A MetaTrader 5 indicator was extended to plot activation functions and their derivatives side by side, focusing on why sigmoid becomes problematic in deeper networks due to derivative attenuation during backpropagation.

The update adds an enum for function selection and new inputs: equation id and Y-axis scale factor, alongside range and step. Output text now includes function name, f(x), and f’(x) at the cursor point, with minor UI cleanup for chart readability.

The core change is a switch-based dispatcher where each case assigns fx and dx. Adding a new activation function requires registering its enum name, then providing the function expression and its derivative in the corresponding case.

Default set includes sigmoid, tanh, ReLU, and eLU, highlighting practical differences in output range and gradient behavior.

👉 Read | CodeBase | @mql5dev

Beluga Whale Optimization (BWO) is evaluated as a population-based optimizer for strategy parameter tuning under a shared, reproducible MT5-style test framework. It uses three operators with a time-varying balance factor that smoothly shifts the population from exploration to exploitation, plus a low-probability “whale fall” step to refresh diversity.

Exploration updates coordinates in sine/cosine pairs around a randomly chosen partner, improving space coverage without many tunable knobs. Exploitation combines attraction to the current best with Lévy-flight steps, where jump magnitude decays over iterations; whale fall injects early large relocations that rapidly shrink over time. Greedy selection prevents fitness degradation.

On the benchmark (30 agents, 10k evaluations), BWO scored 47.51%, but showed suspiciously better results at higher dimensio...

👉 Read | Signals | @mql5dev

Model drift detection for MQL5 can be handled with a lightweight PSI watchdog that compares a rolling live window against a captured reference, logs each refit, and posts a webhook only on state transitions.

Implementation uses one PSI monitor class plus a minimal WebRequest-based JSON sender, integrated into an EMA-cross demo EA with a companion indicator. Two monitors run in parallel: normalized RSI as a feature proxy, and a sigmoid-transformed EMA spread as a prediction proxy.

PSI is treated as distribution shift only, not model accuracy or trading performance. Alerts are investigation triggers, not auto-retrain signals. Quantile buckets, epsilon flooring, and a cooldown-controlled state machine reduce noise; thresholds still require per-symbol calibration.

👉 Read | Signals | @mql5dev

TradeMux splits quant work where it belongs: Python for research and decisions, MetaTrader 5 for broker execution. A Python execution service generates signals (e.g., CatBoost over causally L1-filtered features), runs pre-trade risk checks, then routes validated orders to MT5 without duplicating strategy logic in MQL5.

The MT5 side stays minimal: one EA that polls via WebRequest and calls native trade functions, with a zero-DLL design suited for VPS security. Python reads normalized account/position state, pulls OHLCV into pandas, monitors exposure, and can flatten everything with an atomic kill_switch().

Key benefit for multi-broker deployment: symbol suffixes, lot steps, and execution modes are normalized, so the same code runs across MT4/MT5 brokers; OANDA uses a compatible client class. Multi-account broadcasting and supervisor-style auto-restart c...

👉 Read | NeuroBook | @mql5dev

Probabilistic Sharpe Ratio (PSR) and Minimum Track Record Length (MinTRL) address what a plain Strategy Tester Sharpe cannot: whether the observed Sharpe is statistically credible given finite samples and non-normal returns. The implementation includes skew/kurtosis corrections and clearly distinguishes whether MinTRL supports beating SR* or confidently failing it.

The article builds a per-trade return series directly from MT5 deal history by consolidating partial closes via DEAL_POSITION_ID and normalizing P/L by pre-close balance, with safeguards for balance operations. Annualization is fixed by computing trades-per-year from deal timestamps, avoiding the common “bars-per-year” mismatch.

A real MT5 pitfall is documented: iHighest/iLowest return bar indexes, not handles, so using CopyBuffer silently breaks signals. The corrected Donchian logic reads price array...

👉 Read | VPS | @mql5dev

This article ports a Python/Plotly 3D market view into native MetaTrader 5, replacing external exports and browser snapshots with an on-chart DirectX 11 scene built on CCanvas3D. Price maps to Y, time to Z, and tick volume to X, turning each candle into a lit rectangular prism with direction-based coloring.

The Expert Advisor builds all geometry manually (vertices, normals, indices) and merges axes plus bars into a single CDXMesh for one GPU draw call. Historical rates come from CopyRates, then prices and volumes are normalized into a fixed scene cube, with safeguards to keep low-range or zero-volume bars visible.

Interactivity is handled via an orbital camera (mouse drag + scroll), and rebuilds are deferred from click events to OnTimer to avoid blocking. Time labels are overlaid as standard chart objects, keeping the 3D view readable.

