Articles on strategy testing in MQL5

Here we will start bringing together different components or applications that were previously completely isolated from each other. Chart Trade, the mouse indicator, and the Expert Advisor had already been linked to one another, but there was still no way to directly display on the chart the positions open on the trading server, which are often managed using a cross-order system. From this point on, this becomes possible, opening the way for various ideas and future implementations. Although we are only beginning to put these components into operation, we already have a direction for further development.

The article examines two practical aspects of the Adwizard-based optimization pipeline: diagnostics and recovery after failures when generating the final Expert Advisor database, as well as preliminary selection of strategy parameter ranges before project creation. It is shown how analyzing the stages/jobs/tasks tables in SQLite and restarting stages based on their statuses help restore the process, while trial optimization narrows the search space, eliminates redundant parameters, and reduces the risk of getting stuck at local maxima.

In this article, we will implement a number of improvements to ensure that the position indicator accurately reflects the actual state on the trading server in terms of open positions and their current state. I should point out that the applications shown here are in no way intended to replace any of the elements available in MetaTrader 5. They should also not be used without due caution and a balanced approach, since their purpose is to provide educational code—that is, code intended solely for learning how the system works. The reason I call this code “educational” is that, in some cases, using messages is not the best way to implement certain functions.

In this article, I have shown—in the clearest possible way—how to modify and improve code capable of handling specific tasks while making as few changes as possible to the existing code. We will add a volume display and, at the same time, ensure that users or traders cannot effectively remove objects created by the position indicator.

Until now, the application being developed as part of this series of articles has focused exclusively on simulating the graphical part. However, to obtain a more complete system in which we can test the Expert Advisor within the replay/simulation service, we also need to simulate the trading server. You'll notice that this simulation will include only the most essential elements. Nevertheless, you, dear reader, will be able to fill in the missing parts. Since these additional components don't affect what I want to show, we already have more than enough to implement what we have in mind.

This article implements the Probability of Backtest Overfitting in MQL5 with Combinatorially Symmetric Cross-Validation. It shows how to build the bar-by-bar returns matrix of a parameter grid, aggregate it by blocks and rank the in-sample winner out-of-sample across every split of the history. You get a single probability that this winner ends up in the lower half of the grid out-of-sample, along with the MQL5 code to compute it on your own optimizations.

In this article, we will make the necessary changes so that the position indicator displays the financial result. This way, the trader will be able to get an idea of the financial result of an open position. In addition, I will tell you something that many people do not know, even those who have been using MQL5 for a long time: how to use static variables to share memory and avoid declaring a global variable in the main code.

We're entering the home stretch. The development of the replay/simulation system is nearly complete. Of course, we still have a few things left to finish, but compared to everything we've already done, completing what's left won't be difficult. However, it is essential to fully absorb and understand everything covered in this article. So I hope you enjoy reading this and, above all, that you enjoy this final stage of the journey.

In the previous article, we looked at an example of implementing a class in MQL5 to provide basic support. Its purpose is specifically to allow SQL code to be stored in a separate script file. This way, we won't need to write the same SQL statements as string literals in the MQL5 source code. Although this solution is functional, there are some aspects of it that we can and should improve.

Although many people believe that we can easily embed SQL code into other code, this is usually not the case. The reason is that the SQL code is included in the executable as a string. Embedding SQL code as a string, while not a problem for small snippets, can ultimately cause us quite a few headaches.

Property-based tests exercise a sizing rule across thousands of generated scenarios instead of a few hand-picked cases. A deterministic MQL5 runner creates seeded symbol contracts, checks eight risk-volume properties, and writes text and CSV reports for reproducible evidence. A second script intentionally rounds volume the wrong way, replays the failing seed, and shrinks the counterexample to the half-step boundary, making the defect minimal and diagnosable.