries in DoEasy library (part 39): Library-based indicators - preparing data and timeseries events

How to create a custom Donchian Channel indicator using MQL5

Experiments with neural networks (Part 6): Perceptron as a self-sufficient tool for price forecast

How to use MQL5 to detect candlesticks patterns

Learn how to design a trading system by Fibonacci

Experiments with neural networks (Part 5): Normalizing inputs for passing to a neural network

Creating an EA that works automatically (Part 11): Automation (III)

Category Theory in MQL5 (Part 6): Monomorphic Pull-Backs and Epimorphic Push-Outs

Creating an EA that works automatically (Part 12): Automation (IV)