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 will be able to select a row in the optimization results table and receive a multi-symbol balance and drawdown graph on separate charts.
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.
The article implements an MQL application with a graphical interface for extended visualization of the optimization process. The graphical interface applies the last version of EasyAndFast library. Many users may ask why they need graphical interfaces in MQL applications. This article demonstrates one of multiple cases where they can be useful for traders.
The Strategy Tester in the MetaTrader 5 trading platform provides only two optimization options: complete search of parameters and genetic algorithm. This article proposes a new method for optimizing trading strategies — Simulated annealing. The method's algorithm, its implementation and integration into any Expert Advisor are considered. The developed algorithm is tested on the Moving Average EA.
Different situations happen in trader’s life. Often, the history of successful trades allows us to restore a strategy, while looking at a loss history we try to develop and improve it. In both cases, we compare trades with known indicators. This article suggests methods of batch comparison of trades with a number of indicators.
Mini Market Emulator is an indicator designed for partial emulation of work in the terminal. Presumably, it can be used to test "manual" strategies of market analysis and trading.
Using the object-oriented approach in MQL5 greatly simplifies the creation of multi-currency/multi-system /multi-time-frame Expert Advisors. Just imagine, your single EA trades on several dozens of trading strategies, on all of the available instruments, and on all of the possible time frames! In addition, the EA is easily tested in the tester, and for all of the strategies, included in its composition, it has one or several working systems of money management.
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.
The article deals with a simple approach to creating an automated trading system based on the chart linear markup and offers a ready-made Expert Advisor using the standard properties of the MetaTrader 4 and 5 objects and supporting the main trading operations.
The article provides the analysis of the following patterns: Flag, Pennant, Wedge, Rectangle, Contracting Triangle, Expanding Triangle. In addition to analyzing their similarities and differences, we will create indicators for detecting these patterns on the chart, as well as a tester indicator for the fast evaluation of their effectiveness.
It is time to briefly summarize the information provided in the previous articles on position properties. In this article, we will create a few additional functions to get the properties that can only be obtained after accessing the history of deals. We will also get familiar with data structures that will allow us to access position and symbol properties in a more convenient way.
This article explains the step by step process of identifying and resolving code errors as well as the steps in testing and optimizing of the Expert Advisor input parameters. You will learn how to use Strategy Tester of MetaTrader 5 client terminal to find the best symbol and set of input parameters for your Expert Advisor.
MetaTrader 5 allows us to simulate automatic trading, within an embedded strategy tester, by using Expert Advisors and the MQL5 language. This type of simulation is called testing of Expert Advisors, and can be implemented using multithreaded optimization, as well as simultaneously on a number of instruments. In order to provide a thorough testing, a generation of ticks based on the available minute history, needs to be performed. This article provides a detailed description of the algorithm, by which the ticks are generated for the historical testing in the MetaTrader 5 client terminal.
Analysis of the trade history and plotting distribution charts of trading results in HTML depending on position entry time. The charts are displayed in three sections - by hours, by days of the week and by months.
Before the first single test, every trader faces the same question — "Which of the four modes to use?" Each of the provided modes has its advantages and features, so we will do it the easy way - run all four modes at once with a single button! The article shows how to use the Win API and a little magic to see all four testing chart at the same time.
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.
MQL5.community Market provides Expert Advisors developers with the already formed market consisting of thousands of potential customers. This is the best place for selling trading robots and technical indicators!
There are a lot of measures that allow determining the effectiveness and profitability of a trade system. However, traders are always ready to put any system to a new crash test. The article tells how the statistics based on measures of effectiveness can be used for the MetaTrader 5 platform. It includes the class for transformation of the interpretation of statistics by deals to the one that doesn't contradict the description given in the "Statistika dlya traderov" ("Statistics for Traders") book by S.V. Bulashev. It also includes an example of custom function for optimization.
The article highlights several methods for trend identification aiming to determine the trend duration relative to the flat market. In theory, the trend to flat rate is considered to be 30% to 70%. This is what we'll be checking.
In this article, we develop and tests several strategies based on the Donchian channel using various indicator filters. We also perform a comparative analysis of their operation.
The article provides a brief overview of ten trend following strategies, as well as their testing results and comparative analysis. Based on the obtained results, we draw a general conclusion about the appropriateness, advantages and disadvantages of trend following trading.
The article provides the results of testing a simple trading strategy in three modes: "1 minute OHLC", "Every tick" and "Every tick based on real ticks" using actual historical data.
How to make the testing process more visual? The answer is simple: you need to use one or more indicators in the Strategy Tester, including a tick indicator, an indicator of balance and equity, an indicator of drawdown and deposit load. This solution will help you visually track the nature of ticks, balance and equity changes, as well as drawdown and deposit load.
