MQL4 and MQL5 Programming Articles

Did you know that the Golden Cross and Death Cross strategies, based on moving average crossovers, are some of the most reliable indicators for identifying long-term market trends? A Golden Cross signals a bullish trend when a shorter moving average crosses above a longer one, while a Death Cross indicates a bearish trend when the shorter average moves below. Despite their simplicity and effectiveness, manually applying these strategies often leads to missed opportunities or delayed trades.

Convolutional Neural Networks (CNNs) are renowned for their prowess in detecting patterns in images and videos, with applications spanning diverse fields. In this article, we explore the potential of CNNs to identify valuable patterns in financial markets and generate effective trading signals for MetaTrader 5 trading bots. Let us discover how this deep machine learning technique can be leveraged for smarter trading decisions.

In this article, we delve into enhancing the details of trading reports and delivering the final document via email in PDF format. This marks a progression from our previous work, as we continue exploring how to harness the power of MQL5 and Python to generate and schedule trading reports in the most convenient and professional formats. Join us in this discussion to learn more about optimizing trading report generation within the MQL5 ecosystem.

In the article, let’s improve library methods for correct display of multi-symbol multi-period standard indicators, which lines are displayed on the current symbol chart with a shift set in the settings. As well, let’s put things in order in methods of work with standard indicators and remove the redundant code to the library area in the final indicator program.

You must admit that it sounds alluringly - you become a fortunate possessor of a program that can develop for you a profitable automated trading system (ATC) within a few minutes. All you need is to enter desirable inputs and press Enter. And - here you are, take your ATC tested and having positive expected payoff. Where thousands of people spend thousands of hours on developing that very unique ATC, which will "wine and dine", these statements soundб to put it mildly, very hollow. On the one hand, this really looks a little larger than life... However, to my mind, this problem can be solved.

There are ten basic errors of a newcomer intrading: trading at market opening, undue hurry in taking profit, adding of lots in a losing position, closing positions starting with the best one, revenge, the most preferable positions, trading by the principle of 'bought for ever', closing of a profitable strategic position on the first day, closing of a position when alerted to open an opposite position, doubts.

The article considers an optimized version of the Market Profile indicator, where rendering with multiple graphical objects is replaced with rendering on a canvas - an object of the CCanvas class.

In this article, we create a canvas-based graphing tool in MQL5 for statistical correlation and linear regression analysis between two symbols, with draggable and resizable features. We incorporate ALGLIB for regression calculations, dynamic tick labels, data points, and a stats panel displaying slope, intercept, correlation, and R-squared. This interactive visualization aids in pair trading insights, supporting customizable themes, borders, and real-time updates on new bars

The moving averages are by far the best indicators for our AI models to predict. However, we can improve our accuracy even further by carefully transforming our data. This article will demonstrate, how you can build AI Models capable of forecasting further into the future than you may currently be practicing without significant drops to your accuracy levels. It is truly remarkable, how useful the moving averages are.

In the previous article, we introduced the DIAYN method, which offers the algorithm for learning a variety of skills. The acquired skills can be used for various tasks. But such skills can be quite unpredictable, which can make them difficult to use. In this article, we will look at an algorithm for learning predictable skills.

25 to 30% of all crashlogs received from users appear due to errors occurring when functions imported from custom dlls are executed.

In this discussion, we take a step forward to uncover the underlying price action hidden within candlestick wicks. By integrating a wick visualization feature into the Market Periods Synchronizer, we enhance the tool with greater analytical depth and interactivity. This upgraded system allows traders to visualize higher-timeframe price rejections directly on lower-timeframe charts, revealing detailed structures that were once concealed within the shadows.

This is the third article in a series describing the main aspects of MQL5 programming. This article covers complex data types that were not discussed in the previous article. These include structures, unions, classes, and the 'function' data type. It also explains how to add modularity to your program using the #include preprocessor directive.

We continue our work on creating the FinMem framework, which uses layered memory approaches that mimic human cognitive processes. This allows the model not only to effectively process complex financial data but also to adapt to new signals, significantly improving the accuracy and effectiveness of investment decisions in dynamically changing markets.

What is common between skydiving, Futures, Hawaii, translations and spies? We didn't know it until we've managed to communicate with disqualified participant Atsushi Yamanaka (alohafx). His has a creed "Life is Good!", and one can hardly doubt that. It was interesting to know that distances between the continents are not an obstacle for communication among our Championship's participants.

Today we interview Francisco García García (chuliweb) from Spain. A week ago his Expert Advisor reached the 8th place, but the unfortunate logic error in programming threw it from the first page of the Championship leaders. As confirmed by statistics, such an error is not uncommon for many participants.