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Multilayer perceptron and backpropagation algorithm
Multilayer perceptron and backpropagation algorithm
The popularity of these two methods grows, so a lot of libraries have been developed in Matlab, R, Python, C++ and others, which receive a training set as input and automatically create an appropriate network for the problem. Let us try to understand how the basic neural network type works (including single-neuron perceptron and multilayer perceptron). We will consider an exciting algorithm which is responsible for network training - gradient descent and backpropagation. Existing complex models are often based on such simple network models.
Useful and exotic techniques for automated trading
Useful and exotic techniques for automated trading
In this article I will demonstrate some very interesting and useful techniques for automated trading. Some of them may be familiar to you. I will try to cover the most interesting methods and will explain why they are worth using. Furthermore, I will show what these techniques are apt to in practice. We will create Expert Advisors and test all the described techniques using historic quotes.
Studying the CCanvas Class. How to Draw Transparent Objects
Studying the CCanvas Class. How to Draw Transparent Objects
Do you need more than awkward graphics of moving averages? Do you want to draw something more beautiful than a simple filled rectangle in your terminal? Attractive graphics can be drawn in the terminal. This can be implemented through the CСanvas class, which is used for creating custom graphics. With this class you can implement transparency, blend colors and produce the illusion of transparency by means of overlapping and blending colors.
Neural networks made easy (Part 10): Multi-Head Attention
Neural networks made easy (Part 10): Multi-Head Attention
We have previously considered the mechanism of self-attention in neural networks. In practice, modern neural network architectures use several parallel self-attention threads to find various dependencies between the elements of a sequence. Let us consider the implementation of such an approach and evaluate its impact on the overall network performance.
Neural networks made easy (Part 9): Documenting the work
Neural networks made easy (Part 9): Documenting the work
We have already passed a long way and the code in our library is becoming bigger and bigger. This makes it difficult to keep track of all connections and dependencies. Therefore, I suggest creating documentation for the earlier created code and to keep it updating with each new step. Properly prepared documentation will help us see the integrity of our work.
Neural networks made easy (Part 8): Attention mechanisms
Neural networks made easy (Part 8): Attention mechanisms
In previous articles, we have already tested various options for organizing neural networks. We also considered convolutional networks borrowed from image processing algorithms. In this article, I suggest considering Attention Mechanisms, the appearance of which gave impetus to the development of language models.
Using spreadsheets to build trading strategies
Using spreadsheets to build trading strategies
The article describes the basic principles and methods that allow you to analyze any strategy using spreadsheets (Excel, Calc, Google). The obtained results are compared with MetaTrader 5 tester.
Neural networks made easy (Part 6): Experimenting with the neural network learning rate
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 choose a learning rate. In this article, I want to show the importance of a correctly selected rate and its impact on the neural network training, using examples.
Practical application of neural networks in trading. Python (Part I)
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 learning library developed by Google. We will also use the Keras library for describing neural networks.
Neural networks made easy (Part 3): Convolutional networks
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 will consider the application of these networks in the financial markets.
Neural networks made easy (Part 2): Network training and testing
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 show similar results both in terms of training time and prediction accuracy.
A system of voice notifications for trade events and signals
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 voice notifications for various trade events, market states or signals generated by trading signals.
Practical application of neural networks in trading. It's time to practice
Practical application of neural networks in trading. It's time to practice
The article provides a description and instructions for the practical use of neural network modules on the Matlab platform. It also covers the main aspects of creation of a trading system using the neural network module. In order to be able to introduce the complex within one article, I had to modify it so as to combine several neural network module functions in one program.
Manual charting and trading toolkit (Part I). Preparation: structure description and helper class
Manual charting and trading toolkit (Part I). Preparation: structure description and helper class
This is the first article in a series, in which I am going to describe a toolkit which enables manual application of chart graphics by utilizing keyboard shortcuts. It is very convenient: you press one key and a trendline appears, you press another key — this will create a Fibonacci fan with the necessary parameters. It will also be possible to switch timeframes, to rearrange layers or to delete all objects from the chart.
Native Twitter Client: Part 2
Native Twitter Client: Part 2
A Twitter client implemented as MQL class to allow you to send tweets with photos. All you need is to include a single self contained include file and off you go to tweet all your wonderful charts and signals.
MQL as a Markup Tool for the Graphical Interface of MQL Programs (Part 3). Form Designer
MQL as a Markup Tool for the Graphical Interface of MQL Programs (Part 3). Form Designer
In this paper, we are completing the description of our concept of building the window interface of MQL programs, using the structures of MQL. Specialized graphical editor will allow to interactively set up the layout that consists of the basic classes of the GUI elements and then export it into the MQL description to use it in your MQL project. The paper presents the internal design of the editor and a user guide. Source codes are attached.
MQL as a Markup Tool for the Graphical Interface of MQL Programs. Part 2
MQL as a Markup Tool for the Graphical Interface of MQL Programs. Part 2
This paper continues checking the new conception to describe the window interface of MQL programs, using the structures of MQL. Automatically creating GUI based on the MQL markup provides additional functionality for caching and dynamically generating the elements and controlling the styles and new schemes for processing the events. Attached is an enhanced version of the standard library of controls.
MQL as a Markup Tool for the Graphical Interface of MQL Programs. Part 1
MQL as a Markup Tool for the Graphical Interface of MQL Programs. Part 1
This paper proposes a new conception to describe the window interface of MQL programs, using the structures of MQL. Special classes transform the viewable MQL markup into the GUI elements and allow manage them, set up their properties, and process the events in a unified manner. It also provides some examples of using the markup for the dialogs and elements of a standard library.
