Broker Execution Diagnostics is a read-only script for broker specification analysis and execution troubleshooting prior to Expert Advisor configuration or rejected order review. No trades are opened, modified, or closed. The utility reads the active symbol parameters and prints a structured report on the chart and in the Experts log.

Report fields include bid/ask/spread (points), digits and point size, tick size and tick values, contract size and account currencies, volume limits (min/max/step and directional caps), stop and freeze levels, trade and execution modes, supported filling modes and order features, plus terminal/account/EA trading permissions.

Margin and profit estimates are calculated for configurable test volume and price movement using OrderCalcMargin and OrderCalcProfit. Test volume is normalized to the broker’s min/max/step constraints. Us...

👉 Read | Calendar | @mql5dev

Risk Based Position Size Calculator is a chart indicator used to plan trade volume before execution. It adds draggable Entry and Stop lines, measures the distance, and outputs a broker-normalized position size for a selected risk level. It does not place orders or manage open positions.

Risk can be set as a percentage of balance, percentage of equity, or a fixed amount in account currency. The calculation uses tick size and tick value, with an optional round-turn commission per lot. Volume is rounded down to the broker’s volume step to avoid exceeding the configured risk.

The panel shows direction, entry/stop/target, stop distance, risk amount, risk per lot, raw vs normalized volume, reward-to-risk ratio, and validation status. Position sizing remains an estimate due to slippage, gaps, swaps, and execution differences.

👉 Read | NeuroBook | @mql5dev

A price envelope indicator built on the Nadaraya-Watson estimator with Gaussian smoothing produces adaptive upper and lower bands that follow current volatility and direction.

Signals are generated when price closes beyond either band, with colored arrows marking upper or lower crossings. The logic is non-repainting, keeping historical arrows and band values fixed after calculation to support consistent review and testing.

Configuration includes bandwidth control, envelope multiplier, and selectable applied price. Visual settings cover band and arrow colors, with a lightweight chart footprint. Compatible across symbols and timeframes and operates without external dependencies.

Use as an analytical component only; market risk remains and results are not guaranteed.

👉 Read | AlgoBook | @mql5dev

Broker Info Panel MT5 adds a compact on-chart panel for viewing broker and symbol trading specifications without switching between platform dialogs.

Displayed data includes live Bid/Ask, spread in points and price, tick size and tick value, min/max lot, volume step, stop level, and freeze level. This is relevant when validating a new broker, symbol, or account type where contract settings often differ.

The tool is read-only: it does not place, modify, or close orders. Visible fields can be enabled or disabled via inputs, and the refresh interval is configurable. No external DLLs or third-party libraries are required.

Installation: copy BrokerInfoPanel.mq5 to MQL5\Indicators, compile in MetaEditor, then attach to any chart. Values are sourced from broker-provided trading specifications and will vary by account and symbol.

👉 Read | Docs | @mql5dev

Market Session Separator is a chart-only indicator for intraday work that makes session changes explicit without manual time conversion. It renders up to three configurable windows per day using vertical separators, shaded background bands, or both, with optional labels.

Sessions are defined by start/end hours in server time, including overnight ranges where end precedes start. Colors and labels are independent per session, allowing standard Asian/London/New York presets or custom windows such as overlap periods.

Rendering is kept lightweight: no highs/lows or derived values are computed. Session boxes are rebuilt from the chart’s visible price range so they always span the full view while zooming and scrolling.

Operational controls include a rolling days window with automatic pruning, weekend skipping, selectable line style, and clean deinitializat...

👉 Read | Calendar | @mql5dev

Grid and martingale often look profitable in backtests because results are dominated by completed cycles. Profit factor and expected payoff can be positive per cycle while the equity curve trends up.

The failure mode is the same: an unfinished cycle appears when margin, max orders, or trend length breaks assumptions. One large adverse move offsets prior gains and closes the sequence at a net loss.

