The article discusses Stochastic Diffusion Search (SDS), which is a very powerful and efficient optimization algorithm based on the principles of random walk. The algorithm allows finding optimal solutions in complex multidimensional spaces, while featuring a high speed of convergence and the ability to avoid local extrema.
We will continue to build a system for working in the FOREX market. In order to solve this problem, we must first declare the loading of ticks before loading the previous bars. This solves the problem, but at the same time forces the user to follow some structure in the configuration file, which, personally, does not make much sense to me. The reason is that by designing a program that is responsible for analyzing and executing what is in the configuration file, we can allow the user to declare the elements he needs in any order.
The article considers standard indicators from the oscillator category. We will create ready-to-use templates for their use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.
We continue to explore reinforcement learning methods. In this article, I will focus on a slightly different algorithm that considers the Agent’s policy in the paradigm of constructing a sequence of actions.
In this article, we will create a dashboard class to be used in indicators and EAs. This is an introductory article in a small series of articles with templates for including and using standard indicators in Expert Advisors. I will start by creating a panel similar to the MetaTrader 5 data window.
In this article, we will try to provide trading systems using a very important concept in the financial market which is volatility. We will provide a trading system based on the Keltner Channel indicator after understanding it and how we can code it and how we can create a trading system based on a simple trading strategy and then test it on different assets.
In this reference article, we will look at standard indicators from the Trend Indicators category. We will create ready-to-use templates for indicator use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.
The article takes a quick look at the ALGLIB 3.19 numerical analysis library, its applications and new algorithms that can improve the efficiency of financial data analysis.
The article presents a detailed description of the shuffled frog-leaping (SFL) algorithm and its capabilities in solving optimization problems. The SFL algorithm is inspired by the behavior of frogs in their natural environment and offers a new approach to function optimization. The SFL algorithm is an efficient and flexible tool capable of processing a variety of data types and achieving optimal solutions.
Number Walls are a variant of Linear Shift Back Registers that prescreen sequences for predictability by checking for convergence. We look at how these ideas could be of use in MQL5.
DRAKON is a visual programming language designed to simplify interaction between specialists from different fields (biologists, physicists, engineers...) with programmers in Russian space projects (for example, in the Buran reusable spacecraft project). In this article, I will talk about how DRAKON makes the creation of algorithms accessible and intuitive, even if you have never encountered code, and also how it is easier for customers to explain their thoughts when ordering trading robots, and for programmers to make fewer mistakes in complex functions.
This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy of our model, and even help the model make a qualitative leap!
In this article, we will consider pair trading, namely what its principles are and if there are any prospects for its practical application. We will also try to create a pair trading strategy.
Data classification for purposes of analysis and forecasting is a very diverse arena within machine learning and it features a large number of approaches and methods. This piece looks at one such approach, namely Agglomerative Hierarchical Classification.
In this article, we will look at standard indicators of the Volume and Bill Williams' indicators category. We will create ready-to-use templates for indicator use in EAs - declaring and setting parameters, indicator initialization and deinitialization, as well as receiving data and signals from indicator buffers in EAs.
K-Means clustering takes the approach to grouping data points as a process that’s initially focused on the macro view of a data set that uses random generated cluster centroids before zooming in and adjusting these centroids to accurately represent the data set. We will look at this and exploit a few of its use cases.
The multi-currency expert advisor in this article is an expert advisor or trading robot that uses two RSI indicators with crossing lines, the Fast RSI which crosses with the Slow RSI.
The study of the environment in reinforcement learning is a pressing problem. We have already looked at some approaches previously. In this article, we will have a look at yet another method based on maximizing the nuclear norm. It allows agents to identify environmental states with a high degree of novelty and diversity.
In this article, we will learn how we can build an Aroon trading system after learning the basics of the indicators and the needed steps to build a trading system based on the Aroon indicator. After building this trading system, we will test it to see if it can be profitable or needs more optimization.
Here I will consider the fairly new Stochastic Marginal Actor-Critic (SMAC) algorithm, which allows building latent variable policies within the framework of entropy maximization.
In this article, we explored the classic grid strategy, detailing its automation using an Expert Advisor in MQL5 and analyzing initial backtest results. We highlighted the strategy's need for high holding capacity and outlined plans for optimizing key parameters like distance, takeProfit, and lot sizes in future installments. The series aims to enhance trading strategy efficiency and adaptability to different market conditions.
