Articles with examples of indicators developed in MQL5

This article builds a Hull Moving Average Momentum indicator in MQL5 by combining raw price momentum with Hull MA smoothing. We compute momentum as the close-to-close difference over a user-defined length, form 2×Fast WMA − Slow WMA, then apply a final WMA with a square‑root period. The implementation covers inputs, buffers, warm-up/recalculation, and visualization with a color-coded line and zero-line filling, helping interpret positive/negative momentum without treating zero crossings as signals.

The article details a complete MQL5 implementation of a draggable slider for controlling ranges on the chart. It introduces the CDragHandle class, private state, public APIs for dimensions, colors, range, and value, plus Refresh* and UpdateHandlePosition logic and event processing. A working example changes CHART_SCALE, demonstrating how to connect the control to platform properties.

We integrate parameter configuration into the indicator search workflow in MQL5. A central repository describes each indicator's inputs, a dynamic dialog renders controls from those definitions, and the dialog validates entries and converts them to MqlParam. The chart launcher then creates the indicator with IndicatorCreate using the provided values. This streamlines attaching indicators with custom settings on the chosen symbol.

This article details a practical framework for converting MetaTrader 5 trendlines from static drawings into managed runtime entities. It covers object discovery, event-driven synchronization of user edits, and confirmation logic based on ATR multipliers and closed candles. A central manager coordinates multiple lines and updates their visual state. Readers can implement consistent, extensible rules for detecting proximity, validating bounces, and confirming breakouts.

This article builds a robust SuperTrend indicator in MQL5 using ATR-based bands, a ratchet mechanism, and strict series indexing to avoid silent recursion errors and repainting on closed bars. We walk through buffer binding, ATR handle management, seeding, and arrow confirmation logic. A companion EA demonstrates practical integration

Trend-scanning supports both forward and backward windows, and the labeling default is unsafe for features: it looks ahead and boosts next-bar agreement well above chance on random walks. We provide a dedicated wrapper, get trend scanning features, that forces computational causal and returns only window, slope, t value, and rsquared. A second analysis quantifies errors introduced by the default log transform on signed series.

We implement an interactive Crosshair Volume Profile indicator in MQL5 for MetaTrader 5. Using a right-click-and-drag crosshair, you select a chart region; the indicator then builds adaptive price bins, accumulates tick or real volume, detects the POC, and renders the profile on the chart. You will practice OnChartEvent()-driven interaction, cursor-to-time/price mapping, and price-source models (Close, Median, Typical, Weighted, OHLC4) for on-demand volume analysis.

This article develops a dynamic ATR-based trend channel indicator in MQL5 that responds to current market volatility. It derives True Range, applies a two-step ATR smoothing, and constructs adaptive upper and lower boundaries to track trend shifts. The tool also renders a trailing trend line, trend-colored candles, and reversal arrows, offering a usable code base for volatility-aware analysis and further indicator design.

An innovative indicator based on prime number theory helps identify strong reversal levels that other traders overlook. Testing on 10 assets showed that reversals in mathematically significant zones occur 1.5 to 1.8 times more frequently. Five practical application scenarios with specific rules for filtering out false breakouts and making precise market entries.

EGARCH models log-variance, avoiding the non-negativity constraints that can distort GARCH estimates and enabling a clear treatment of leverage asymmetry. The article provides a complete MQL5 implementation with logarithmic backcasting, simulation-based multi-step forecasting, and diagnostics including the Engle–Ng Sign Bias, Leverage Correlation, and Volatility Runs tests. Practical outputs include EGARCH Volatility, an Innovation Z-Score, and an Asymmetric Volatility Regime Oscillator to support regime analysis and strategy design.

A direct MQL5 port of the fractal detector writes each pattern at its center bar, so a buffer read by an expert advisor holds a value that only existed n bars later. We implement CFractalFeatures.mqh with ProcessBar for bar-by-bar use and Compute for full-series recalculation, covering detection, strength scored against a fixed or volatility-scaled floor, an event-based support/resistance ring, and trend-filtered breakout signals. Output is eighteen buffers published at the confirmation bar, verified against the Python reference to within 1e-13.

This article builds a white-box classifier in MQL5 using the Tsetlin Machine. It learns human-readable AND-rules instead of weights, trains with integer state updates, and requires no external dependencies. You will assemble the automaton, clause, and multi-class voter, verify on XOR and other boolean tasks, booleanize indicators, label by forward ATR-scaled return, save the model to CSV, and view active rules on a live chart.

We implement a Future Swing Projection indicator in MQL5 that analyzes historical swing structure and estimates the next move from recent price behavior. It locates six alternating swing points, measures five completed legs, and uses their average distance to project a target five bars ahead. The indicator draws swing legs, a projection line, ATR‑based support and resistance zones, and a label with the projected price to keep the process rule‑based and reproducible.

A step-by-step guide to building an anchored VWAP indicator with an interactive draggable anchor line in MQL5. The article covers the complete implementation, including calculation methodology, session resets, standard deviation bands, and custom visualization. Learn the architectural design decisions behind stateless boundary detection, multi-instance support, and cross-asset volume handling to build a versatile indicator with benchmarking, technical, and analytical capabilities.

Build a level-2 path-signature engine in pure MQL5 to read the lead-lag ordering between two data streams without choosing a lag and without a linear model. The article delivers a reusable library, an indicator that plots the Levy‑area oscillator, and a simple rule‑based Expert Advisor. Code is cross‑checked against closed‑form cases, and the components are ready to plug into your projects.

