History of MQL5.community development

The Darvas Box Breakout Strategy, created by Nicolas Darvas, is a technical trading approach that spots potential buy signals when a stock’s price rises above a set "box" range, suggesting strong upward momentum. In this article, we will apply this strategy concept as an example to explore three advanced machine learning techniques. These include using a machine learning model to generate signals rather than to filter trades, employing continuous signals rather than discrete ones, and using models trained on different timeframes to confirm trades.

In this article, we will explore and implement, methods for assessing model quality that utilize a single dataset as both training and validation sets.

In this article, we will share insights on how to leverage MQL5 programming to pinpoint market levels—differentiating between weaker and strongest price levels. We will fully develop a working, Support and Resistance Strength Indicator (SRSI).

We will consider the creation and updating of USD index (USDX) and EUR index (EURX) charts using a MetaTrader 5 service as an example. When launching the service, we will check for the presence of the required synthetic instrument, create it if necessary, and place it in the Market Watch window. The minute and tick history of the synthetic instrument is to be created afterwards followed by the chart of the created instrument.

The first of a series of articles looking at the mathematics of Custom Criteria with a specific focus on non-linear functions used in Neural Networks, MQL5 code for implementation and the use of targeted and correctional offsets.

The article discusses the Tabu Search algorithm, one of the first and most well-known metaheuristic methods. We will go through the algorithm operation in detail, starting with choosing an initial solution and exploring neighboring options, with an emphasis on using a tabu list. The article covers the key aspects of the algorithm and its features.

Moving Average and Stochastic Oscillator are very common indicators that some traders may not use a lot because of their lagging nature. In a 3-part ‘miniseries' that considers the 3 main forms of machine learning, we look to see if this bias against these indicators is justified, or they might be holding an edge. We do our examination in wizard assembled Expert Advisors.