This article describes the usage of the TesterWithDrawal() function for estimating risks in trade systems which imply the withdrawing of a certain part of assets during their operation. In addition, it describes the effect of this function on the algorithm of calculation of the drawdown of equity in the strategy tester. This function is useful when optimizing parameter of your Expert Advisors.
When communicating in various forums, I often used examples of my test results displayed as screenshots of Microsoft Excel charts. I have many times been asked to explain how such charts can be created. Finally, I now have some time to explain it all in this article.
We continue the series of articles on MQL5 programming. This time we will see how to get results of each optimization pass right during the Expert Advisor parameter optimization. The implementation will be done so as to ensure that if the conditions specified in the external parameters are met, the corresponding pass values will be written to a file. In addition to test values, we will also save the parameters that brought about such results.
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.
This article will describe an implementation of a simple approach suitable for a multi-currency Expert Advisor. This means that you will be able to set up the Expert Advisor for testing/trading under identical conditions but with different parameters for each symbol. As an example, we will create a pattern for two symbols but in such a way so as to be able to add additional symbols, if necessary, by making small changes to the code.
In this article, we will develop a framework for a trading system based on the Triple Screen strategy in MQL5. The Expert Advisor will not be developed from scratch. Instead, we will simply modify the program from the previous article "MQL5 Cookbook: Using Indicators to Set Trading Conditions in Expert Advisors" which already substantially serves our purpose. So the article will also demonstrate how you can easily modify patterns of ready-made programs.
In this article, we will continue to modify the Expert Advisor we have been working on throughout the preceding articles of the MQL5 Cookbook series. This time, the Expert Advisor will be enhanced with indicators whose values will be used to check position opening conditions. To spice it up, we will create a drop-down list in the external parameters to be able to select one out of three trading indicators.
In continuation of our work on the Expert Advisor from the previous article of the series called "MQL5 Cookbook: Analyzing Position Properties in the MetaTrader 5 Strategy Tester", we will enhance it with a whole lot of useful functions, as well as improve and optimize the existing ones. The Expert Advisor will this time have external parameters that can be optimized in the MetaTrader 5 Strategy Tester and will in some ways resemble a simple trading system.
MetaEditor 5 has the debugging feature. But when you write your MQL5 programs, you often want to display not the individual values, but all messages that appear during testing and online work. When the log file contents have large size, it is obvious to automate quick and easy retrieval of required message. In this article we will consider ways of finding errors in MQL5 programs and methods of logging. Also we will simplify logging into files and will get to know a simple program LogMon for comfortable viewing of logs.
The article presents a new metaheuristic optimization Circle Search Algorithm (CSA) based on the geometric properties of a circle. The algorithm uses the principle of moving points along tangents to find the optimal solution, combining the phases of global exploration and local exploitation.
If we are going to automate periodic optimization, we need to think about auto updates of the settings of the EAs already running on the trading account. This should also allow us to run the EA in the strategy tester and change its settings within a single run.
We commence a new article series that builds upon our earlier efforts laid out in the MQL5 Wizard series, by taking them further as we step up our approach to systematic trading and strategy testing. Within these new series, we’ll concentrate our focus on Expert Advisors that are coded to hold only a single type of position - primarily longs. Focusing on just one market trend can simplify analysis, lessen strategy complexity and expose some key insights, especially when dealing in assets beyond forex. Our series, therefore, will investigate if this is effective in equities and other non-forex assets, where long only systems usually correlate well with smart money or institution strategies.
We continue our new series on Market-Positioning, where we study particular assets, with specific trade directions over manageable test windows. We started this by considering Nvidia Corp stock in the last article, where we covered 5 signal patterns from the complimentary pairing of the RSI and DeMarker oscillators. For this article, we cover the remaining 5 patterns and also delve into multi-pattern options that not only feature untethered combinations of all ten, but also specialized combinations of just a pair.
We aim to create a system for automatic periodic optimization of trading strategies used in one final EA. As the system evolves, it becomes increasingly complex, so it is necessary to look at it as a whole from time to time in order to identify bottlenecks and suboptimal solutions.
Trading without session awareness is like navigating without a compass—you're moving, but not with purpose. Today, we're revolutionizing how traders perceive market timing by transforming ordinary charts into dynamic geographical displays. Using MQL5's powerful visualization capabilities, we'll build a live world map that illuminates active trading sessions in real-time, turning abstract market hours into intuitive visual intelligence. This journey sharpens your trading psychology and reveals professional-grade programming techniques that bridge the gap between complex market structure and practical, actionable insight.
In this article, we will look at how to connect a new strategy to the auto optimization system we have created. Let's see what kind of EAs we need to create and whether it will be possible to do without changing the EA library files or minimize the necessary changes.
The article presents a new metaheuristic algorithm, Chaos Game Optimization (CGO), which demonstrates a unique ability to maintain high efficiency when dealing with high-dimensional problems. Unlike most optimization algorithms, CGO not only does not lose, but sometimes even increases performance when scaling a problem, which is its key feature.