6 new topics on forum:
- Optimize or try new strategies?
- EA designed to bypass the Broker's detection systems even "AutoTrading disabled by server”.
- MT5 VPS memory consumption

We are making a remote professional risk manager for Forex in Python, deploying it on the server step by step. In the course of the article, we will understand how to programmatically manage Forex risks, and how not to waste a Forex deposit any more.

In this article, we demonstrate an easy way to install MetaTrader 5 on popular Linux versions — Ubuntu and Debian. These systems are widely used on server hardware as well as on traders’ personal computers.

How to purchase a trading robot from the MetaTrader Market and to install it?
A product from the MetaTrader Market can be purchased on the MQL5.com website or straight from the MetaTrader 4 and MetaTrader 5 trading platforms. Choose a desired product that suits your trading style, pay for it using your preferred payment method, and activate the product.
How to Test a Trading Robot Before Buying
Buying a trading robot on MQL5 Market has a distinct benefit over all other similar options - an automated system offered can be thoroughly tested directly in the MetaTrader 5 terminal. Before buying, an Expert Advisor can and should be carefully run in all unfavorable modes in the built-in Strategy Tester to get a complete grasp of the system.

In this article, we will continue to connect the new strategy to the created auto optimization system. Let's look at what changes need to be made to the optimization project creation EA, as well as the second and third stage EAs.

In this article we introduce Python-MetaTrader5-like ways of handling trading operations such as opening, closing, and modifying orders in the simulator. To ensure the simulation behaves like MT5, a strict validation layer for trade requests is implemented, taking into account symbol trading parameters and typical brokerage restrictions.

In this article, we enhance the Smart WaveTrend Crossover indicator in MQL5 by integrating canvas-based drawing for fog gradient overlays, signal boxes that detect breakouts, and customizable buy/sell bubbles or triangles for visual alerts. We incorporate risk management features with dynamic take-profit and stop-loss levels calculated via candle multipliers or percentages, displayed through lines and a table, alongside options for trend filtering and box extensions.

This article presents the design and MetaTrader 5 implementation of the Candle Pressure Index (CPI)—a CLV-based overlay that visualizes intra-Bar buying and selling pressure directly on price charts. The discussion focuses on candle structure, pressure classification, visualization mechanics, and a non-repainting, transition-based alert system designed for consistent behavior across timeframes and instruments.

Discover how to detect user actions in MetaTrader 5, send requests to an AI API, extract responses, and implement scrolling text in your panel.

Today's article is a continuation of the previous one. We will look at the implementation of an Expert Advisor, focusing mainly on how the server code is executed. The code given in the previous article is not enough to make everything work as expected, so we need to dig a little deeper into it. Therefore, it is necessary to read both articles to better understand what will happen.

In this article, we demonstrate an easy way to install MetaTrader 5 on popular Linux versions — Ubuntu and Debian. These systems are widely used on server hardware as well as on traders’ personal computers.

Larry Williams Market Secrets (Part 2): Automating a Market Structure Trading System
Learn how to automate Larry Williams market structure concepts in MQL5 by building a complete Expert Advisor that reads swing points, generates trade signals, manages risk, and applies a dynamic trailing stop strategy.

From Novice to Expert: Higher Probability Signals
In high-probability support and resistance zones, valid entry confirmation signals are always present once the zone has been correctly identified. In this discussion, we build an intelligent MQL5 program that automatically detects entry conditions within these zones. We leverage well-known candlestick patterns alongside native confirmation indicators to validate trade decisions. Click to read further.

We continue to explore the innovative Chimera framework – a two-dimensional state-space model that uses neural network technologies to analyze multidimensional time series. This method provides high forecasting accuracy with low computational cost.

This article explores the development of an ensemble algorithmic trading strategy for the EURUSD market that combines the Bollinger Bands and the Relative Strength Indicator (RSI). Initial rule-based strategies produced high-quality signals but suffered from low trade frequency and limited profitability. Multiple iterations of the strategy were evaluated, revealing flaws in our understanding of the market, increased noise, and degraded performance. By appropriately employing statistical learning algorithms, shifting the modeling target to technical indicators, applying proper scaling, and combining machine learning forecasts with classical trading rules, the final strategy achieved significantly improved profitability and trade frequency while maintaining acceptable signal quality.

In this article, we build a correlation matrix dashboard in MQL5 to compute asset relationships using Pearson, Spearman, and Kendall methods over a set timeframe and bars. The system offers standard mode with color thresholds and p-value stars, plus heatmap mode with gradient visuals for correlation strengths. It includes an interactive UI with timeframe selectors, mode toggles, and a dynamic legend for efficient analysis of symbol interdependencies.

In this article, we will examine the movements of synthetic currencies using Python and MQL5 and explore how feasible Forex arbitrage is today. We will also consider ready-made Python code for analyzing synthetic currencies and share more details on what synthetic currencies are in Forex.

This is a specialized trend-following EA that makes both short and long-term analyses, trading decisions, and executions based on the overall trend and its strength. This article will explore in detail an EA that is specifically designed for traders who are patient, disciplined, and focused enough to only execute trades and hold their positions only when trading with strength and in the trend direction without changing their bias frequently, especially against the trend, until take-profit targets are hit.

This article explores a method that combines Heikin‑Ashi smoothing with EMA20 High and Low boundaries and an EMA50 trend filter to improve trade clarity and timing. It demonstrates how these tools can help traders identify genuine momentum, filter out noise, and better navigate volatile or trending markets.