Restrictive Boltzmann Machines are at the basic level, a two-layer neural network that is proficient at unsupervised classification through dimensionality reduction. We take its basic principles and examine if we were to re-design and train it unorthodoxly, we could get a useful signal filter.
This article is the fifth part of a series describing our development steps of a native MQL5 client for the MQTT 5.0 protocol. In this part we describe the structure of PUBLISH packets, how we are setting their Publish Flags, encoding Topic Name(s) strings, and setting Packet Identifier(s) when required.
In this article we demonstrate the implementation of the Augmented Dickey-Fuller test, and apply it to conduct cointegration tests using the Engle-Granger method.
Here we will see how to implement something really interesting, but at the same time very difficult due to certain points that can be very confusing. The worst thing that can happen is that some traders who consider themselves professionals do not know anything about the importance of these concepts in the capital market. Well, although we focus here on programming, understanding some of the issues involved in market trading is paramount to what we are going to implement.
This series of articles introduces several time series labeling methods, which can create data that meets most artificial intelligence models, and targeted data labeling according to needs can make the trained artificial intelligence model more in line with the expected design, improve the accuracy of our model, and even help the model make a qualitative leap!
In this article, we will complete our series about the Design Patterns topic, we mentioned that there are three types of design patterns creational, structural, and behavioral. We will complete the remaining patterns of the behavioral type which can help set the method of interaction between objects in a way that makes our code clean.
Contrastive training is an unsupervised method of training representation. Its goal is to train a model to highlight similarities and differences in data sets. In this article, we will talk about using contrastive training approaches to explore different Actor skills.
Learn about programming paradigms and their application in MQL5 code. This article explores the specifics of procedural programming, offering hands-on experience through a practical example. You'll learn how to develop a price action expert advisor using the EMA indicator and candlestick price data. Additionally, the article introduces you to the functional programming paradigm.
Discover the secrets of algorithmic alchemy as we guide you through the blend of artistry and precision in decoding financial landscapes. Unearth how Random Forests transform data into predictive prowess, offering a unique perspective on navigating the complex terrain of stock markets. Join us on this journey into the heart of financial wizardry, where we demystify the role of Random Forests in shaping market destiny and unlocking the doors to lucrative opportunities
In this article I will show the first part of the improvements that allowed me not only to close the entire automation chain for MetaTrader 4 and 5 trading, but also to do something much more interesting. From now on, this solution allows me to fully automate both creating EAs and optimization, as well as to minimize labor costs for finding effective trading configurations.
We need to organize our work better. The code is growing, and if this is not done now, then it will become impossible. Let's divide and conquer. MQL5 allows the use of classes which will assist in implementing this task, but for this we need to have some knowledge about classes. Probably the thing that confuses beginners the most is inheritance. In this article, we will look at how to use these mechanisms in a practical and simple way.
In this article we explore the application of digital filters on time series represented in the frequency domain so as to extract unique features that may be useful to prediction models.
The initial goal of this article is not to cover all the possibilities of Forex trading, but rather to adapt the system so that you can perform at least one market replay. We'll leave simulation for another moment. However, if we don't have ticks and only bars, with a little effort we can simulate possible trades that could happen in the Forex market. This will be the case until we look at how to adapt the simulator. An attempt to work with Forex data inside the system without modifying it leads to a range of errors.
Dive into the intricate world of decision trees in the latest installment of our Data Science and Machine Learning series. Tailored for traders seeking strategic insights, this article serves as a comprehensive recap, shedding light on the powerful role decision trees play in the analysis of market trends. Explore the roots and branches of these algorithmic trees, unlocking their potential to enhance your trading decisions. Join us for a refreshing perspective on decision trees and discover how they can be your allies in navigating the complexities of financial markets.
The Multi-Currency Expert Advisor in this article is an Expert Advisor or Trading Robot that can trade (open orders, close orders and manage orders for example: Trailing Stop Loss and Trailing Profit) for more than one symbol pair from only one symbol chart. In this article we will use signals from two indicators, in this case Bollinger Bands® on Keltner Channel.
Whenever we consider reinforcement learning methods, we are faced with the issue of efficiently exploring the environment. Solving this issue often leads to complication of the algorithm and training of additional models. In this article, we will look at an alternative approach to solving this problem.
