![Developing a Replay System — Market simulation (Part 01): First experiments (I)](https://c.mql5.com/2/52/replay-p1_600x314.jpg)
Developing a Replay System — Market simulation (Part 01): First experiments (I)
How about creating a system that would allow us to study the market when it is closed or even to simulate market situations? Here we are going to start a new series of articles in which we will deal with this topic.
![Neural networks made easy (Part 19): Association rules using MQL5](https://c.mql5.com/2/49/Neural_Networks_Easy_011_600x314.jpg)
Neural networks made easy (Part 19): Association rules using MQL5
We continue considering association rules. In the previous article, we have discussed theoretical aspect of this type of problem. In this article, I will show the implementation of the FP Growth method using MQL5. We will also test the implemented solution using real data.
![Neural networks made easy (Part 28): Policy gradient algorithm](https://c.mql5.com/2/49/Neural_Networks_Easy_020_600x314.jpg)
Neural networks made easy (Part 28): Policy gradient algorithm
We continue to study reinforcement learning methods. In the previous article, we got acquainted with the Deep Q-Learning method. In this method, the model is trained to predict the upcoming reward depending on the action taken in a particular situation. Then, an action is performed in accordance with the policy and the expected reward. But it is not always possible to approximate the Q-function. Sometimes its approximation does not generate the desired result. In such cases, approximation methods are applied not to utility functions, but to a direct policy (strategy) of actions. One of such methods is Policy Gradient.
![Creating an EA that works automatically (Part 09): Automation (I)](https://c.mql5.com/2/50/aprendendo_construindo_009_600x314.jpg)
Creating an EA that works automatically (Part 09): Automation (I)
Although the creation of an automated EA is not a very difficult task, however, many mistakes can be made without the necessary knowledge. In this article, we will look at how to build the first level of automation, which consists in creating a trigger to activate breakeven and a trailing stop level.
![Creating an EA that works automatically (Part 13): Automation (V)](https://c.mql5.com/2/51/aprendendo_construindo_013_600x314.jpg)
Creating an EA that works automatically (Part 13): Automation (V)
Do you know what a flowchart is? Can you use it? Do you think flowcharts are for beginners? I suggest that we proceed to this new article and learn how to work with flowcharts.
![How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 5): Bollinger Bands On Keltner Channel — Indicators Signal](https://c.mql5.com/2/61/rj-article-images_600x314.jpg)
How to create a simple Multi-Currency Expert Advisor using MQL5 (Part 5): Bollinger Bands On Keltner Channel — Indicators Signal
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.
![MQL5 Wizard techniques you should know (Part 02): Kohonen Maps](https://c.mql5.com/2/49/kohonen-maps_600x314.jpg)
MQL5 Wizard techniques you should know (Part 02): Kohonen Maps
These series of articles will proposition that the MQL5 Wizard should be a mainstay for traders. Why? Because not only does the trader save time by assembling his new ideas with the MQL5 Wizard, and greatly reduce mistakes from duplicate coding; he is ultimately set-up to channel his energy on the few critical areas of his trading philosophy.
![Prices in DoEasy library (part 59): Object to store data of one tick](https://c.mql5.com/2/41/MQL5-avatar-doeasy-library__3.png)
![Prices in DoEasy library (part 59): Object to store data of one tick](https://c.mql5.com/i/articles/overlay.png)
Prices in DoEasy library (part 59): Object to store data of one tick
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.
![Trading strategy based on the improved Doji candlestick pattern recognition indicator](https://c.mql5.com/2/53/doji_candlestick_pattern_600x314.jpg)
Trading strategy based on the improved Doji candlestick pattern recognition indicator
The metabar-based indicator detected more candles than the conventional one. Let's check if this provides real benefit in the automated trading.
![Trading Strategies](https://c.mql5.com/2/13/175_1.png)
![Trading Strategies](https://c.mql5.com/i/articles/overlay.png)
Trading Strategies
All categories classifying trading strategies are fully arbitrary. The classification below is to emphasize the basic differences between possible approaches to trading.