MQL5: Analysis and Processing of Commodity Futures Trading Commission (CFTC) Reports in MetaTrader 5
MQL5: Analysis and Processing of Commodity Futures Trading Commission (CFTC) Reports in MetaTrader 5
In this article, we will develop a tool for CFTC report analysis. We will solve the following problem: to develop an indicator, that allows using the CFTC report data directly from the data files provided by Commission without an intermediate processing and conversion. Further, it can be used for the different purposes: to plot the data as an indicator, to proceed with the data in the other indicators, in the scripts for the automated analysis, in the Expert Advisors for the use in the trading strategies.
An Example of Developing a Spread Strategy for Moscow Exchange Futures
An Example of Developing a Spread Strategy for Moscow Exchange Futures
The MetaTrader 5 platform allows developing and testing trading robots that simultaneously trade multiple financial instruments. The built-in Strategy Tester automatically downloads required tick history from the broker's server taking into account contract specifications, so the developer does not need to do anything manually. This makes it possible to easily and reliably reproduce trading environment conditions, including even millisecond intervals between the arrival of ticks on different symbols. In this article we will demonstrate the development and testing of a spread strategy on two Moscow Exchange futures.
Graphical Interfaces II: the Separation Line and Context Menu Elements (Chapter 2)
Graphical Interfaces II: the Separation Line and Context Menu Elements (Chapter 2)
In this article we will create the separation line element. It will be possible to use it not only as an independent interface element but also as a part of many other elements. After that, we will have everything required for the development of the context menu class, which will be also considered in this article in detail. Added to that, we will introduce all necessary additions to the class, which is the base for storing pointers to all the elements of the graphical interface of the application.
MQL5 Cookbook: Indicator Subwindow Controls - Scrollbar
MQL5 Cookbook: Indicator Subwindow Controls - Scrollbar
Let's continue exploring various controls and this time turn our attention to scrollbar. Just like in the previous article entitled "MQL5 Cookbook: Indicator Subwindow Controls - Buttons", all operations will be performed in the indicator subwindow. Take a moment to read the above mentioned article as it provides a detailed description of working with events in the OnChartEvent() function, while this point will only be casually touched upon in this article. For illustrative purposes, this time around we will create a vertical scrollbar for a large list of all financial instrument properties that can be obtained using MQL5 resources.
Drawing Dial Gauges Using the CCanvas Class
Drawing Dial Gauges Using the CCanvas Class
We can find dial gauges in cars and airplanes, in industrial production and everyday life. They are used in all spheres which require quick response to behavior of a controlled value. This article describes the library of dial gauges for MetaTrader 5.
Graphical Interfaces VII: the Tables Controls (Chapter 1)
Graphical Interfaces VII: the Tables Controls (Chapter 1)
The seventh part of the series on MetaTrader graphical interfaces deals with three table types: text label, edit box and rendered one. Another important and frequently used controls are tabs allowing you to show/hide groups of other controls and develop space effective interfaces in your MQL applications.
Custom Strategy Tester based on fast mathematical calculations
Custom Strategy Tester based on fast mathematical calculations
The article describes the way to create a custom strategy tester and a custom analyzer of the optimization passes. After reading it, you will understand how the math calculations mode and the mechanism of so-called frames work, how to prepare and load custom data for calculations and use effective algorithms for their compression. This article will also be interesting to those interested in ways of storing custom information within an expert.
MQL5 Cookbook: Developing a Multi-Symbol Volatility Indicator in MQL5
MQL5 Cookbook: Developing a Multi-Symbol Volatility Indicator in MQL5
In this article, we will consider the development of a multi-symbol volatility indicator. The development of multi-symbol indicators may present some difficulties for novice MQL5 developers which this article helps to clarify. The major issues arising in the course of development of a multi-symbol indicator have to do with the synchronization of other symbols' data with respect to the current symbol, the lack of some indicator data and the identification of the beginning of 'true' bars of a given time frame. All of these issues will be closely considered in the article.
MQL5 Cookbook: Development of a Multi-Symbol Indicator to Analyze Price Divergence
MQL5 Cookbook: Development of a Multi-Symbol Indicator to Analyze Price Divergence
In this article, we will consider the development of a multi-symbol indicator to analyze price divergence in a specified period of time. The core topics have been already discussed in the previous article on the programming of multi-currency indicators "MQL5 Cookbook: Developing a Multi-Symbol Volatility Indicator in MQL5". So this time we will dwell only on those new features and functions that have been changed dramatically. If you are new to the programming of multi-currency indicators, I recommend you to first read the previous article.
How to quickly develop and debug a trading strategy in MetaTrader 5
How to quickly develop and debug a trading strategy in MetaTrader 5
Scalping automatic systems are rightfully regarded the pinnacle of algorithmic trading, but at the same time their code is the most difficult to write. In this article we will show how to build strategies based on analysis of incoming ticks using the built-in debugging tools and visual testing. Developing rules for entry and exit often require years of manual trading. But with the help of MetaTrader 5, you can quickly test any such strategy on real history.
Creating and testing custom symbols in MetaTrader 5
Creating and testing custom symbols in MetaTrader 5
Creating custom symbols pushes the boundaries in the development of trading systems and financial market analysis. Now traders are able to plot charts and test trading strategies on an unlimited number of financial instruments.