👉 Read | AlgoBook | @mql5dev

MQL5 model visualization can show layer topology but not the actual connectivity implied by dense weights. A dense layer’s weight tensor is a matrix where each cell is a single connection from an input index to a neuron index, with sign and magnitude affecting direction and strength.

The approach builds a second layout: rows of neurons (“bands”) and runs of connections (“webs”) keyed by exported value names. Dense ops open new rows and record their matrices; unary ops (activations, reshapes) are folded into the existing row label to avoid duplicating nodes.

Matrix orientation is resolved via the exporter attribute (e.g., transB), not heuristics, preventing plausible but incorrect wiring. Unsupported layers (conv, RNN, attention) are declined with a reason instead of drawn inaccurately.

Rendering draws one line per stored weight with per-layer normaliz...

👉 Read | Quotes | @mql5dev

A tick scalper passed CodeBase validation on the fifth submission after multiple failed runs, but local Strategy Tester runs with execution delay still produced systematic trade-operation rejections. The surviving validator log referenced EURUSD H1 despite M1 design, while the actual issues were execution timing, freeze-level constraints, and position tracking under latency.

Key failures observed: forced closes rejected inside freeze level; SL/TP computed from stale price snapshots leading to INVALID_STOPS; two-step entry leaving positions temporarily unprotected and, on hedging accounts, sometimes modifying or closing the wrong position due to symbol-only selection. Near session close, modify and safety-close requests were rejected as MARKET_CLOSED, leaving trades unmanaged.

Result: validation success did not confirm correct behavior under delay. Requ...

👉 Read | Signals | @mql5dev

Tick Scalper Helper is a manual trading utility for MetaTrader 5 focused on tick-level charting and fast order handling. It replaces time-based candles with a compact tick chart where each tick is rendered as a bar, with configurable aggregation (1, 2, 4, 8… ticks per bar), optional time-scaled mode, and light/dark themes. Live BID/ASK lines are updated on every tick with fixed, non-ambiguous colors.

The on-chart panel provides one-click buy/sell, optional SL/TP in points with automatic adjustment to broker stop constraints, and symbol-scoped close actions (buy, sell, profitable only, all). Orders are prebuilt for lower terminal-side processing overhead, with server rejects and constraint issues reported on-chart and in logs. Positions, pending orders, and SL/TP levels are drawn directly on the tick chart.

A built-in depth-of-market view can be shown on ...

👉 Read | NeuroBook | @mql5dev

An indicator tracks the Asian session range per day (default 00:00–07:00 UTC) and renders it as a rectangle. A breakout window then runs until 11:00 UTC, placing a BUY/SELL arrow on the first closed candle that exits the range with an added buffer (default 10% of the range).

Risk/return levels are calculated from the range: stop is either the midpoint or the opposite boundary; target is entry price ± (range × multiplier), with 1.5 used by default. Signals are generated on closed bars only and are not repainted.

Key inputs cover server UTC offset, Asian range start/end, breakout window end, buffer percentage, TP multiplier, stop mode, one-signal-per-day limit, alerts, and box color. Typical use is on M5–M15 for GBPUSD, EURUSD, and XAUUSD. This is a session breakout visual tool, not a profit guarantee.

👉 Read | Quotes | @mql5dev

A new MT5 indicator adds TradingView-style chart navigation by handling mouse input via chart events and disabling the platform’s default left-button scroll. Candles can be dragged freely in both axes, with vertical panning implemented through a fixed price scale derived from the current visible range to avoid jumps.

The price scale supports stretch/compress by dragging, and price zoom is available via Shift+wheel over the chart or wheel over the price scale. Time zoom maps to MT5’s discrete bar zoom levels and can also be controlled by dragging the time axis.

AUTO and ON/OFF controls restore auto-fit scaling and toggle the behavior without affecting trades or drawings. Order/SL/TP lines and selected objects remain draggable, and removing the indicator restores prior chart settings. Single-file MQL5 code is structured as a reference for mouse events...

👉 Read | Signals | @mql5dev

Prop firms often restrict trading minutes around high-impact news. Prop News Countdown reads the MT5 built-in economic calendar and renders a chart overlay with the next event and a live hh:mm:ss countdown, plus a configurable list of upcoming releases.

A “NEWS WINDOW NOW” state is shown from X minutes before to Y minutes after each event, matching firm rules. Optional features include vertical dotted lines at news time and alerts (pre-news and window start) via popup and MT5 mobile push. The indicator is display-only and never opens, closes, or modifies trades.

Filtering supports AUTO currencies from the chart symbol or an explicit list, with importance and look-ahead controls. Error handling flags missing/unsynced calendar data, warns on unknown currencies, and ignores all-day/tentative times for window logic. All timing uses trade-server time and ...

