CLatencyMonitor is a lightweight MQL5 include-file that adds latency awareness to execution-sensitive EAs via a single reusable class. It measures inter-tick deltas with GetTickCount64(), applies an ATR-based volatility gate to reduce false positives during high-volatility bursts, and publishes confirmed lag events through a named GlobalVariable for cross-EA IPC on the same terminal.

On each OnTick() call, the elapsed milliseconds since the previous tick are computed, with the first tick seeding state only. A lag candidate is suppressed when ATR exceeds AtrSmaMultiplier × SMA(ATR, AtrPeriod), with the SMA calculated manually from the ATR buffer for self-normalisation across symbols and timeframes. If ATR setup fails or history is insufficient, the gate fails open so detection remains active.

A timer-driven persistence check confirms lag only after Persistenc...

👉 Read | Quotes | @mql5dev

#MQL5 #MT5 #EA

ExMachina Safe Scalping is a breakout scalping EA designed to stay flat unless six independent conditions align on the same bar. Filters include dual EMA trend (150/510), ATR-based trend strength to reject weak ranges, price location relative to both EMAs, an N-bar high/low breakout with a volatility-adjusted buffer, RSI kept out of extremes, and close-to-close momentum confirmation.

Risk controls are fixed per trade: predefined stop loss and take profit at entry, single open position, and no martingale, grid, hedging, or averaging down. Breakeven can move the stop to entry after favorable movement, and a drawdown threshold can auto-pause trading.

Operational filters include session-hour limits, maximum spread gating, and optional news-time blocking. The Code Base release is a single .mq5 file using the standard MT5 Trade library, with readable logic and an ...

👉 Read | Forum | @mql5dev

#MQL5 #MT5 #Scalper

The DoEasy chart subsystem is finished by making chart windows first-class library objects, enabling reliable auto-refresh of chart and subwindow properties. Instead of manually syncing state, every tracked integer/real/string property updates its stored parameters and emits structured custom events when values change, cross a threshold, or match a configured combination.

Core refactor work includes new message indices, a dedicated chart-window list ID for event attribution, and aligned enumerations for properties and sort criteria so search/sort stays consistent. The chart window class now owns its property arrays, descriptions, compare logic, and refresh flow, including indicator add/remove handling.

Chart objects gain symbol/timeframe change events, explicit helpers to set tracked values, and cleaner property population methods. Practical result: EA...

👉 Read | Signals | @mql5dev

#MQL5 #MT5 #AlgoTrading

Last Structure Indicator (Single Phase) implements a framework to test the Last Structure Break (LSB) concept using structured price-action rules.

Session boundaries are detected via logical day separation, based on chart separators and datetime normalization rather than daily timeframe data. This keeps day transitions consistent across timeframes and broker feeds.

The scan builds support/resistance pivots with configurable modes (wick-based or body-based) and pivot strength validation using left/right bar requirements. Only the final structural levels of a session that remain unbroken into the close are accepted, then projected forward as trendlines into the next session.

Designed for real-time use with minimal recalculation, the tool aims to measure whether end-of-session structure has repeatable relevance for subsequent price action.

👉 Read | Forum | @mql5dev

#MQL5 #MT5 #Indicator

This article breaks down how to consistently identify Premium/Discount (PD) arrays and imbalances in price action, and why traders fail when they pick the wrong “reaction zones” or trade against the broader narrative. It emphasizes using a simple checklist mindset to reduce impulse entries and indecision.

Core concepts are defined practically: imbalances as fast, one-sided moves that often get revisited; market structure shifts as decisive breaks that flip highs/lows; PD arrays as splitting an expansion leg into premium vs discount to avoid buying high or selling low; and using fractal behavior to refine higher-timeframe ideas into lower-timeframe entries.

A MetaTrader 5 EA in MQL5 is presented to automate this workflow: detect trend and consolidation with stacked moving averages, map higher-timeframe expansion legs into PD zones, track imbalances inside th...

👉 Read | VPS | @mql5dev

#MQL5 #MT5 #EA

An updated Limit Channels indicator adds a “states” panel rendered as a colored histogram to summarize channel conditions.

States are derived from three nested level groups. Level 3 uses the outer bands and represents the slowest state. Level 2 uses the middle bands. Level 1 uses the inner bands and reacts fastest.

The six total levels allow additional combinations beyond the default three-state mapping. Color transitions in the histogram can be used as event markers, with signal rules left to the implementer based on timeframe, instrument, and risk constraints.

👉 Read | Freelance | @mql5dev

#MQL5 #MT5 #Indicator

ALGLIB’s MQL5 port ships minLBFGS but lacks a box-constrained variant, pushing developers toward heavier optimizers for simple bound-limited calibration tasks. A compact Truncated Newton Conjugate-Gradient (TNC) solver fills that gap with an API designed to drop into projects like minLBFGS.

TNC approximates Newton steps using an inner Conjugate Gradient loop, relying on Hessian-vector products derived from gradient finite differences instead of forming a full Hessian. It supports analytic gradients when available, plus stable numerical differentiation near bounds, while enforcing constraints via projection and variable clamping.