This article implements an MQL5 Liquidity Heatmap that infers likely liquidation zones from price and volume. It qualifies bars with a rolling volume SMA, computes leverage-based liquidation levels from candle extremes, ranks signals across two volume modes, and manages chart objects (lines and bubbles) that extend until price crosses them, allowing you to highlight potential stop-hunt areas and strengthen structural analysis.

This article introduces a modular Fair Value Gap (FVG) detection engine for MQL5 packaged as a reusable include class, it evaluates imbalance zones on closed bars, applies a Simple True Range average filter to eliminate low-volatility noise, and supports wick-touch and close-through mitigation. A companion diagnostic indicator plots active gaps, and an Expert Advisor template demonstrates automated pullback entries with new-bar execution controls.

The article introduces the Mapper pipeline in MQL5 by implementing the two fundamental components: CTDAMapperFilter (lens) and CTDAMapperCover (overlapping intervals). It explains three lens options—eccentricity, density, and coordinate—plus cover parameters (resolution and gain), and demonstrates how a price point cloud is reduced to one value per point and interval memberships. Readers obtain ready inputs for subsequent clustering and graph construction.

A structured MQL5 implementation of a multi‑symbol trading panel with clear separation of concerns: symbol handling, trading logic, and GUI. Integrated into an Expert Advisor, it validates symbols, exposes centralized controls for opening and positions managing across symbols, and applies SL/TP changes. Real‑time account and portfolio metrics help streamline routine operations from a single chart.

Part 8 adds bar-by-bar micro-trend scoring for NQ M1. GetMicroTrendStrength() builds a continuous [-1, +1] composite from EMA alignment, ATR‑normalized price position, slope consistency, and volume, with a contradiction penalty to suppress alignment/price conflicts. Session-adaptive thresholds scale by Part 7 confidence to modulate signal frequency across regimes. Outputs include a seven-state label, a binary signal, and a persistence check, calibrated on 514 New York sessions (May 2024–May 2026).

We implement an interactive, anchored multi-timeframe volume profile in MQL5 for MetaTrader 5. The indicator draws the current-timeframe profile on the main chart and a higher timeframe profile in a subwindow, both aligned by a draggable anchor and the visible range. You will learn keyboard-driven bin editing (E/S double-click), robust timeframe validation, viewport-aware updates, and object restoration to build a reliable, synchronized volume workflow.

This article turns the verified TDA pipeline into a live MQL5 indicator. It reduces each price window to two persistence-entropy lines (H0 and H1), computes a normalized loop-strength metric with an adaptive percentile band, and places fade marks only when loop strength is high and price hits a window extreme. You can attach the indicator, read six buffers from an Expert Advisor, and tune key window, ranking, and performance parameters.

The ProSpread seasonality index indicator with a Moving Average is a technical analysis tool that identifies seasonal patterns in price movements, analyzes price behavior during specific trading hours and is able to work with either a single instrument or a spread between two assets. It also visualizes the statistical probability of directional movements.

This article develops a rule-based daily pivot point indicator in MQL5 that uses the previous trading day's high, low, and close values to generate pivot, support, and resistance levels. It details historical data retrieval, pivot computation, chart object management, configurable label rendering, and automatic level updates as new trading days begin. The completed indicator displays multiple historical pivot sessions on the main chart for technical analysis on daily and lower timeframes.

The article upgrades SuperTrend by integrating a divergence engine (MPO4 or RSI) the dynamically reduces the ATR multiplier during weakening momentum. It covers the shrinking formula, non-repainting state propagation with dedicated buffers, and a step-by-step MQL5 implementation on the price chart. You will learn how to interpret arrows and line flips, adjust inputs, and apply the indicator for disciplined trailing and earlier confirmations.

This article demonstrates how to build the UT Bot Alerts indicator in MQL5 using a clear, step-by-step approach. The tutorial explains how to implement an ATR-based trailing stop system, compute a custom EMA for signal detection, and generate buy and sell signals without repainting. The final indicator provides well-structured buffers that enable easy integration with Expert Advisors, automated trading systems, and other algorithmic tools within the MetaTrader 5 platform.

We complete persistent homology for MQL5 by reducing the Vietoris–Rips boundary matrix to a persistence diagram. The article implements Z/2 column reduction (CTDAReduction), a diagram container with analytics (CTDADiagram), and a facade that runs the six-stage pipeline in one call (CTDA). Outputs are cross-checked against Ripser to numerical agreement, enabling reliable diagram-based metrics.

We build a Support and Resistance Volume Profile indicator that adapts to the current viewport in MetaTrader 5. You will learn viewport detection, dynamic SnR identification, zoom‑driven bin sizing, min‑max volume scaling, and fast on‑chart rendering controlled by OnChartEvent. This approach expresses the relative strength of SnR levels with volume, keeping the chart focused on actionable reaction zones.

The article presents a structured approach to external and internal market structure in MQL5, from swing identification to CHoCH/BoS validation within an established trend. It explains refining true highs/lows, enforcing “first internal signal” logic, and rendering lines, labels, and markers on the chart. The outcome is a consistent indicator that converts price structure into defined entries, stop losses, and 1.5R targets.

This article finalizes the Forward Simulation Engine for MetaTrader 5 by calibrating synthetic candles to recent market volatility instead of using slope-only sizing. It samples average body, upper wick, and lower wick from closed bars, applies a sine-envelope with decay, proportional wicks, gaps between candles, and periodic counter-trend injections. The result is a live projection that advances one bar ahead, with code you can reuse for calibrated, anchor-based forward rendering and automatic cleanup.