![MQL5 Wizard techniques you should know (Part 05): Markov Chains](https://c.mql5.com/2/51/markov_chains_600x314.jpg)
MQL5 Wizard techniques you should know (Part 05): Markov Chains
Markov chains are a powerful mathematical tool that can be used to model and forecast time series data in various fields, including finance. In financial time series modelling and forecasting, Markov chains are often used to model the evolution of financial assets over time, such as stock prices or exchange rates. One of the main advantages of Markov chain models is their simplicity and ease of use.
![Moral expectation in trading](https://c.mql5.com/2/0/Moral_expectation_600x314.jpg)
Moral expectation in trading
This article is about moral expectation. We will look at several examples of its use in trading, as well as the results that can be achieved with its help.
![A Step-by-Step Guide on Trading the Break of Structure (BoS) Strategy](https://c.mql5.com/2/80/A_Step-by-Step_Guide_on_Trading_the_Break_of_Structure__600x314.jpg)
A Step-by-Step Guide on Trading the Break of Structure (BoS) Strategy
A comprehensive guide to developing an automated trading algorithm based on the Break of Structure (BoS) strategy. Detailed information on all aspects of creating an advisor in MQL5 and testing it in MetaTrader 5 — from analyzing price support and resistance to risk management
![Cascade Order Trading Strategy Based on EMA Crossovers for MetaTrader 5](https://c.mql5.com/2/84/Cascade_Order_Trading_Strategy_Based_on_EMA_Crossovers_600x314.jpg)
Cascade Order Trading Strategy Based on EMA Crossovers for MetaTrader 5
The article guides in demonstrating an automated algorithm based on EMA Crossovers for MetaTrader 5. Detailed information on all aspects of demonstrating an Expert Advisor in MQL5 and testing it in MetaTrader 5 - from analyzing price range behaviors to risk management.
![Neural networks made easy (Part 24): Improving the tool for Transfer Learning](https://c.mql5.com/2/49/Neural_Networks_Easy_016_600x314.jpg)
Neural networks made easy (Part 24): Improving the tool for Transfer Learning
In the previous article, we created a tool for creating and editing the architecture of neural networks. Today we will continue working on this tool. We will try to make it more user friendly. This may see, top be a step away form our topic. But don't you think that a well organized workspace plays an important role in achieving the result.
![Developing a Replay System — Market simulation (Part 02): First experiments (II)](https://c.mql5.com/2/52/replay-p2_600x314.jpg)
Developing a Replay System — Market simulation (Part 02): First experiments (II)
This time, let's try a different approach to achieve the 1 minute goal. However, this task is not as simple as one might think.
![Alan Andrews and his methods of time series analysis](https://c.mql5.com/2/0/Alan_Andrews_600x314.jpg)
Alan Andrews and his methods of time series analysis
Alan Andrews is one of the most famous "educators" of the modern world in the field of trading. His "pitchfork" is included in almost all modern quote analysis programs. But most traders do not use even a fraction of the opportunities that this tool provides. Besides, Andrews' original training course includes a description not only of the pitchfork (although it remains the main tool), but also of some other useful constructions. The article provides an insight into the marvelous chart analysis methods that Andrews taught in his original course. Beware, there will be a lot of images.
![Timeseries in DoEasy library (part 54): Descendant classes of abstract base indicator](https://c.mql5.com/2/49/doeasy_054_600x314.jpg)
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.
![Creating an EA that works automatically (Part 08): OnTradeTransaction](https://c.mql5.com/2/50/aprendendo_construindo_008_600x314.jpg)
Creating an EA that works automatically (Part 08): OnTradeTransaction
In this article, we will see how to use the event handling system to quickly and efficiently process issues related to the order system. With this system the EA will work faster, so that it will not have to constantly search for the required data.
![Advanced resampling and selection of CatBoost models by brute-force method](https://c.mql5.com/2/49/Advanced-resampling-and-selection-of-CatBoost-models-by-brute-force-method_600x314.jpg)
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.
![Understanding MQL5 Object-Oriented Programming (OOP)](https://c.mql5.com/2/56/object-oriented-programming_600x314__1.jpg)
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.
