Articles on strategy testing in MQL5

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How to develop, write and test a trading strategy, how to find the optimal system parameters and how to analyze the results? The MetaTrader platform offers developers of trading robots rich functionality for fast and accurate testing of trading ideas. Read these articles to learn how to test multi-currency robots and how to use MQL5 Cloud Network for optimization purposes.

Developers of automated trading systems are recommended to start with the testing fundamentals and tick generation algorithms in the strategy tester.

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Practical Use of Kohonen Neural Networks in Algorithmic Trading. Part II. Optimizing and forecasting
Practical Use of Kohonen Neural Networks in Algorithmic Trading. Part II. Optimizing and forecasting

Practical Use of Kohonen Neural Networks in Algorithmic Trading. Part II. Optimizing and forecasting

Based on universal tools designed for working with Kohonen networks, we construct the system of analyzing and selecting the optimal EA parameters and consider forecasting time series. In Part I, we corrected and improved the publicly available neural network classes, having added necessary algorithms. Now, it is time to apply them to practice.
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Gradient Boosting (CatBoost) in the development of trading systems. A naive approach

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 used for preparing the data and for training the model.
An Example of Developing a Spread Strategy for Moscow Exchange Futures
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.
MQL5 Cookbook: Analyzing Position Properties in the MetaTrader 5 Strategy Tester
MQL5 Cookbook: Analyzing Position Properties in the MetaTrader 5 Strategy Tester

MQL5 Cookbook: Analyzing Position Properties in the MetaTrader 5 Strategy Tester

We will present a modified version of the Expert Advisor from the previous article "MQL5 Cookbook: Position Properties on the Custom Info Panel". Some of the issues we will address include getting data from bars, checking for new bar events on the current symbol, including a trade class of the Standard Library to a file, creating a function to search for trading signals and a function for executing trading operations, as well as determining trade events in the OnTrade() function.
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Brute force approach to pattern search (Part III): New horizons

Brute force approach to pattern search (Part III): New horizons

This article provides a continuation to the brute force topic, and it introduces new opportunities for market analysis into the program algorithm, thereby accelerating the speed of analysis and improving the quality of results. New additions enable the highest-quality view of global patterns within this approach.
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Experiments with neural networks (Part 1): Revisiting geometry

Experiments with neural networks (Part 1): Revisiting geometry

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.
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Brute force approach to pattern search (Part II): Immersion

Brute force approach to pattern search (Part II): Immersion

In this article we will continue discussing the brute force approach. I will try to provide a better explanation of the pattern using the new improved version of my application. I will also try to find the difference in stability using different time intervals and timeframes.
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Magic of time trading intervals with Frames Analyzer tool

Magic of time trading intervals with Frames Analyzer tool

What is Frames Analyzer? This is a plug-in module for any Expert Advisor for analyzing optimization frames during parameter optimization in the strategy tester, as well as outside the tester, by reading an MQD file or a database that is created immediately after parameter optimization. You will be able to share these optimization results with other users who have the Frames Analyzer tool to discuss the results together.
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Population optimization algorithms: Particle swarm (PSO)

Population optimization algorithms: Particle swarm (PSO)

In this article, I will consider the popular Particle Swarm Optimization (PSO) algorithm. Previously, we discussed such important characteristics of optimization algorithms as convergence, convergence rate, stability, scalability, as well as developed a test stand and considered the simplest RNG algorithm.
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Developing a Replay System — Market simulation (Part 03): Adjusting the settings (I)

Developing a Replay System — Market simulation (Part 03): Adjusting the settings (I)

Let's start by clarifying the current situation, because we didn't start in the best way. If we don't do it now, we'll be in trouble soon.
MQL5 Cloud Network: Are You Still Calculating?
MQL5 Cloud Network: Are You Still Calculating?

MQL5 Cloud Network: Are You Still Calculating?

It will soon be a year and a half since the MQL5 Cloud Network has been launched. This leading edge event ushered in a new era of algorithmic trading - now with a couple of clicks, traders can have hundreds and thousands of computing cores at their disposal for the optimization of their trading strategies.
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Testing different Moving Average types to see how insightful they are

Testing different Moving Average types to see how insightful they are

We all know the importance of the Moving Average indicator for a lot of traders. There are other Moving average types that can be useful in trading, we will identify these types in this article and make a simple comparison between each one of them and the most popular simple Moving average type to see which one can show the best results.
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Category Theory in MQL5 (Part 16): Functors with Multi-Layer Perceptrons

Category Theory in MQL5 (Part 16): Functors with Multi-Layer Perceptrons

This article, the 16th in our series, continues with a look at Functors and how they can be implemented using artificial neural networks. We depart from our approach so far in the series, that has involved forecasting volatility and try to implement a custom signal class for setting position entry and exit signals.
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Population optimization algorithms: Ant Colony Optimization (ACO)

Population optimization algorithms: Ant Colony Optimization (ACO)

This time I will analyze the Ant Colony optimization algorithm. The algorithm is very interesting and complex. In the article, I make an attempt to create a new type of ACO.
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Rebuy algorithm: Multicurrency trading simulation

Rebuy algorithm: Multicurrency trading simulation

In this article, we will create a mathematical model for simulating multicurrency pricing and complete the study of the diversification principle as part of the search for mechanisms to increase the trading efficiency, which I started in the previous article with theoretical calculations.
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How to choose an Expert Advisor: Twenty strong criteria to reject a trading bot

