![Neural networks made easy (Part 49): Soft Actor-Critic](https://c.mql5.com/2/56/Neural_Networks_are_Easy_Part_49_600x314.jpg)
Neural networks made easy (Part 49): Soft Actor-Critic
We continue our discussion of reinforcement learning algorithms for solving continuous action space problems. In this article, I will present the Soft Actor-Critic (SAC) algorithm. The main advantage of SAC is the ability to find optimal policies that not only maximize the expected reward, but also have maximum entropy (diversity) of actions.
![Data Science and Machine Learning (Part 06): Gradient Descent](https://c.mql5.com/2/49/gradient_descent_600x314.jpg)
Data Science and Machine Learning (Part 06): Gradient Descent
The gradient descent plays a significant role in training neural networks and many machine learning algorithms. It is a quick and intelligent algorithm despite its impressive work it is still misunderstood by a lot of data scientists let's see what it is all about.
![Data Science and Machine Learning (Part 13): Improve your financial market analysis with Principal Component Analysis (PCA)](https://c.mql5.com/2/52/pca_600x314.jpg)
Data Science and Machine Learning (Part 13): Improve your financial market analysis with Principal Component Analysis (PCA)
Revolutionize your financial market analysis with Principal Component Analysis (PCA)! Discover how this powerful technique can unlock hidden patterns in your data, uncover latent market trends, and optimize your investment strategies. In this article, we explore how PCA can provide a new lens for analyzing complex financial data, revealing insights that would be missed by traditional approaches. Find out how applying PCA to financial market data can give you a competitive edge and help you stay ahead of the curve
![Multibot in MetaTrader (Part II): Improved dynamic template](https://c.mql5.com/2/71/Multibot_in_MetaTrader_Part_II_600x314.jpg)
Multibot in MetaTrader (Part II): Improved dynamic template
Developing the theme of the previous article, I decided to create a more flexible and functional template that has greater capabilities and can be effectively used both in freelancing and as a base for developing multi-currency and multi-period EAs with the ability to integrate with external solutions.
![How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 6): Two RSI indicators cross each other's lines](https://c.mql5.com/2/64/rj-article-images_600x314.jpg)
How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 6): Two RSI indicators cross each other's lines
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.
![Revisiting Murray system](https://c.mql5.com/2/51/murrey-system_600x314.jpg)
Revisiting Murray system
Graphical price analysis systems are deservedly popular among traders. In this article, I am going to describe the complete Murray system, including its famous levels, as well as some other useful techniques for assessing the current price position and making a trading decision.
![How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 4): Triangular moving average — Indicator Signals](https://c.mql5.com/2/60/rj-article-images_600x314.jpg)
How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 4): Triangular moving average — Indicator Signals
The Multi-Currency Expert Advisor in this article is 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 only from one symbol chart. This time we will use only 1 indicator, namely Triangular moving average in multi-timeframes or single timeframe.
![Experiments with neural networks (Part 2): Smart neural network optimization](https://c.mql5.com/2/51/neural_network_experiments_p2_600x314.jpg)
Experiments with neural networks (Part 2): Smart neural network optimization
In this article, I will use experimentation and non-standard approaches to develop a profitable trading system and check whether neural networks can be of any help for traders. MetaTrader 5 as a self-sufficient tool for using neural networks in trading.
![Neural networks made easy (Part 31): Evolutionary algorithms](https://c.mql5.com/2/50/Neural_Networks_are_Simple-_Part_31_600x314.jpg)
Neural networks made easy (Part 31): Evolutionary algorithms
In the previous article, we started exploring non-gradient optimization methods. We got acquainted with the genetic algorithm. Today, we will continue this topic and will consider another class of evolutionary algorithms.
![Developing a Replay System — Market simulation (Part 20): FOREX (I)](https://c.mql5.com/2/56/replay_p20_600x314.jpg)
Developing a Replay System — Market simulation (Part 20): FOREX (I)
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.
![Neural networks made easy (Part 55): Contrastive intrinsic control (CIC)](https://c.mql5.com/2/57/cic-055_600x314.jpg)
Neural networks made easy (Part 55): Contrastive intrinsic control (CIC)
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.
