Articles on the MQL5 programming and use of technical indicators

The article deals with creating a collection class of indicator buffer objects. I am going to test the ability to create and work with any number of buffers for indicators (the maximum number of buffers that can be created in MQL indicators is 512).

This article develops a practical MQL5 indicator that identifies Hidden Smash Day bars by strict numeric criteria and optional confirmation on the following session. We cover detection routines, buffer registration, and plot configuration to place arrows at valid bars. The approach delivers stable, non-repainting signals for historical testing and real-time monitoring.

Head and Shoulders patterns are difficult to identify consistently in live market data due to noise and structural ambiguity. This article presents a structured, triangle-based MQL5 indicator that isolates pattern components, constructs the neckline, and validates formations using ATR, symmetry, and slope constraints. The system detects and draws standard and inverse patterns, assigns a quality score, and confirms breakouts with optional alerts, enabling consistent and rule-based chart analysis.

In this article, I will make additional changes to the CCI affecting the very logic of this indicator. Moreover, we will be able to see it in the main chart window.

Here I will show how to create screens with price tickers which are usually used to display quotes on the exchange. I will do it by only using MQL5, without using complex external programming.

In this article, we create a Pivot-Based Trend Indicator in MQL5 that calculates fast and slow pivot lines over user-defined periods, detects trend directions based on price relative to these lines, and signals trend starts with arrows while optionally extending lines beyond the current bar. The indicator supports dynamic visualization with separate up/down lines in customizable colors, dotted fast lines that change color on trend shifts, and optional gradient filling between lines, using a canvas object for enhanced trend-area highlighting.

Building on the previous article that introduced the market state classification module, this installment focuses on implementing the core logic for identifying and evaluating compression zones. It presents a range contraction detection and maturity grading system in MQL5 that analyzes market congestion using price action alone.

The article considers an example of creating multi-symbol multi-period standard indicators using a single indicator buffer for construction and working in the indicator subwindow. I am going to prepare the library classes for working with standard indicators working in the program main window and having more than one buffer for displaying their data.

In this article we are developing a custom market sentiment indicator to classify conditions into bullish, bearish, risk-on, risk-off, or neutral. Using multi-timeframe, the indicator can provide traders with a clearer perspective of overall market bias and short-term confirmations.

The article considers creation of an abstract indicator which further will be used as the base class to create objects of library’s standard and custom indicators.

In this article, I will start developing the methods of working with standard indicators, which will ultimately allow creating multi-symbol multi-period standard indicators based on library classes. Besides, I will add the "Skipped bars" event to the timeseries classes and eliminate excessive load from the main program code by moving the library preparation functions to CEngine class.

In the article, consider creation of multi-symbol multi-period standard indicator Accumulation/Distribution. Slightly improve library classes with respect to indicators so that, the programs developed for outdated platform MetaTrader 4 based on this library could work normally when switching over to MetaTrader 5.

In this discussion, we will develop an indicator to identify price zones created by strong market activity, such as impulsive moves, structure shifts, and liquidity events. These zones represent areas where the market has left “memory” due to unfilled orders or rapid price displacement. By marking these regions on the chart, the indicator highlights where price is statistically more likely to revisit and react in the future.