Market Simulation (Part 23): Getting Started with SQL (VI)
In this article, we will see how to visualize a database and, from that, understand how it is structured. This is done by analyzing the database’s internal structure. Although this may seem unnecessary at first, it is fully justified if we really want to become database administrators. After all, some people make a living maintaining and designing databases.
From Basic to Intermediate: Function Pointers
You have probably already heard about pointers when it comes to programming. But did you know that we can use this kind of data here in MQL5? Of course, this must be done in a way that keeps us in control and avoids strange program behavior during execution. Still, because this is a resource with a very specific purpose and aimed at particular kinds of tasks, it is rare to hear anyone discuss what a pointer is and how to use it in MQL5.
Analyzing Price Time Gaps in MQL5 (Part II): Creating a Heat Map of Liquidity Distribution Over Time
A detailed guide on how to create a heat map indicator for MetaTrader 5 that visualizes the price distribution over time. The article reveals the mathematical basis of time density analysis, where each price level is colored from red (minimum stay time) to blue (maximum stay time).
Market Simulation (Part 24): Getting Started with SQL (VII)
In the previous article, we completed the necessary introduction to SQL. And, in my opinion, we properly clarified what we wanted to show and explain about SQL. This was done so that anyone who comes to look at the replication/simulation system being built can at least get an idea of what may be happening there. The point is that there is no sense in programming things that SQL handles perfectly.
From Basic to Intermediate: Objects (II)
In today's article, we will look at how to control some object properties in a simple way using code. We will also see how a custom application can place more than one object on the same chart. In addition, we will begin to understand the importance of assigning a short name to any indicator we plan to implement.
Market Microstructure in MQL5 (Part 4): Volatility That Remembers
This article adds eight volatility functions to MicroStructure_Foundation.mqh, including realized volatility, duration-adjusted volatility, fractional volatility, a FIGARCH-inspired proxy, a volatility clustering index, a GJR-GARCH asymmetry measure (using the Dube library), bipower-variation jump detection, and a wrapper function. The MFDFA implementation is revised to return the conventional Legendre-transform Δα with an R² confidence field, replacing the τ-spread proxy used in the original submission. Thresholds are derived from 514 NY sessions of NQ E-mini Nasdaq 100 futures (May 2024–May 2026); no new include file is created.
Interactive Supply and Demand Zone Manager in MQL5: From Manual to Automated Lifecycle
Replace static drawings with automated, stateful zones controlled by a CZone wrapper. The system synchronizes user rectangles, sizes zones by ATR, validates breakouts using consecutive closes, applies ghost/deactivation rules, merges nearby structures by a 1.5×ATR threshold, and projects edges forward. Traders gain durable levels that update themselves and reduce repetitive chart management.