![Developing a trading Expert Advisor from scratch (Part 11): Cross order system](https://c.mql5.com/2/49/Developing_a_trading_Expert_Advisor_from_scratch_002_600x314.jpg)
Developing a trading Expert Advisor from scratch (Part 11): Cross order system
In this article we will create a system of cross orders. There is one type of assets that makes traders' life very difficult for traders — futures contracts. But why do they make life difficult?
![Neural networks made easy (Part 33): Quantile regression in distributed Q-learning](https://c.mql5.com/2/50/Neural_Networks_Made_Easy_q-learning_600x314.jpg)
Neural networks made easy (Part 33): Quantile regression in distributed Q-learning
We continue studying distributed Q-learning. Today we will look at this approach from the other side. We will consider the possibility of using quantile regression to solve price prediction tasks.
![Developing a Replay System (Part 38): Paving the Path (II)](https://c.mql5.com/2/61/Replay_Parte_38_Pavimentando_o_Terreno_600x314.jpg)
Developing a Replay System (Part 38): Paving the Path (II)
Many people who consider themselves MQL5 programmers do not have the basic knowledge that I will outline in this article. Many people consider MQL5 to be a limited tool, but the actual reason is that they do not have the required knowledge. So, if you don't know something, don't be ashamed of it. It's better to feel ashamed for not asking. Simply forcing MetaTrader 5 to disable indicator duplication in no way ensures two-way communication between the indicator and the Expert Advisor. We are still very far from this, but the fact that the indicator is not duplicated on the chart gives us some confidence.
![Developing a Replay System — Market simulation (Part 04): adjusting the settings (II)](https://c.mql5.com/2/52/replay-p4_600x314.jpg)
Developing a Replay System — Market simulation (Part 04): adjusting the settings (II)
Let's continue creating the system and controls. Without the ability to control the service, it is difficult to move forward and improve the system.
![How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 3): Added symbols prefixes and/or suffixes and Trading Time Session](https://c.mql5.com/2/60/Parabolic_SAR_MTF_600x314.jpg)
How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 3): Added symbols prefixes and/or suffixes and Trading Time Session
Several fellow traders sent emails or commented about how to use this Multi-Currency EA on brokers with symbol names that have prefixes and/or suffixes, and also how to implement trading time zones or trading time sessions on this Multi-Currency EA.
![Neural networks made easy (Part 56): Using nuclear norm to drive research](https://c.mql5.com/2/57/nuclear_norm_utilization_600x314.jpg)
Neural networks made easy (Part 56): Using nuclear norm to drive research
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.
![Developing a Replay System — Market simulation (Part 15): Birth of the SIMULATOR (V) - RANDOM WALK](https://c.mql5.com/2/55/Desenvolvendo_um_sistema_de_Replay_Parte_15_600x314.jpg)
Developing a Replay System — Market simulation (Part 15): Birth of the SIMULATOR (V) - RANDOM WALK
In this article we will complete the development of a simulator for our system. The main goal here will be to configure the algorithm discussed in the previous article. This algorithm aims to create a RANDOM WALK movement. Therefore, to understand today's material, it is necessary to understand the content of previous articles. If you have not followed the development of the simulator, I advise you to read this sequence from the very beginning. Otherwise, you may get confused about what will be explained here.
![Neural networks made easy (Part 54): Using random encoder for efficient research (RE3)](https://c.mql5.com/2/57/random_encoder_for_efficient_exploration_054_600x314.jpg)
Neural networks made easy (Part 54): Using random encoder for efficient research (RE3)
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.
![Developing a trading Expert Advisor from scratch (Part 14): Adding Volume At Price (II)](https://c.mql5.com/2/49/Developing_a_trading_Expert_Advisor_from_scratch_005_600x314.jpg)
Developing a trading Expert Advisor from scratch (Part 14): Adding Volume At Price (II)
Today we will add some more resources to our EA. This interesting article can provide some new ideas and methods of presenting information. At the same time, it can assist in fixing minor flaws in your projects.
![Timeseries in DoEasy library (part 51): Composite multi-period multi-symbol standard indicators](https://c.mql5.com/2/49/doeasy_051_600x314.jpg)
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.
![MQL5 Wizard Techniques you should know (Part 09): Pairing K-Means Clustering with Fractal Waves](https://c.mql5.com/2/62/midjourney_image_13915_50_439_5_600x314.jpg)
MQL5 Wizard Techniques you should know (Part 09): Pairing K-Means Clustering with Fractal Waves
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.
