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MQL4 and MQL5 Programming Articles
Study the MQL5 language for programming trading strategies in numerous published articles mostly written by you - the community members. The articles are grouped into categories to help you quicker find answers to any questions related to programming: Integration, Tester, Trading Strategies, etc.
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Neural networks made easy (Part 7): Adaptive optimization methods
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
Analyzing charts using DeMark Sequential and Murray-Gann levels
Thomas DeMark Sequential is good at showing balance changes in the price movement. This is especially evident if we combine its signals with a level indicator, for example, Murray levels. The article
Gradient boosting in transductive and active machine learning
In this article, we will consider active machine learning methods utilizing real data, as well discuss their pros and cons. Perhaps you will find these methods useful and will include them in your
Neural networks made easy (Part 6): Experimenting with the neural network learning rate
We have previously considered various types of neural networks along with their implementations. In all cases, the neural networks were trained using the gradient decent method, for which we need to
Optimal approach to the development and analysis of trading systems
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
Timeseries in DoEasy library (part 57): Indicator buffer data object
In the article, develop an object which will contain all data of one buffer for one indicator. Such objects will be necessary for storing serial data of indicator buffers. With their help, it will be
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
Practical application of neural networks in trading. Python (Part I)
In this article, we will analyze the step-by-step implementation of a trading system based on the programming of deep neural networks in Python. This will be performed using the TensorFlow machine
Neural networks made easy (Part 5): Multithreaded calculations in OpenCL
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
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
Neural networks made easy (Part 4): Recurrent networks
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
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
Grid and martingale: what are they and how to use them?
In this article, I will try to explain in detail what grid and martingale are, as well as what they have in common. Besides, I will try to analyze how viable these strategies really are. The article
Brute force approach to pattern search
In this article, we will search for market patterns, create Expert Advisors based on the identified patterns, and check how long these patterns remain valid, if they ever retain their validity
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
Parallel Particle Swarm Optimization
The article describes a method of fast optimization using the particle swarm algorithm. It also presents the method implementation in MQL, which is ready for use both in single-threaded mode inside an
Neural networks made easy (Part 3): Convolutional networks
As a continuation of the neural network topic, I propose considering convolutional neural networks. This type of neural network are usually applied to analyzing visual imagery. In this article, we
Continuous walk-forward optimization (Part 8): Program improvements and fixes
The program has been modified based on comments and requests from users and readers of this article series. This article contains a new version of the auto optimizer. This version implements requested
Basic math behind Forex trading
The article aims to describe the main features of Forex trading as simply and quickly as possible, as well as share some basic ideas with beginners. It also attempts to answer the most tantalizing
Advanced resampling and selection of CatBoost models by brute-force method
This article describes one of the possible approaches to data transformation aimed at improving the generalizability of the model, and also discusses sampling and selection of CatBoost models
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
A scientific approach to the development of trading algorithms
The article considers the methodology for developing trading algorithms, in which a consistent scientific approach is used to analyze possible price patterns and to build trading algorithms based on
CatBoost machine learning algorithm from Yandex with no Python or R knowledge required
The article provides the code and the description of the main stages of the machine learning process using a specific example. To obtain the model, you do not need Python or R knowledge. Furthermore
Timeseries in DoEasy library (part 50): Multi-period multi-symbol standard indicators with a shift
In the article, let’s improve library methods for correct display of multi-symbol multi-period standard indicators, which lines are displayed on the current symbol chart with a shift set in the
Custom symbols: Practical basics
The article is devoted to the programmatic generation of custom symbols which are used to demonstrate some popular methods for displaying quotes. It describes a suggested variant of minimally invasive
Neural networks made easy (Part 2): Network training and testing
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
What is a trend and is the market structure based on trend or flat?
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
Websockets for MetaTrader 5
Before the introduction of the network functionality provided with the updated MQL5 API, MetaTrader programs have been limited in their ability to connect and interface with websocket based services
Price series discretization, random component and noise
We usually analyze the market using candlesticks or bars that slice the price series into regular intervals. Doesn't such discretization method distort the real structure of market movements
Timeseries in DoEasy library (part 49): Multi-period multi-symbol multi-buffer standard indicators
In the current article, I will improve the library classes to implement the ability to develop multi-symbol multi-period standard indicators requiring several indicator buffers to display their data
Gradient Boosting (CatBoost) in the development of trading systems. A naive approach
Training the CatBoost classifier in Python and exporting the model to mql5, as well as parsing the model parameters and a custom strategy tester. The Python language and the MetaTrader 5 library are
Using cryptography with external applications
In this article, we consider encryption/decryption of objects in MetaTrader and in external applications. Our purpose is to determine the conditions under which the same results will be obtained with
Timeseries in DoEasy library (part 48): Multi-period multi-symbol indicators on one buffer in a subwindow
The article considers an example of creating multi-symbol multi-period standard indicators using a single indicator buffer for construction and working in the indicator subwindow. I am going to
A system of voice notifications for trade events and signals
Nowadays, voice assistants play a prominent role in human life, as we often use navigators, voice search and translators. In this article, I will try to develop a simple and user friendly system of
Timeseries in DoEasy library (part 47): Multi-period multi-symbol standard indicators
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
On Methods to Detect Overbought/Oversold Zones. Part I
Overbought/oversold zones characterize a certain state of the market, differentiating through weaker changes in the prices of securities. This adverse change in the synamics is pronounced most at the
Probability theory and mathematical statistics with examples (part I): Fundamentals and elementary theory
Trading is always about making decisions in the face of uncertainty. This means that the results of the decisions are not quite obvious at the time these decisions are made. This entails the
Quick Manual Trading Toolkit: Working with open positions and pending orders
In this article, we will expand the capabilities of the toolkit: we will add the ability to close trade positions upon specific conditions and will create tables for controlling market and pending
Timeseries in DoEasy library (part 46): Multi-period multi-symbol indicator buffers
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