Simple MT5 EAs with fixed steps (grid) and recursive sizing (martingale) typically reproduce this behavior. Spread and execution costs then push the long-run outcome further negative, even when many cycles finish in profit.

The core math frames both as zero-expectancy without edge on direction, with blow-up risk concentrated in rare tails.

👉 Read | Freelance | @mql5dev

IronHawk Fibonacci Structure Map applies Fibonacci levels only to confirmed swing highs and lows, then validates those levels with higher-timeframe alignment. It calculates key retracement and extension levels and compares them across up to three timeframes.

When multiple Fibonacci references cluster within a volatility-adjusted distance, the tool groups them into a confluence zone using ATR-based rules. Levels include 23.6, 38.2, 50, 61.8, 78.6, 127.2, and 161.8. Zones are context markers, not trade signals, and are intended to focus attention on price reaction.

Additional outputs include basic market-structure context, Premium/Discount around the active swing, and the nearest level with distance from current price. Configuration covers timeframe selection, lookback, swing depth, per-level toggles, ATR period, cluster sizing, minimum overlaps, view ...

👉 Read | CodeBase | @mql5dev

Work described: pattern search in FX data, automated generation of Expert Advisors, and measurement of how long detected patterns remain statistically usable.

Method focus is brute-force coefficient search versus neural-network map search. Both reduce to selecting parameter bytes, but brute force keeps a fixed algorithm and varies a simple coefficient array, while NN varies a larger strategy representation with higher compute and stronger dependence on implementation quality.

Core model uses a bounded multidimensional Taylor polynomial over recent candles, with inputs based on (Close[i]-Open[i]). Positive output maps to buy, negative to sell, with optional sign inversion and a tunable signal threshold.

Optimization is staged: first, coefficient arrays are ranked on next-bar direction metrics (expected payoff or profit factor). Second, full-period ...

👉 Read | AppStore | @mql5dev

A compact Renko context indicator displays the active Renko direction, count of consecutive confirmed bricks, fixed brick size, last confirmed Renko close, and the exact price level where a reversal becomes confirmed. It also reports the remaining distance to that reversal level measured in bricks, with an optional dashed horizontal line on the chart.

The internal model is built from recent tick history. Continuation confirms after price moves one full brick beyond the last Renko close. Reversal is confirmed only after a two-brick move against the current direction: for an UP run, reversal = last close − 2×brick size; for a DOWN run, reversal = last close + 2×brick size.

The goal is to prevent treating minor counter-moves as reversals. No buy/sell signals are generated, and no prediction logic is included. Configuration covers brick size in points, tick...

👉 Read | AppStore | @mql5dev

GDS Renko Bricks renders a fixed-size Renko view directly inside a standard MT5 chart window, without relying on offline charts or custom symbols. Brick formation is driven by tick data, producing completed bricks in real time.

The display keeps uniform brick width and hides the usual time scale, since construction is based on price movement. Reversals follow a two-brick logic consistent with classic Renko rules.

Configuration is minimal: a single Brick Size input. The selected chart timeframe acts only as a host and does not affect Renko generation. Example: on XAUUSD, Brick Size 1.00 produces $1 bricks. No DLLs or external libraries are required.

👉 Read | CodeBase | @mql5dev

System logic uses two internal Renko streams built from BID ticks. A slow stream defines direction, while a fast stream provides the entry trigger. Both apply classic two-brick reversal rules, and entries are permitted only when fast and slow directions match.

Exits are handled by a small target, stop, opposite fast Renko reversal, or a maximum holding time. After closing, a short cooldown in Renko bricks blocks immediate re-entry. Only one position per symbol is allowed, and a spread filter blocks entries when spread is large relative to the fast brick.

Default inputs: Fast 21, Slow 39, Entry Run 1, TP 1.4 fast bricks, SL 2.1, Max Hold 200 minutes, Cooldown 3, Max Spread Fraction 0.57, Lots 0.01.