![Developing a trading Expert Advisor from scratch (Part 20): New order system (III)](https://c.mql5.com/2/49/Developing_a_trading_Expert_Advisor_from_scratch_011_600x314.jpg)
Developing a trading Expert Advisor from scratch (Part 20): New order system (III)
We continue to implement the new order system. The creation of such a system requires a good command of MQL5, as well as an understanding of how the MetaTrader 5 platform actually works and what resources it provides.
![Improve Your Trading Charts With Interactive GUI's in MQL5 (Part II): Movable GUI (II)](https://c.mql5.com/2/56/Revolutionize_Your_Trading_Charts_Part_2_600x314.jpg)
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.
![Category Theory in MQL5 (Part 8): Monoids](https://c.mql5.com/2/54/Category-Theory-p8_600x314.jpg)
Category Theory in MQL5 (Part 8): Monoids
This article continues the series on category theory implementation in MQL5. Here we introduce monoids as domain (set) that sets category theory apart from other data classification methods by including rules and an identity element.
![MQL5 Wizard techniques you should know (Part 04): Linear Discriminant Analysis](https://c.mql5.com/2/50/linear_discriminant_analysis_600x314.jpg)
MQL5 Wizard techniques you should know (Part 04): Linear Discriminant Analysis
Todays trader is a philomath who is almost always looking up new ideas, trying them out, choosing to modify them or discard them; an exploratory process that should cost a fair amount of diligence. These series of articles will proposition that the MQL5 wizard should be a mainstay for traders in this effort.
![Creating an EA that works automatically (Part 07): Account types (II)](https://c.mql5.com/2/50/aprendendo_construindo_007_600x314.jpg)
Creating an EA that works automatically (Part 07): Account types (II)
Today we'll see how to create an Expert Advisor that simply and safely works in automatic mode. The trader should always be aware of what the automatic EA is doing, so that if it "goes off the rails", the trader could remove it from the chart as soon as possible and take control of the situation.
![Design Patterns in software development and MQL5 (Part 3): Behavioral Patterns 1](https://c.mql5.com/2/61/Design_Patterns_wPart_3z_Behavioral_Patterns_1_600x314.jpg)
Design Patterns in software development and MQL5 (Part 3): Behavioral Patterns 1
A new article from Design Patterns articles and we will take a look at one of its types which is behavioral patterns to understand how we can build communication methods between created objects effectively. By completing these Behavior patterns we will be able to understand how we can create and build a reusable, extendable, tested software.
![Neural networks made easy (Part 18): Association rules](https://c.mql5.com/2/49/Neural_Networks_Easy_010_600x314.jpg)
Neural networks made easy (Part 18): Association rules
As a continuation of this series of articles, let's consider another type of problems within unsupervised learning methods: mining association rules. This problem type was first used in retail, namely supermarkets, to analyze market baskets. In this article, we will talk about the applicability of such algorithms in trading.
![Data Science and Machine Learning (Part 15): SVM, A Must-Have Tool in Every Trader's Toolbox](https://c.mql5.com/2/60/Data_Science_and_Machine_Learning1Part_15n_SVM_600x314.jpg)
Data Science and Machine Learning (Part 15): SVM, A Must-Have Tool in Every Trader's Toolbox
Discover the indispensable role of Support Vector Machines (SVM) in shaping the future of trading. This comprehensive guide explores how SVM can elevate your trading strategies, enhance decision-making, and unlock new opportunities in the financial markets. Dive into the world of SVM with real-world applications, step-by-step tutorials, and expert insights. Equip yourself with the essential tool that can help you navigate the complexities of modern trading. Elevate your trading game with SVM—a must-have for every trader's toolbox.
![Understanding Programming Paradigms (Part 2): An Object-Oriented Approach to Developing a Price Action Expert Advisor](https://c.mql5.com/2/71/MQL5_Article-02_Artwork_hero_1200_x_628px_600x314.jpg)
Understanding Programming Paradigms (Part 2): An Object-Oriented Approach to Developing a Price Action Expert Advisor
Learn about the object-oriented programming paradigm and its application in MQL5 code. This second article goes deeper into the specifics of object-oriented programming, offering hands-on experience through a practical example. You'll learn how to convert our earlier developed procedural price action expert advisor using the EMA indicator and candlestick price data to object-oriented code.