The implementation is packaged as tnc.mqh with a CFunctor/CTruncNewtonCG interface, tunable stopping criteria, and clear termination codes. It’s validated on Rosenbrock and used to fit logistic regression alongside LBFGS, pro...

👉 Read | AlgoBook | @mql5dev

#MQL5 #MT5 #algorithm

A trend indicator is used to classify market direction as uptrend or downtrend based on the line state.

Common operational logic is straightforward: a green line is treated as a bullish condition and a red line as a bearish condition. Some traders use this as a basic ruleset to align entries and exits with the prevailing direction.

For practical use, results depend on the instrument, timeframe, and parameter settings. As with any single-signal approach, confirmation with volatility, volume, or higher-timeframe structure is typically required to reduce false signals.

👉 Read | Freelance | @mql5dev

#MQL5 #MT5 #Indicator

This MQL5 binomial distribution viewer evolves from a 2D canvas into a Direct3D-backed tool that can switch between 2D and 3D at runtime. The goal is practical: make frequency differences and PMF shape easier to inspect using depth, perspective, and camera control instead of restarting or redrawing separate views.

The implementation adds CCanvas3D plus DXBox primitives, a view-mode enum, and configurable inputs for camera, ground plane, and axis styling. The codebase is refactored into a single visualizer class that centralizes state, data arrays, and interaction logic, with a destructor that explicitly releases GPU resources.

On the 3D side, histogram bins become box meshes updated via scaling/translation matrices, with an auto-fit camera derived from scene bounds. Mouse interactions handle rotation and zoom, while 2D overlays (header, legend, swit...

👉 Read | AppStore | @mql5dev

#MQL5 #MT5 #AlgoTrading

An updated version of the MetaTrader 4 platform will be released on Friday, March 13, 2026. This build includes improved interface translations, bug fixes, and enhanced platform stability.

The update will be distributed via Live Update.

Discuss the update...

An MT4 version of the Limit Channels indicator has been published.

The release targets traders and developers maintaining MT4 stacks that require channel-based boundary calculations with configurable limits. Typical usage includes defining dynamic upper and lower bands and tracking price interaction with those levels for alerts or signal logic.

Implementation details, parameters, and example configurations are available at the referenced source.

👉 Read | Quotes | @mql5dev

#MQL4 #MT4 #Indicator

Symbol discipline fails when a solid strategy is applied to the wrong instrument. This MQL5 solution enforces a strict symbol whitelist at the execution layer, blocking both manual and EA trades on non-approved symbols using OnTradeTransaction.

The design is modular: a shared include file centralizes whitelist parsing, case-insensitive validation, and file I/O; an indicator dashboard writes the approved universe and displays status plus recent blocks; an enforcement EA reacts to ORDER_ADD and DEAL_ADD events to cancel pending orders or flatten positions.

Configuration is persisted in a plain text file, blocked actions are audited to CSV, and components synchronize via shared storage. Result: strategy scope stays aligned with backtests, exposure can’t silently expand, and every violation is traceable.

👉 Read | CodeBase | @mql5dev

#MQL5 #MT5 #AlgoTrading

A minimal channel tool can be built from recent high/low values with band spacing derived from ATR. The result is a dynamic range framework that adapts to volatility and updates with each bar.

In practice, these bands are more suitable for estimating short-term support and resistance than for generating entries. They can also serve as consistent reference levels for take-profit and stop-loss placement in systems that already define direction and timing.

This setup is intended for trend context, range boundaries, and risk parameterization, not as a standalone signal source.

👉 Read | NeuroBook | @mql5dev

#MQL5 #MT5 #Indicator

This article turns discretionary price action into a testable model by representing confirmed swing highs/lows as nodes and swing transitions as edges in a market-structure graph. Depth-First Search is then used to “commit” to one structural branch (higher highs/lows or lower lows/highs), only accepting a directional bias after a minimum path depth confirms continuation.

The EA implements this in MQL5 with configurable swing sensitivity, minimum depth, target tolerance, and either fixed-lot or risk-based sizing. Key invalidation levels (last higher low / last lower high) make trend failure deterministic: if broken, the system backtracks, clears state, and searches for an alternate path.

Operationally, the design emphasizes longevity: daily resets, capped node storage, array resizing, and cleanup on deinit keep the swing graph and DFS state stable d...

👉 Read | AlgoBook | @mql5dev

#MQL5 #MT5 #AlgoTrading

Quant research keeps producing backtests with high Sharpe, low drawdown, and immediate live failure. The main driver is overfitting through multiple channels, not a single mistake fixed by a basic train/test split.

Common failure modes include data snooping across many candidates, curve-fitting to path-specific noise, and accumulated researcher degrees of freedom during iterative tuning.

Three controls target different layers. Validation-within-Validation enforces outer training, inner validation, and a one-time final test, often with anchored walkforward. CPCV removes temporal leakage via purging and embargoing, then evaluates combinatorial OOS paths. CSCV audits selection with Probability of Backtest Overfitting, reporting how often the in-sample winner ranks poorly out-of-sample.