Example tester run (XAUUSD, M1 host, real ticks, 2026-05-01 to 2026-08-24): 79 trades, +589.34 USD, PF 2.27, max DD 1.18%, win rate 64.56%. Historical demonstrat...

👉 Read | AlgoBook | @mql5dev

An EA implementation that constructs fixed-size Renko bricks directly from BID ticks, using classic two-brick reversal confirmation. A confirmed DOWN->UP reversal defines a support zone; a confirmed UP->DOWN reversal defines a resistance zone.

Entries require displacement: price must move away from the new zone before any retest qualifies. On a return to the zone, a completed Renko brick confirming rejection triggers an order. Each zone is tradable once, with a single active position per symbol. Exits occur via TP, SL, opposite reversal, or maximum holding time. A spread filter blocks trades when spread is large relative to brick size. No DLLs, external libraries, custom indicators, custom symbols, or offline Renko charts; the chart timeframe is only a host.

Defaults: Brick 18.0; Zone half width 1.65; Move away 0.90; Max age 53 bricks; TP 5.50; SL 2.90; Hold 6...

👉 Read | Forum | @mql5dev

This article connects sorting/searching basics to core data structures that make trading code faster and easier to reason about in MQL5: queues, as a foundation for later lists and trees.

It first builds a FIFO queue using a dynamic array with two operations: append at the end and restore from index 0. Removing index 0 triggers a shift, preserving insertion order and providing a clear “empty” return value.

It then upgrades to a circular queue (ring buffer) with fixed capacity, using read/write indices that wrap around. New data overwrites the oldest when full, avoiding costly shifts—ideal for sliding-window indicators like moving averages and other stream-processing tasks in MetaTrader 5.

👉 Read | AlgoBook | @mql5dev

This article tackles a practical UI gap in MT5 replay/simulation: restoring deleted Stop Loss and Take Profit directly from the chart, without relying on terminal dialogs.

The approach uses a draggable price line and derives the intended SL/TP from context (position side and relative level), while snapping to the symbol’s tick size by reusing the existing mouse indicator’s normalized price.

On the EA side, two new events are added and routed through a single SL/TP modifier. A key detail is passing negative values to mean “keep the current server-side value”, forcing a fresh PositionSelectByTicket and preventing accidental deletion of the other leg.

On the indicator side, interaction is rebuilt around C_Mouse instead of C_Terminal, with explicit hitboxes (e.g., close button) to make chart-only control deterministic for traders and developers.

👉 Read | NeuroBook | @mql5dev

MetaTrader 5’s History Navigator is extended from one-off date/time jumps into a persistent “historical bookmarks” system for repeatable chart research.

Each bookmark captures symbol, timeframe, timestamp (not bar index), plus a user-defined name and optional notes, so the original chart context can be reconstructed reliably even as history loads or shifts.

Persistence is handled by a dedicated CBookmarkStorage layer that serializes records to a small CSV file, validates input on load, and keeps UI logic out of file I/O. Updates are written immediately, with rollback on save failure to prevent memory/file divergence.

The existing NavigateToDateTime() engine is reused for both manual date navigation and bookmark recall, avoiding duplicated bar-search and chart-positioning logic while adding create/select/go-to/delete workflows in the dialog.

👉 Read | CodeBase | @mql5dev

MT5 Strategy Tester covers automated backtests, but manual price-action review still lacks an interactive bar-by-bar replay mode. A replay tool can hide future candles, reveal one bar at a time, and allow decision-making without hindsight bias.

A practical MQL5 design uses DRAW_COLOR_CANDLES with buffers initialized to EMPTY_VALUE, then progressively filled to reveal candles. Controls include an ON/OFF toggle, a draggable vertical anchor for the start point, Play/Pause, and Buy/Sell for a single paper trade with Entry/SL/TP lines.

