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Articles on strategy testing in MQL5
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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Combinatorics and probability theory for trading (Part I): The basics
In this series of article, we will try to find a practical application of probability theory to describe trading and pricing processes. In the first article, we will look into the basics of
Brute force approach to pattern search (Part IV): Minimal functionality
The article presents an improved brute force version, based on the goals set in the previous article. I will try to cover this topic as broadly as possible using Expert Advisors with settings obtained
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
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
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
Brute force approach to pattern search
In this article, we will search for market patterns, create Expert Advisors based on the identified patterns, and check how long these patterns remain valid, if they ever retain their validity
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
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
Custom symbols: Practical basics
The article is devoted to the programmatic generation of custom symbols which are used to demonstrate some popular methods for displaying quotes. It describes a suggested variant of minimally invasive
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
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
Continuous Walk-Forward Optimization (Part 7): Binding Auto Optimizer's logical part with graphics and controlling graphics from the program
This article describes the connection of the graphical part of the auto optimizer program with its logical part. It considers the optimization launch process, from a button click to task redirection
Continuous Walk-Forward Optimization (Part 6): Auto optimizer's logical part and structure
We have previously considered the creation of automatic walk-forward optimization. This time, we will proceed to the internal structure of the auto optimizer tool. The article will be useful for all
Continuous Walk-Forward Optimization (Part 5): Auto Optimizer project overview and creation of a GUI
This article provides further description of the walk-forward optimization in the MetaTrader 5 terminal. In previous articles, we considered methods for generating and filtering the optimization
Continuous Walk-Forward Optimization (Part 4): Optimization Manager (Auto Optimizer)
The main purpose of the article is to describe the mechanism of working with our application and its capabilities. Thus the article can be treated as an instruction on how to use the application. It
Continuous Walk-Forward Optimization (Part 3): Adapting a Robot to Auto Optimizer
The third part serves as a bridge between the previous two parts: it describes the mechanism of interaction with the DLL considered in the first article and the objects for report downloading, which
SQLite: Native handling of SQL databases in MQL5
The development of trading strategies is associated with handling large amounts of data. Now, you are able to work with databases using SQL queries based on SQLite directly in MQL5. An important
Continuous Walk-Forward Optimization (Part 2): Mechanism for creating an optimization report for any robot
The first article within the Walk-Through Optimization series described the creation of a DLL to be used in our auto optimizer. This continuation is entirely devoted to the MQL5 language
Exploring Seasonal Patterns of Financial Time Series with Boxplot
In this article we will view seasonal characteristics of financial time series using Boxplot diagrams. Each separate boxplot (or box-and-whiskey diagram) provides a good visualization of how values
Continuous Walk-Forward Optimization (Part 1): Working with Optimization Reports
The first article is devoted to the creation of a toolkit for working with optimization reports, for importing them from the terminal, as well as for filtering and sorting the obtained data
MQL5 Cookbook: Trading strategy stress testing using custom symbols
The article considers an approach to stress testing of a trading strategy using custom symbols. A custom symbol class is created for this purpose. This class is used to receive tick data from
Merrill patterns
In this article, we will have a look at Merrill patterns' model and try to evaluate their current relevance. To do this, we will develop a tool to test the patterns and apply the model to various data
Optimization management (Part II): Creating key objects and add-on logic
This article is a continuation of the previous publication related to the creation of a graphical interface for optimization management. The article considers the logic of the add-on. A wrapper for
Optimization management (Part I): Creating a GUI
This article describes the process of creating an extension for the MetaTrader terminal. The solution discussed helps to automate the optimization process by running optimizations in other terminals
Extract profit down to the last pip
The article describes an attempt to combine theory with practice in the algorithmic trading field. Most of discussions concerning the creation of Trading Systems is connected with the use of historic
Color optimization of trading strategies
In this article we will perform an experiment: we will color optimization results. The color is determined by three parameters: the levels of red, green and blue (RGB). There are other color coding
Studying candlestick analysis techniques (Part II): Auto search for new patterns
In the previous article, we analyzed 14 patterns selected from a large variety of existing candlestick formations. It is impossible to analyze all the patterns one by one, therefore another solution
Studying candlestick analysis techniques (part I): Checking existing patterns
In this article, we will consider popular candlestick patterns and will try to find out if they are still relevant and effective in today's markets. Candlestick analysis appeared more than 20 years
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
Separate optimization of a strategy on trend and flat conditions
The article considers applying the separate optimization method during various market conditions. Separate optimization means defining trading system's optimal parameters by optimizing for an uptrend
100 best optimization passes (part 1). Developing optimization analyzer
The article dwells on the development of an application for selecting the best optimization passes using several possible options. The application is able to sort out the optimization results by a
Modeling time series using custom symbols according to specified distribution laws
The article provides an overview of the terminal's capabilities for creating and working with custom symbols, offers options for simulating a trading history using custom symbols, trend and various
Using indicators for optimizing Expert Advisors in real time
Efficiency of any trading robot depends on the correct selection of its parameters (optimization). However, parameters that are considered optimal for one time interval may not retain their
Automated Optimization of an EA for MetaTrader 5
This article describes the implementation of a self-optimization mechanism under MetaTrader 5
Developing stock indicators featuring volume control through the example of the delta indicator
The article deals with the algorithm of developing stock indicators based on real volumes using the CopyTicks() and CopyTicksRange() functions. Some subtle aspects of developing such indicators, as
Visualizing optimization results using a selected criterion
In the article, we continue to develop the MQL application for working with optimization results. This time, we will show how to form the table of the best results after optimizing the parameters by
Applying the Monte Carlo method for optimizing trading strategies
Before launching a robot on a trading account, we usually test and optimize it on quotes history. However, a reasonable question arises: how can past results help us in the future? The article
Visual strategy builder. Creating trading robots without programming
This article presents a visual strategy builder. It is shown how any user can create trading robots and utilities without programming. Created Expert Advisors are fully functional and can be tested in
Processing optimization results using the graphical interface
This is a continuation of the idea of processing and analysis of optimization results. This time, our purpose is to select the 100 best optimization results and display them in a GUI table. The user
Multi-symbol balance graph in MetaTrader 5
The article provides an example of an MQL application with its graphical interface featuring multi-symbol balance and deposit drawdown graphs based on the last test results