👉 Read | CodeBase | @mql5dev

#MQL5 #MT5 #AlgoTrading

The article shifts a retail stat-arb workflow from SQLite (OLTP) to DuckDB-backed analytics using Parquet files, keeping mean-reversion and sub-second HFT out of scope. The goal is faster research loops: qualify ideas in seconds before spending time on full MT5 EA backtests.

It shows how to export an entire SQLite database or selected tables to Parquet via DuckDB, then query those files directly with SQL or Python’s lazy relational API.

Key technical gains come from Parquet’s columnar layout, embedded min/max statistics, compression, and DuckDB’s zero-copy reads, which reduce I/O and skip irrelevant files.

For scalable history storage, the plan is to denormalize price data and adopt Hive-style partitioning (source, asset class, ticker, timeframe, year, month) to keep datasets portable and easy to merge across brokers and providers.

👉 Read | NeuroBook | @mql5dev

#MQL5 #MT5 #AlgoTrading

ExMachina Trade Pilot is an MT5 expert advisor focused on order execution and position lifecycle management from a single control panel. It targets common platform gaps: partial take-profits, automated breakeven, and trailing logic beyond fixed-point trails.

The workflow consolidates risk-based lot sizing, SL/TP placement, and multi-stage exits. Up to three take-profit levels can be configured with independent close percentages; each hit triggers an automatic partial close with logging and live status tracking.

Management tools include ATR-based, fixed-point, and previous-candle trailing with a minimum step, plus breakeven on a profit threshold with optional offset. One-click market and pending orders apply predefined offsets and SL/TP rules. Additional controls cover close-all, direction-based closes, pending cleanup, and a dashboard for spread, exposure, ...

👉 Read | Calendar | @mql5dev

#MQL5 #MT5 #EA

ExMachina Prop Dashboard is an MT5 chart indicator focused on real-time compliance tracking for funded-account rules. It updates on every tick and keeps key risk limits visible without relying on delayed web dashboards or window switching.

The tool provides prop-firm presets plus a full custom ruleset, covering daily loss limits, max drawdown variants (static, trailing high-water mark, end-of-day), profit targets, minimum trading days, and calendar deadlines. It reports current P&L in dollars and percent, remaining buffer before breach, and supports configurable day reset time to match broker rollover.

Status logic summarizes progress as ON TRACK, AT RISK, TARGET HIT (days pending), PASSED, or FAILED (limit breach or time expiry). Alerts can trigger at a configurable threshold (default 80%) and on breach via popup, sound, push, or email. It monitors all ...

👉 Read | Calendar | @mql5dev

#MQL5 #MT5 #Indicator

Parameter persistence in MQL after terminal restart comes down to four storage options: terminal global variables, chart objects, order comments, and text files. Each has hard limits on type, scope, and lifetime.

Terminal globals are cross-chart but only store double, so packing integers into 64 bits is sometimes required. Chart objects can hold state via hidden properties and survive via templates. Order comments are capped at 23 chars but can encode compact metadata for post-trade analytics and runtime routing.

Text files remain the most flexible: Key=Value params per analyzer, per chart ID, restored on EA restart and only re-run on the next bar. External integration is typically file-based: JSON outbound, Key=Value inbound, plus optional WebRequest notifications to mobile.

👉 Read | VPS | @mql5dev

#MQL5 #MT5 #AlgoTrading

An MT5 mean-reversion EA design based on dynamic price zones and momentum filtering.

Supply/demand boundaries are derived from the highest high and lowest low over the last 48 candles, with entries triggered when price reaches a configurable buffer around these levels. Trend context is taken from a moving average, while RSI is used to reduce false breaks: BUY when price hits the lower zone with RSI below 40; SELL when price hits the upper zone with RSI above 55.

Risk controls include balance-based position sizing using a fixed risk percentage, plus mandatory stop loss and take profit on every order. Break-even and trailing stop logic automate profit protection. Positions can also be closed early when RSI reaches extreme opposite readings.

Operational features include an on-chart dashboard (RSI, spread, risk, magic number), detailed expert logs, zero compil...

👉 Read | Signals | @mql5dev

#MQL5 #MT5 #EA

This article extends a MetaTrader 5 chart-management library with explicit event support for chart objects, subwindows, and indicators. A new enumeration defines chart event types, and registered changes trigger custom events sent to the controlling chart, enabling deterministic event routing in the EA.

A key implementation detail is reliable identification of removed windows/indicators. Indicator objects now store their chart subwindow index, and deleted charts, windows, and indicators are preserved in dedicated lists so handlers can query historical context after removal.

The chart window and chart classes are updated to share these lists via pointers owned by the chart collection, avoiding duplication while enforcing read-only access outside the collection. Indicator handle lifecycle is corrected: handles are retained during use and released in de...

👉 Read | Docs | @mql5dev

#MQL5 #MT5 #Indicator