Articles, Library comments - page 26

Check out the new article: Trend criteria. Conclusion . In this article, we will consider the specifics of applying some trend criteria in practice. We will also try to develop several new criteria. The focus will be on the efficiency of applying these criteria to market data analysis and trading

Imbalance Finder (FVG) : Imbalance Finder is an MT5 indicator that automatically detects bullish and bearish Fair Value Gaps (FVGs) and tracks whether each imbalance remains active, gets tapped, or becomes fully filled. It draws clear chart zones in real time, helps traders identify potential

ASQ PropFirm Shield : Institutional prop firm protection library for MetaTrader 5. Author: Muharrem Rogova

ASQ Recovery Engine : Intelligent anti-tilt risk management library for MetaTrader 5. Author: Muharrem Rogova

Root - Analizer : Binary Analizerr Author: Yevheniy Kopanitskyy

Root -Utility Diamond : Utility designed for opening BUY and SELL positions using Root - BinaryMiner Author: Yevheniy Kopanitskyy

Check out the new article: Swing Extremes and Pullbacks in MQL5 (Part 3): Defining Structural Validity Beyond Simple Highs/Lows . 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

ASQ Telegram Notifier : Professional Telegram integration library for MetaTrader 5 EAs. Author: Muharrem Rogova

ASQ Trade Frequency Controller : Runtime trade frequency adjustment library for MetaTrader 5. Author: Muharrem Rogova

ASQ Risk Analytics Engine : Institutional risk analysis library for MetaTrader 5. Zero external dependencies. Pure MQL5 mathematics. Author: Muharrem Rogova

ASQ Indicator Manager : Centralized indicator handle management library for MetaTrader 5 EAs. Author: Muharrem Rogova

New article How to Order a Trading Robot in MQL5 and MQL4 is published: With the launch of the "Jobs" service, the MQL5.community became an ideal place for placing orders and providing programming services. Thousands of traders and developers visit this resource on a daily basis, and can easily help

Pivot point : Line to change direction Author: namakulabu

ASQ NeuralNet Pure MQL5 Neural Network Library : Complete deep learning library in pure MQL5. Build, train and deploy neural networks natively in MetaTrader 5. No DLLs, no Python, no external APIs. Author: Muharrem Rogova

Check out the new article: Python-MetaTrader 5 Strategy Tester (Part 05): Multi-Symbols and Timeframes Strategy Tester . This article presents a MetaTrader 5–compatible backtesting workflow that scales across symbols and timeframes. We use HistoryManager to parallelize data collection, synchronize

Fair Value Gap FVG MT5 : Detects and draws Fair Value Gaps (price imbalances) on your chart — a core concept in ICT/Smart Money methodology. Tracks when price returns to fill the gap. Author: Kestutis Balciunas

Check out the new article: Market Simulation (Part 20): First steps in SQL (III) . Although we can perform operations on a database containing about 10 records, the material is absorbed much better when we work with a file that contains more than 15 thousand records. That is, if we tried to create

Check out the new article: MetaTrader 5 Machine Learning Blueprint (Part 10): Bet Sizing for Financial Machine Learning . Fixed fractions and raw probabilities misallocate risk under overlapping labels and induce overtrading. This article delivers four AFML-compliant sizers: probability-based

Monitoring Spread : Tools for monitoring spread of currency pairs Author: Alexey Sergeev

Check out the new article: Employing Game Theory Approaches in Trading Algorithms . We are creating an adaptive self-learning trading expert advisor based on DQN machine learning, with multidimensional causal inference. The EA will successfully trade simultaneously on 7 currency pairs. And agents of

Check out the new article: Market Simulation (Part 19): First Steps in SQL (II) . As we explained in the first article about SQL, there is no point in spending time programming procedures to do what is already built into SQL. However, without knowing the basics, you won’t be able to do anything with

BinanceQuotesDownloader : Real-time display of Binance quotes Author: Yuriy Lyachshenko

Check out the new article: MetaTrader 5 Machine Learning Blueprint (Part 9): Integrating Bayesian HPO into the Production Pipeline . ​ This article integrates the Optuna hyperparameter optimization (HPO) backend into a unified ModelDevelopmentPipeline. It adds joint tuning of model hyperparameters

Check out the new article: From Basic to Intermediate: Inheritance . No doubt, this article will require a significant amount of your time to understand how and why the materials described here work. This is because everything that will be shown here is initially oriented toward object-oriented

Check out the new article: Market Simulation (Part 18): First Steps in SQL (I) . It doesn't matter which SQL program we use: MySQL, SQL Server, SQLite, OpenSQL, or another. They all have something in common, and that common element is the SQL language. Even if we do not intend to use WorkBench, we

Stoch_Cross : Stoch_Cross monitors the %K and %D lines of the Stochastic Oscillator and provides instant confirmation when a bullish or bearish crossover occurs in the zone. Author: Lubexbill Semi

New interview Johnpaul77 Signal Providers: "Our Strategy Remains Profitable for More Than Three Years Now. So Why Would We Change It?" has been published: Let us reveal a little secret: MQL5.com website visitors spend most of their time on Johnpaul77 signal's page. It is a leader of our signal

Institutional Nadaraya-Watson Kernel Regression : A quantitative machine learning envelope that utilizes Nadaraya-Watson kernel regression math to dynamically project statistically significant mean-reversion zones without relying on traditional standard deviation. Author: Amanda Vitoria De Paula

New article Introduction to the Empirical Mode Decomposition Method is published: This article serves to familiarize the reader with the empirical mode decomposition (EMD) method. It is the fundamental part of the Hilbert–Huang transform and is intended for analyzing data from nonstationary and

Multi-Symbol Alert Panel : An indicator to watch highs/lows of all markets simultaneously. Author: Hammad Dilber