![Mastering ONNX: The Game-Changer for MQL5 Traders](https://c.mql5.com/2/59/Mastering_ONNX_up_600x314__1.jpg)
Mastering ONNX: The Game-Changer for MQL5 Traders
Dive into the world of ONNX, the powerful open-standard format for exchanging machine learning models. Discover how leveraging ONNX can revolutionize algorithmic trading in MQL5, allowing traders to seamlessly integrate cutting-edge AI models and elevate their strategies to new heights. Uncover the secrets to cross-platform compatibility and learn how to unlock the full potential of ONNX in your MQL5 trading endeavors. Elevate your trading game with this comprehensive guide to Mastering ONNX
![Developing a trading Expert Advisor from scratch (Part 24): Providing system robustness (I)](https://c.mql5.com/2/49/Developing_a_trading_Expert_Advisor_003_600x314.jpg)
Developing a trading Expert Advisor from scratch (Part 24): Providing system robustness (I)
In this article, we will make the system more reliable to ensure a robust and secure use. One of the ways to achieve the desired robustness is to try to re-use the code as much as possible so that it is constantly tested in different cases. But this is only one of the ways. Another one is to use OOP.
![Building Your First Glass-box Model Using Python And MQL5](https://c.mql5.com/2/61/Building_Your_First_Glass_Box_Model_Using_Python_And_MQL5_600x314.jpg)
Building Your First Glass-box Model Using Python And MQL5
Machine learning models are difficult to interpret and understanding why our models deviate from our expectations is critical if we want to gain any value from using such advanced techniques. Without comprehensive insight into the inner workings of our model, we might fail to spot bugs that are corrupting our model's performance, we may waste time over engineering features that aren't predictive and in the long run we risk underutilizing the power of these models. Fortunately, there is a sophisticated and well maintained all in one solution that allows us to see exactly what our model is doing underneath the hood.
![Testing and optimization of binary options strategies in MetaTrader 5](https://c.mql5.com/2/0/binary-strategy-tester_600x314.jpg)
Testing and optimization of binary options strategies in MetaTrader 5
In this article, I will check and optimize binary options strategies in MetaTrader 5.
![Neural networks made easy (Part 17): Dimensionality reduction](https://c.mql5.com/2/49/Neural_networks_made_easy_007_600x314.jpg)
Neural networks made easy (Part 17): Dimensionality reduction
In this part we continue discussing Artificial Intelligence models. Namely, we study unsupervised learning algorithms. We have already discussed one of the clustering algorithms. In this article, I am sharing a variant of solving problems related to dimensionality reduction.
![How to Integrate Smart Money Concepts (BOS) Coupled with the RSI Indicator into an EA](https://c.mql5.com/2/83/Integrate_Smart_Money_Concepts_coupled_with_the_RSI_Indicator_into_an_EA_600x314.jpg)
How to Integrate Smart Money Concepts (BOS) Coupled with the RSI Indicator into an EA
Smart Money Concept (Break Of Structure) coupled with the RSI Indicator to make in informed automated trading decisions based on the market structure.
![Neural networks made easy (Part 58): Decision Transformer (DT)](https://c.mql5.com/2/58/decision-transformer_600x314.jpg)
Neural networks made easy (Part 58): Decision Transformer (DT)
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.
![Experiments with neural networks (Part 7): Passing indicators](https://c.mql5.com/2/59/Experiments_with_neural_networks_7_600x314.jpg)
Experiments with neural networks (Part 7): Passing indicators
Examples of passing indicators to a perceptron. The article describes general concepts and showcases the simplest ready-made Expert Advisor followed by the results of its optimization and forward test.
![Mastering Market Dynamics: Creating a Support and Resistance Strategy Expert Advisor (EA)](https://c.mql5.com/2/82/Creating_a_Support_and_Resistance_Strategy_Expert_Advisor_600x314.jpg)
Mastering Market Dynamics: Creating a Support and Resistance Strategy Expert Advisor (EA)
A comprehensive guide to developing an automated trading algorithm based on the Support and Resistance strategy. Detailed information on all aspects of creating an expert advisor in MQL5 and testing it in MetaTrader 5 – from analyzing price range behaviors to risk management.