![Understanding Programming Paradigms (Part 1): A Procedural Approach to Developing a Price Action Expert Advisor](https://c.mql5.com/2/61/MQL5_Article01_Artwork_hero_600x314.jpg)
Understanding Programming Paradigms (Part 1): A Procedural Approach to Developing a Price Action Expert Advisor
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.
![Developing a trading Expert Advisor from scratch (Part 22): New order system (V)](https://c.mql5.com/2/49/Developing_a_trading_Expert_Advisor_001_600x314.jpg)
Developing a trading Expert Advisor from scratch (Part 22): New order system (V)
Today we will continue to develop the new order system. It is not that easy to implement a new system as we often encounter problems which greatly complicate the process. When these problems appear, we have to stop and re-analyze the direction in which we are moving.
![Modified Grid-Hedge EA in MQL5 (Part I): Making a Simple Hedge EA](https://c.mql5.com/2/62/Modified_Grid-Hedge_EA_in_MQL5_qPart_Il_Making_a_Simple_Hedge_EA_600x314.jpg)
Modified Grid-Hedge EA in MQL5 (Part I): Making a Simple Hedge EA
We will be creating a simple hedge EA as a base for our more advanced Grid-Hedge EA, which will be a mixture of classic grid and classic hedge strategies. By the end of this article, you will know how to create a simple hedge strategy, and you will also get to know what people say about whether this strategy is truly 100% profitable.
![Neural networks made easy (Part 67): Using past experience to solve new tasks](https://c.mql5.com/2/62/Neural_networks_made_easy_Part_67_600x314.jpg)
Neural networks made easy (Part 67): Using past experience to solve new tasks
In this article, we continue discussing methods for collecting data into a training set. Obviously, the learning process requires constant interaction with the environment. However, situations can be different.
![How to create a custom True Strength Index indicator using MQL5](https://c.mql5.com/2/54/true_strength_index_600x314.jpg)
How to create a custom True Strength Index indicator using MQL5
Here is a new article about how to create a custom indicator. This time we will work with the True Strength Index (TSI) and will create an Expert Advisor based on it.
![How we developed the MetaTrader Signals service and Social Trading](https://c.mql5.com/2/11/signals_icon.png)
![How we developed the MetaTrader Signals service and Social Trading](https://c.mql5.com/i/articles/overlay.png)
How we developed the MetaTrader Signals service and Social Trading
We continue to enhance the Signals service, improve the mechanisms, add new functions and fix flaws. The MetaTrader Signals Service of 2012 and the current MetaTrader Signals Service are like two completely different services. Currently, we are implementing A Virtual Hosting Cloud service which consists of a network of servers to support specific versions of the MetaTrader client terminal.
![Experiments with neural networks (Part 5): Normalizing inputs for passing to a neural network](https://c.mql5.com/2/53/neural_network_experiments-p5_600x314.jpg)
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.
![Multiple indicators on one chart (Part 05): Turning MetaTrader 5 into a RAD system (I)](https://c.mql5.com/2/49/Multiple-indicators-on-one-chart-9Part-05a-Turning-MetaTrader-5-into-a-RAD-system-yI6_600x314.jpg)
Multiple indicators on one chart (Part 05): Turning MetaTrader 5 into a RAD system (I)
There are a lot of people who do not know how to program but they are quite creative and have great ideas. However, the lack of programming knowledge prevents them from implementing these ideas. Let's see together how to create a Chart Trade using the MetaTrader 5 platform itself, as if it were an IDE.
![Expert Advisors Based on Popular Trading Strategies and Alchemy of Trading Robot Optimization (Part VI)](https://c.mql5.com/2/16/633_39.gif)
![Expert Advisors Based on Popular Trading Strategies and Alchemy of Trading Robot Optimization (Part VI)](https://c.mql5.com/i/articles/overlay.png)
Expert Advisors Based on Popular Trading Strategies and Alchemy of Trading Robot Optimization (Part VI)
In this article, the author proposes the way of improving trading systems presented in his previous articles. The article is of interest for traders already having experiences in writing Expert Advisors.
