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From Basic to Intermediate: Struct (IV)
From Basic to Intermediate: Struct (IV)
In this article, we will explore how to create so-called structural code, where the entire context and methods for manipulating variables and information are placed within a structure to create a suitable context for implementing any code. Therefore, we will examine the necessity of using a private section of the code to separate what is public from what is not, thereby adhering to the rule of encapsulation and preserving the context for which the data structure was created.
Market Simulation (Part 14): Sockets (VIII)
Market Simulation (Part 14): Sockets (VIII)
Many programmers might assume we should abandon using Excel and move directly to Python, using some packages that allow Python to generate an Excel file for later analysis of results. However, as mentioned in the previous article, although this solution is the simplest for many programmers, it will not be accepted by some users. And in this particular case, the user is always right. As programmers, we must find a way to make everything work.
Developing A Custom Account Performance Matrix Indicator
Developing A Custom Account Performance Matrix Indicator
This indicator acts as a discipline enforcer by tracking account equity, profit/loss, and drawdown in real-time while displaying a performance dashboard. It can help traders stay consistent, avoid overtrading, and comply with prop-firm challenge rules.
From Novice to Expert: Automating Intraday Strategies
From Novice to Expert: Automating Intraday Strategies
We translate the EMA‑50 retest idea into a behavior‑driven Expert Advisor for intraday trading. The study formalizes trend bias, EMA interaction (pierce and close), reaction confirmation, and optional filters, then implements them in MQL5 with modular functions and resource‑safe handles. Visual testing in the Strategy Tester verifies signal correctness. The result is a clear template for coding discretionary bounces.
From Novice to Expert: Extending a Liquidity Strategy with Trend Filters
From Novice to Expert: Extending a Liquidity Strategy with Trend Filters
The article extends a liquidity-based strategy with a simple trend constraint: trade liquidity zones only in the direction of the EMA(50). It explains filtering rules, presents a reusable TrendFilter.mqh class and EA integration in MQL5, and compares baseline versus filtered tests. Readers gain a clear directional bias, reduced overtrading in countertrend phases, and ready-to-use source files.
Automating Swing Extremes and the Pullback Indicator: Anticipating Reversals with LTF Market Structure
Automating Swing Extremes and the Pullback Indicator: Anticipating Reversals with LTF Market Structure
In this discussion we will Automate Swing Extremes and the Pullback Indicator, which transforms raw lower-timeframe (LTF) price action into a structured map of market intent, precisely identifying swing highs, swing lows, and corrective phases in real time. By programmatically tracking microstructure shifts, it anticipates potential reversals before they fully unfold—turning noise into actionable insight.
Implementation of a Breakeven Mechanism in MQL5 (Part 1): Base Class and Fixed-Points Breakeven Mode
Implementation of a Breakeven Mechanism in MQL5 (Part 1): Base Class and Fixed-Points Breakeven Mode
This article discusses the application of a breakeven mechanism in automated strategies using the MQL5 language. We will start with a simple explanation of what the breakeven mode is, how it is implemented, and its possible variations. Next, this functionality will be integrated into the Order Blocks expert advisor, which we created in our last article on risk management. To evaluate its effectiveness, we will run two backtests under specific conditions: one using the breakeven mechanism and the other without it.