Articles with MQL5 programming examples

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During sideways price movements, traders face excessive signals from multiple moving average crossovers. Today, we discuss how ALGLIB preprocesses raw price data to produce filtered crossover layers, which can also generate alerts when they occur. Join this discussion to learn how a mathematical library can be leveraged in MQL5 programs.

In this article, I will consider creation of descendant objects for the terminal abstract standard graphical object. The class object describes the properties that are common for all graphical objects. So, it is simply some kind of a graphical object. To clarify its affiliation with a real graphical object, we need to set the properties inherent in this particular graphical object in the descendant object class.

What indicator of trading alerts or just the methods of their calculating to use is usually decided when testing EAs using these alerts. However, it is not always possible/necessary/reasonable to write an EA for each indicator. You can promptly calculate the profitability of trading on the alerts from other indicators, using a special indicator that collects their alerts itself and draws a picture of ideal trading with them. It can help you both make a visual estimate of the results obtained and quickly choose most optimal parameters.

How best can we combine multiple strategies to create a powerful ensemble strategy? Join us in this discussion as we look to fit together three different strategies into our trading application. Traders often employ specialized strategies for opening and closing positions, and we want to know if our machines can perform this task better. For our opening discussion, we will get familiar with the faculties of the strategy tester and the principles of OOP we will need for this task.

In this article we explore the application of digital filters on time series represented in the frequency domain so as to extract unique features that may be useful to prediction models.

Fibonacci levels provide a practical framework that markets often respect, highlighting price zones where reactions are more likely. In this article, we build an expert advisor that applies Fibonacci retracement logic to anticipate likely future moves and trade retracements with pending orders. Explore the full workflow—from swing detection to level plotting, risk controls, and execution.

In this article, I will place header scrolling control buttons in TabControl WinForms object in case the header bar does not fit the size of the control. Besides, I will implement the shift of the header bar when clicking on the cropped tab header.

Gamma and Delta measure how an option’s value reacts to changes in the underlying asset’s price. Delta represents the rate of change of the option’s price relative to the underlying, while Gamma measures how Delta itself changes as price moves. Together, they describe an option’s directional sensitivity and convexity—critical for dynamic hedging and volatility-based trading strategies.

The article presents a systematic approach to news trading in MetaTrader 5 using the built-in economic calendar: data structure, API functions, time synchronization rules, and event filtering. Methods of caching and incremental updating without overloading the server are described. The article also provides a working mechanism for exporting history to an .EX5 resource for deterministic testing using the same algorithm.

In the article, consider creation of multi-symbol multi-period standard indicator Accumulation/Distribution. Slightly improve library classes with respect to indicators so that, the programs developed for outdated platform MetaTrader 4 based on this library could work normally when switching over to MetaTrader 5.

In this discussion, we will develop an indicator to identify price zones created by strong market activity, such as impulsive moves, structure shifts, and liquidity events. These zones represent areas where the market has left “memory” due to unfilled orders or rapid price displacement. By marking these regions on the chart, the indicator highlights where price is statistically more likely to revisit and react in the future.

In this article, I will fix the names of WinForms object class methods and create Button and RadioButton WinForms objects.

Discover how to leverage MQL5 to forecast the S&P 500 with precision, blending in classical technical analysis for added stability and combining algorithms with time-tested principles for robust market insights.

In the previous article, I implemented the ability to move pivot points of an extended graphical object using control forms. Now I am going to implement the ability to move a composite graphical object using a single graphical object control point (form).

This article presents an MQL5 Expert Advisor that upgrades raw swing detection to a rule-based Structural Validation Engine. Swings are confirmed by a break of structure, displacement, liquidity sweeps, or time-based respect, then linked to a liquidity map and a structural state machine. The result is context-aware entries and stops anchored to validated levels, helping filter noise and systematize execution.

Numerous attempts to apply statistical methods to the objective reality, i.e. to financial series, crash when met with the nonstationarity of processes, "fat tails" of accompanying probability distributions, and insufficient volume of financial data.In this publication I will try to refer not to the financial series as such, but to their subjective presentation - in this case, to the way a trader tries to halter the series, i.e. to the trading system. The eduction of statistical regularities of the trading results process is a rather enthralling task. In some cases quite true conclusions about the model of this process can be made, and these can be applied to the trading system.

In the article, I will create the class of the standard graphical object memory allowing the object to save its states when its properties are modified. In turn, this allows retracting to the previous graphical object states.

In this article, I will implement handling Padding (internal indents/margin on all sides of an element) and Dock parameters (the way an object is located inside its container).

Machine learning has become a popular method for strategy development. Whilst there has been more emphasis on maximizing profitability and prediction accuracy , the importance of processing the data used to build predictive models has not received a lot of attention. In this article we consider using the concept of entropy to evaluate the appropriateness of indicators to be used in predictive model building as documented in the book Testing and Tuning Market Trading Systems by Timothy Masters.