How to choose an Expert Advisor: Twenty strong criteria to reject a trading bot

This article tries to answer the question: how can we choose the right expert advisors? Which are the best for our portfolio, and how can we filter the large trading bots list available on the market? This article will present twenty clear and strong criteria to reject an expert advisor. Each criterion will be presented and well explained to help you make a more sustained decision and build a more profitable expert advisor collection for your profits.
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MQL5 Wizard techniques you should know (Part 06): Fourier Transform

MQL5 Wizard techniques you should know (Part 06): Fourier Transform

The Fourier transform introduced by Joseph Fourier is a means of deconstructing complex data wave points into simple constituent waves. This feature could be resourceful to traders and this article takes a look at that.
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Introduction to MQL5 (Part 1): A Beginner's Guide into Algorithmic Trading

Introduction to MQL5 (Part 1): A Beginner's Guide into Algorithmic Trading

Dive into the fascinating realm of algorithmic trading with our beginner-friendly guide to MQL5 programming. Discover the essentials of MQL5, the language powering MetaTrader 5, as we demystify the world of automated trading. From understanding the basics to taking your first steps in coding, this article is your key to unlocking the potential of algorithmic trading even without a programming background. Join us on a journey where simplicity meets sophistication in the exciting universe of MQL5.
MQL5 Cookbook: Reducing the Effect of Overfitting and Handling the Lack of Quotes
MQL5 Cookbook: Reducing the Effect of Overfitting and Handling the Lack of Quotes

MQL5 Cookbook: Reducing the Effect of Overfitting and Handling the Lack of Quotes

Whatever trading strategy you use, there will always be a question of what parameters to choose to ensure future profits. This article gives an example of an Expert Advisor with a possibility to optimize multiple symbol parameters at the same time. This method is intended to reduce the effect of overfitting parameters and handle situations where data from a single symbol are not enough for the study.
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Visual evaluation of optimization results

Visual evaluation of optimization results

In this article, we will consider how to build graphs of all optimization passes and to select the optimal custom criterion. We will also see how to create a desired solution with little MQL5 knowledge, using the articles published on the website and forum comments.
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MQL5 Wizard techniques you should know (Part 01): Regression Analysis

MQL5 Wizard techniques you should know (Part 01): Regression Analysis

Todays trader is a philomath who is almost always (either consciously or not...) 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. This clearly places a premium on the trader's time and the need to avoid mistakes. 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.
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Developing a Replay System — Market simulation (Part 01): First experiments (I)

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.
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MQL5 Wizard techniques you should know (Part 05): Markov Chains

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.
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Understand and Use MQL5 Strategy Tester Effectively

Understand and Use MQL5 Strategy Tester Effectively

There is an essential need for MQL5 programmers or developers to master important and valuable tools. One of these tools is the Strategy Tester, this article is a practical guide to understanding and using the strategy tester of MQL5.
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Trading strategy based on the improved Doji candlestick pattern recognition indicator

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.
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Developing a Replay System — Market simulation (Part 02): First experiments (II)

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.
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Category Theory in MQL5 (Part 14): Functors with Linear-Orders

Category Theory in MQL5 (Part 14): Functors with Linear-Orders

This article which is part of a broader series on Category Theory implementation in MQL5, delves into Functors. We examine how a Linear Order can be mapped to a set, thanks to Functors; by considering two sets of data that one would typically dismiss as having any connection.
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Monte Carlo Permutation Tests in MetaTrader 5

Monte Carlo Permutation Tests in MetaTrader 5

In this article we take a look at how we can conduct permutation tests based on shuffled tick data on any expert advisor using only Metatrader 5.
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Developing an Expert Advisor from scratch (Part 30): CHART TRADE as an indicator?

Developing an Expert Advisor from scratch (Part 30): CHART TRADE as an indicator?

Today we are going to use Chart Trade again, but this time it will be an on-chart indicator which may or may not be present on the chart.
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Category Theory (Part 9): Monoid-Actions

Category Theory (Part 9): Monoid-Actions

This article continues the series on category theory implementation in MQL5. Here we continue monoid-actions as a means of transforming monoids, covered in the previous article, leading to increased applications.
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Parallel Particle Swarm Optimization

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 Expert Advisor and in a parallel multi-threaded mode as an add-on that runs on local tester agents.
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MQL5 Wizard techniques you should know (Part 03): Shannon's Entropy

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.
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Developing a Replay System — Market simulation (Part 21): FOREX (II)

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.
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Developing a Replay System — Market simulation (Part 06): First improvements (I)

Developing a Replay System — Market simulation (Part 06): First improvements (I)

In this article, we will begin to stabilize the entire system, without which we might not be able to proceed to the next steps.
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Backpropagation Neural Networks using MQL5 Matrices

Backpropagation Neural Networks using MQL5 Matrices

The article describes the theory and practice of applying the backpropagation algorithm in MQL5 using matrices. It provides ready-made classes along with script, indicator and Expert Advisor examples.
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Continuous walk-forward optimization (Part 8): Program improvements and fixes

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 features and provides other improvements, which I found when working with the program.
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Population optimization algorithms: Grey Wolf Optimizer (GWO)

Population optimization algorithms: Grey Wolf Optimizer (GWO)

Let's consider one of the newest modern optimization algorithms - Grey Wolf Optimization. The original behavior on test functions makes this algorithm one of the most interesting among the ones considered earlier. This is one of the top algorithms for use in training neural networks, smooth functions with many variables.
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Experiments with neural networks (Part 2): Smart neural network optimization

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.
Population optimization algorithms
Population optimization algorithms

Population optimization algorithms

This is an introductory article on optimization algorithm (OA) classification. The article attempts to create a test stand (a set of functions), which is to be used for comparing OAs and, perhaps, identifying the most universal algorithm out of all widely known ones.
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Developing a Replay System — Market simulation (Part 20): FOREX (I)

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.