Christian Benjamin / プロファイル

We introduce an MQL5 discipline engine that enforces risk consistently at the account level. It continuously scans positions from any source, validates SL/TP, equity-based exposure, and target R:R, and automatically corrects deviations by setting levels or adjusting volume. The result is uniform risk structure across manual and EA trades, supported by on-chart feedback and mode-based control.

We present a chart-embedded RSI panel that removes the need for a separate window by attaching momentum directly to live price. The article explains the design and MQL5 code: real-time RSI retrieval, slope-based signal classification, and adaptive positioning. Traders get RSI value, state, and signal strength where decisions are made, improving clarity across timeframes.

This article implements a complete MQL5 Expert Advisor that monitors manually drawn support and resistance levels in real time. It synchronizes horizontal lines, detects approaches, touches, breakouts, reversals, and retests, and adds optional candlestick pattern checks. Alerts and on‑chart markers provide clear, repeatable feedback, allowing you to keep manual analysis while automating the surveillance of key price levels.

An MQL5 control system that blocks orders outside scheduled trading hours and during scheduled news releases, converting time rules into executable restrictions. It combines a permissions management mechanism, a transaction-level expert advisor, and a visual dashboard for real-time status and upcoming restrictions. Configuration is accomplished using editable files, with caching and a CSV audit log for traceability.

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.

The Fibonacci retracement tool is an essential component of price action analysis, providing critical levels for potential market reactions. However, its effectiveness is often limited by the need for continuous human monitoring, which can lead to missed setups. In this part of our series, we introduce a tool that synchronizes and actively monitors manually drawn Fibonacci levels using MQL5, combining discretionary insight with automated oversight.

Monitoring manually drawn trendlines requires constant chart observation, which can cause important price interactions to be missed. This article develops a trendline monitoring Expert Advisor that synchronizes manually drawn trendlines with automated monitoring logic in MQL5, generating alerts when price approaches, touches, or breaks a monitored line.

This article details an MQL5 framework that restricts trading to an approved set of symbols. The solution combines a shared library, a configuration dashboard, and an enforcement Expert Advisor that validates each trade against a whitelist and logs blocked attempts. It includes fully functional code examples, a clear explanation of the structural design decisions, and validation tests that confirm reliable symbol filtering, controlled market exposure, and transparent monitoring of rule enforcement.

We have developed a system that enforces a daily trade limit to keep you aligned with your trading rules. It monitors all executed trades across the account and automatically intervenes once the defined limit is reached, preventing any further activity. By embedding control directly into the platform, the system ensures discipline is maintained even when market pressure rises.

In this part of the Price Action Analysis Toolkit Development series, we develop an MQL5 indicator that automatically detects rising and falling wedge patterns in real time. The system confirms pivot structures, validates boundary convergence mathematically, prevents overlapping formations, and monitors breakout and failure conditions with precise visual feedback. Built using a clean object-oriented architecture, this implementation converts subjective wedge recognition into a structured, state-aware analytical component designed to strengthen disciplined price action analysis.

This article presents an adaptive parallel channel detection and breakout system in MQL5. It explains how swing points are identified, channels are constructed and dynamically recalculated, and breakouts are confirmed and visualized with persistent signals. The framework integrates trendline geometry, ATR-based filtering, and retest validation to provide reliable, real-time price action analysis for professional charting and trading decisions.

Discipline becomes reliable when it is produced by system design, not willpower. Using MQL5, the article implements real-time constraints—trade-frequency caps and daily equity-based stops—that monitor behavior and trigger actions on breach. Readers gain a practical template for governance layers that stabilize execution under market pressure.

We present a slanted trendline breakout tool that relies on three‑swing validation to generate objective, price‑action signals. The system automates swing detection, trendline construction, and breakout confirmation using crossing logic to reduce noise and standardize execution. The article explains the strategy rules, shows the MQL5 implementation, and reviews testing results; the tool is intended for analysis and signal confirmation, not automated trading.

We present a rule-based approach to trendlines that avoids indicator pivots and uses ordered swings derived from raw prices. The article walks through swing detection, size qualification via ATR or fixed thresholds, and validation of ascending and descending structures, then implements these rules in MQL5 with non-repainting drawing and selective output. You get a clear, repeatable way to track structural support and resistance that holds up across market conditions.

While studying a wide range of breakout setups, I noticed that failed breakouts were rarely caused by a lack of volatility, but more often by weak internal structure. That observation led to the framework presented in this article. The approach identifies patterns where the final price leg shows superior length, steepness, and speed—clear signs of momentum accumulation ahead of directional expansion. By detecting these subtle geometric imbalances within consolidation, traders can anticipate higher-probability breakouts before price exits the range. Continue reading to see how this fractal-based, geometric framework translates structural imbalance into precise breakout signals.

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.

This article develops a market state classification module for MQL5 that interprets price behavior using completed price data. By examining volatility contraction, expansion, and structural consistency, the tool classifies market conditions as compression, transition, expansion, or trend, providing a clear contextual framework for price action analysis.

時間で区切られた市場セッションとCandle Pressure Index (CPI)を組み合わせ、確定足データと明確に定義されたルールに基づき、セッション境界での受容と拒否の挙動を分類するセッションに基づいた分析手法を提示します。

価格チャート上にバー内の買い圧力と売り圧力を可視化するCLVベースのオーバーレイであるCandle Pressure Index（CPI、ローソク足圧力指数）の設計とMetaTrader 5への実装について解説します。本記事では、ローソク足の構造、圧力分類および可視化の仕組み、そして時間足や銘柄に依存せず一貫した動作を維持する、リペイントなしの遷移ベースアラートシステムに焦点を当てます。

取引の明確さとタイミングを向上させるために、平均足による平滑化とEMA20の高値および安値のバンド、さらにEMA50のトレンドフィルターを組み合わせた手法を解説します。これらのツールにより、トレーダーは真のモメンタムを見極め、ノイズを排除し、ボラティリティの高い局面やトレンド相場により適切に対応できます。