![Neural networks made easy (Part 15): Data clustering using MQL5](https://c.mql5.com/2/49/Neural_networks_made_easy_005_600x314.jpg)
Neural networks made easy (Part 15): Data clustering using MQL5
We continue to consider the clustering method. In this article, we will create a new CKmeans class to implement one of the most common k-means clustering methods. During tests, the model managed to identify about 500 patterns.
![MQL5 Market Results for Q2 2013](https://c.mql5.com/2/0/MQL5_Market_Results_2_2013.png)
![MQL5 Market Results for Q2 2013](https://c.mql5.com/i/articles/overlay.png)
MQL5 Market Results for Q2 2013
Successfully operating for 1.5 years, MQL5 Market has become the largest traders' store of trading strategies and technical indicators. It offers around 800 trading applications provided by 350 developers from around the world. Over 100.000 trading programs have already been purchased and downloaded by traders to their MetaTrader 5 terminals.
![Developing a trading Expert Advisor from scratch (Part 28): Towards the future (III)](https://c.mql5.com/2/49/Developing_a_trading_Expert_Advisor_007_600x314.jpg)
Developing a trading Expert Advisor from scratch (Part 28): Towards the future (III)
There is still one task which our order system is not up to, but we will FINALLY figure it out. The MetaTrader 5 provides a system of tickets which allows creating and correcting order values. The idea is to have an Expert Advisor that would make the same ticket system faster and more efficient.
![MQL5 Wizard techniques you should know (Part 03): Shannon's Entropy](https://c.mql5.com/2/49/Regression_Analysis_Cover_600x314.jpg)
MQL5 Wizard techniques you should know (Part 03): Shannon's Entropy
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.
![Timeseries in DoEasy library (part 47): Multi-period multi-symbol standard indicators](https://c.mql5.com/2/39/MQL5-avatar-doeasy-library__4.png)
![Timeseries in DoEasy library (part 47): Multi-period multi-symbol standard indicators](https://c.mql5.com/i/articles/overlay.png)
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. 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.
![Neural networks made easy (Part 32): Distributed Q-Learning](https://c.mql5.com/2/50/Neural_networks_are_simple-32_600x314.jpg)
Neural networks made easy (Part 32): Distributed Q-Learning
We got acquainted with the Q-learning method in one of the earlier articles within this series. This method averages rewards for each action. Two works were presented in 2017, which show greater success when studying the reward distribution function. Let's consider the possibility of using such technology to solve our problems.
![Creating an EA that works automatically (Part 10): Automation (II)](https://c.mql5.com/2/50/aprendendo_construindo_010_600x314.jpg)
Creating an EA that works automatically (Part 10): Automation (II)
Automation means nothing if you cannot control its schedule. No worker can be efficient working 24 hours a day. However, many believe that an automated system should operate 24 hours a day. But it is always good to have means to set a working time range for the EA. In this article, we will consider how to properly set such a time range.
![Developing a Replay System — Market simulation (Part 21): FOREX (II)](https://c.mql5.com/2/57/replay_p21_600x314.jpg)
Developing a Replay System — Market simulation (Part 21): FOREX (II)
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 price movement model and its main provisions. (Part 3): Calculating optimal parameters of stock exchange speculations](https://c.mql5.com/2/56/The_price_movement_model_and_its_main_points_Part_3_600x314.jpg)
The price movement model and its main provisions. (Part 3): Calculating optimal parameters of stock exchange speculations
Within the framework of the engineering approach developed by the author based on the probability theory, the conditions for opening a profitable position are found and the optimal (profit-maximizing) take profit and stop loss values are calculated.
![Neural networks made easy (Part 21): Variational autoencoders (VAE)](https://c.mql5.com/2/49/Neural_Networks_Easy_013_600x314.jpg)
Neural networks made easy (Part 21): Variational autoencoders (VAE)
In the last article, we got acquainted with the Autoencoder algorithm. Like any other algorithm, it has its advantages and disadvantages. In its original implementation, the autoenctoder is used to separate the objects from the training sample as much as possible. This time we will talk about how to deal with some of its disadvantages.