Core logic combines OnChartEvent() for UI and drag handling with OnTimer() for timed playback, viewport tracking, price line updates, and TP/SL monitoring. Deactivation restores original chart properties and removes all replay objects.

👉 Read | VPS | @mql5dev

Part II extends queues into LIFO behavior by converting a FIFO implementation into a stack with minimal changes: only the read/remove point is adjusted, while insertion order stays intact.

It also notes that stacks mirror how CPUs manage call frames, which makes the data structure relevant beyond textbook exercises.

The text then moves from arrays to lists in MQL5. Because pointers to structures are restricted, classes are used to model nodes, enabling a singly linked list that behaves like a stack without relying on arrays.

Key takeaway: internal implementation can vary, but a stable interface determines usability and outcomes.

👉 Read | Signals | @mql5dev

MetaTrader 5 ZOrder cannot be overridden in a reliable way, so the focus shifts to using the platform event sequence to identify the real click target.

A minimal indicator shows the pattern: CHARTEVENT_MOUSE_MOVE is emitted before CHARTEVENT_OBJECT_CLICK. With overlapping objects, this order remains consistent and can be used to gate interaction.

Code updates consolidate priorities: keep default 0 and add ePriorityNull for non-interactive objects. This requires recompilation and small fixes in classes such as C_ChartFloatingRAD.

Input handling is adjusted by adding a state flag in C_Terminal and checking validity on MOUSE_MOVE, then accepting OBJECT_CLICK only when the click is marked valid and the object name matches. This avoids foreground checks and reduces dependency on manual ZOrder management.

Next step prepares multi-position and pending-ord...

👉 Read | Quotes | @mql5dev

Prop-firm sizing is a constrained optimization problem: the trade size must reflect both signal strength and the remaining daily/overall drawdown budget. Because these limits are path-dependent and sometimes expand with locked-in profit, static fractional or Kelly-based sizing cannot react correctly without live account state.

The refactor takes a previously firm-specific PropFirmAwareSizer and separates program terms from sizing math. A frozen PropFirmRuleSet captures variable rules (phase targets, fixed vs dynamic daily cap, news profit-credit haircut, drawdown basis, overnight policy). PropFirmAccountState becomes stateful and rule-driven, while pure functions stay unit-testable.

Key technical gain: correct handling of equity- vs balance-based drawdown checks, and explicit branching for dynamic daily limits. Validation compares the new implement...

👉 Read | Quotes | @mql5dev

A trade management panel defines batch order actions with configurable entry count for BUY and SELL buttons, opening positions based on lot size and selected entries.

Risk and cleanup controls include Close Profit (closes all profitable orders), Close Loss (closes all losing orders), and Close ALL (closes every open order). Set All TP and Set All SL apply a single take-profit or stop-loss value across all active orders.

Operational tools include trailing stop on/off, Buy Pending and Sell Pending using an input price to place limit orders, and Delete Pending to remove all pending orders. Close Above and Close Below close orders based on a user-defined price threshold.

Key parameters cover trailing timer frequency, optional break-even for orders without SL, default trailing behavior, pending-order TP/SL in pips, and a lot size calculator using risk percent a...

👉 Read | VPS | @mql5dev

Classic fixed-size Renko is generated internally from BID ticks, using the standard two-brick reversal rule. SuperTrend ATR and band values are computed from completed Renko bricks rather than time-based candles.

Trade entries are permitted only when the latest completed Renko brick direction matches the Renko-based SuperTrend direction. Position exits can be triggered by take-profit, stop-loss, a SuperTrend direction change, or a maximum holding-time limit. An optional short cooldown can be enforced before re-entry.

Risk controls include a strict one-position-per-symbol rule. The EA runs standalone with no external indicator, DLL, custom symbol, or offline chart requirement. A separate visual companion indicator is available at https://www.mql5.com/en/market/product/175340.

This is intended as an educational historical demonstration; default settings are not...

👉 Read | AppStore | @mql5dev