All About Price Action - page 7

[Sergey Golubev]

Price Action Analysis Toolkit Development (Part 60): Objective Swing-Based Trendlines for Structural Analysis

In Part 19 of this series, I introduced an analysis tool that relied on the ZigZag indicator to identify swing points, using them as a basis for drawing trendlines to interpret evolving price structure. That work laid an important foundation: demonstrating that trendlines are not merely visual aids, but vital structural references that help frame how price may behave ahead of time. Building on that concept, this article approaches the same core idea from a more deliberate and refined perspective. Instead of depending on an indicator to define swings, the current tool derives swing points directly from raw price action. By working solely with observed price behavior, the analysis becomes more transparent and controllable, reducing the instability often associated with indicator-based pivots.

[Sergey Golubev]

Price Action Analysis Toolkit Development (Part 61): Structural Slanted Trendline Breakouts with 3-Swing Validation

The previous article established a structured approach to drawing slanted trendlines as a practical way of interpreting market direction and understanding how price behaves within evolving structure. Anchoring trendlines to validated swing points grounds the analysis directly in market structure, improving consistency while removing discretionary line placement.

This tool is developed using the MQL5 programming language. The sections that follow outline the strategy logic first, then demonstrate how that structure is translated into an MQL5 implementation. Testing and observed outcomes are then examined, before concluding with final observations.

[Sergey Golubev]

Price Action Analysis Toolkit Development (Part 62): Building an Adaptive Parallel Channel Detection and Breakout System in MQL5

In the previous part of this series, we explored a trendline breakout framework validated through three swing points. Testing showed that the approach effectively flagged clear breakout opportunities. However, one limitation became apparent: the system only captured breakouts in the direction of the trendlines being constructed. This meant that if price movement occurred in the opposite direction or on the unmonitored side, those breakout structures would go unnoticed.

This article extends that approach by introducing an adaptive parallel channel detection and breakout system. The system constructs channels based on swing points, monitors price action within these channels, and confirms breakouts dynamically. By tracking both sides of the channel, the framework ensures no significant movement is missed.

[Sergey Golubev]

Price Action Analysis Toolkit Development (Part 63): Automating Rising and Falling Wedge Detection in MQL5

When a chart is opened, the first instinct is to scan for structure. Familiar patterns help frame expectations, manage risk, and prepare for high-probability entries. Among the most traded price structures are rising and falling wedges—compression formations that often precede expansion.

The challenge, however, is not in knowing that wedges exist. The challenge lies in identifying them consistently and objectively. Many traders, especially those still developing chart-reading skills, struggle to recognize proper wedge structure. Even experienced analysts can spend considerable time drawing, adjusting, and validating trendlines—and sometimes miss a valid formation altogether. Subjective pattern recognition introduces delay, inconsistency, and bias.

To address this, we introduce an MQL5 indicator engineered to automatically detect and construct rising and falling wedge formations directly on the chart. The system identifies pivot points, validates slope convergence, prevents structural overlap, and monitors breakout or failure conditions—turning geometric theory into structured algorithmic logic.

[Sergey Golubev]

Price Action Analysis Toolkit Development (Part 64): Synchronizing Manually Drawn Trendlines with Automated Monitoring

You already draw trendlines manually and trust your visual judgment more than fully automated detection. The practical problem is different: as you place more lines across one or several charts, you physically cannot watch every level all the time. Key moments—price approaching, touching, breaking, or rejecting a manually drawn trendline—often occur while you switch timeframes, step away from the terminal, or manage other positions. The article addresses this precise deficit: how to keep manual charting as your analytical input while automating the repetitive task of monitoring those lines.