👉 Read | Signals | @mql5dev

VrDz Bot v1.23 is a lightweight EA that combines scalp and swing workflows behind a panel-based control surface. It focuses on manual execution support with automated position management rather than fixed entry signals.

Core risk controls include fixed-lot or risk-percent sizing, max-lot caps, margin checks, and spread/slippage filters. SL/TP can be configured as fixed points or ATR-based, with enforcement of broker minimum stop distance.

A one-click Scalp/Swing toggle rewrites SL/TP across open positions, disables scalp-only functions in Swing mode, and restores prior state when switching back. Partial close, break-even, and trailing stop are configurable and automatically disabled in Swing mode.

The “Secure All” layer runs in both modes, moving stop loss to lock in profit on winning positions while skipping losers. The panel exposes live RSI/ATR/spread/Pn...

👉 Read | Signals | @mql5dev

Spread is a major execution cost factor for scalpers, automated systems, and news-driven trading. Standard terminal charts show only the current instant spread, while intra-bar widening during rollovers, session transitions, and macro releases remains hidden.

The Spread Monitor indicator adds a subwindow view for MT4/MT5 that records live ticks and plots two curves per candle: Max Spread for the bar and Avg Spread across captured ticks. This makes spread behavior measurable instead of anecdotal when assessing execution quality and setting risk constraints.

Max Spread highlights peak spikes used to configure Max Spread Allowed filters for EAs. Avg Spread provides a practical baseline for real transaction costs. A dashboard displays current spread, active-bar average, active-bar maximum, and tick count.

Works on FX, metals, indices, and crypto CFDs, wi...

👉 Read | VPS | @mql5dev

Event streams in markets are irregular and bursty, so fixed-interval models often miss the underlying dynamics. The article maps this problem to event-based vision and the E-STMFlow framework, which treats data as a continuous process driven by micro-events.

Core idea: a spatio-temporal state-space model maintains a compact hidden state and updates it per event using efficient linear transitions. This avoids heavy correlation tensors and reduces compute while preserving long-range structure.

For trading systems, the same design fits tick/order-flow feeds: fast online updates, noise-robust behavior from small parameter counts, and better tracking of latent factors (momentum, liquidity pressure) without forcing data onto an artificial time grid.

👉 Read | NeuroBook | @mql5dev

MQL5 resource handling changes how MT5 systems get packaged and maintained. The key split is internal resources embedded into the executable versus external resources loaded from files at runtime.

Embedding allows shipping a single Expert Advisor that contains dependent assets, including indicators and data. This reduces failure modes caused by missing or deleted files and enables controlled configurability, including reset-by-reinstall workflows.

At compile time, a resource directive can read a file (for example a text file) and store its contents as a constant data block inside the EX5, effectively equivalent to a large in-code array.

For executable embedding, compiler path rules matter. Resource paths are resolved relative to the source file, while terminal loading uses sandbox-relative paths. With correct relative placement, compilation can also build th...

👉 Read | AppStore | @mql5dev

This article digs into a subtle MT5 behavior: graphical objects behave differently in the main chart versus indicator subwindows, especially when an indicator that “draws in main window” is hosted inside another indicator’s subwindow.

A simple OBJ_CHART-based indicator is refactored into an OOP-friendly design, then embedded as a compiled resource inside a wrapper indicator. Even when the embedded indicator is shown in a subwindow, its OBJ_CHART can still appear in the main window, revealing that object placement depends on how MT5 resolves window context, not only where the indicator is listed.

The practical fix is to detect the actual subwindow index after the indicator is attached, then create objects using that resolved index, with proper cleanup and unique object naming to support multiple instances.

👉 Read | Calendar | @mql5dev

Part 5 moves eigenvalue-based risk concentration from a one-shot script into an MQL5 indicator. RiskConcentrationIndicator.mq5 plots the dominant eigenvalue as a percentage of total variance in a separate window, with blue bars below an alert level and red bars at or above it, updated per bar.

The calculation treats three instruments as an equally weighted, unit-exposure basket. It measures concentration in the covariance of the return series, not position sizing, contract multipliers, or currency exposure.

Core changes target live performance and data quality. A rolling prefix-sum engine keeps return sums, squares, and cross-products in persistent arrays, enabling O(1) window covariance via subtraction. Timestamp alignment uses iBarShift() exact matches; missing or asynchronous bars are excluded rather than zero-filled, with MinValidDataFraction gat...

👉 Read | Docs | @mql5dev

Multi-position monitoring benefits from separating selected-position loss, stop-based estimates, and account-wide pressure.

A reusable MQL5 calculator is defined as a measurement layer for an existing EA. It builds a snapshot with explicit validity flags, quote freshness checks, and stop-estimate availability, then exposes selected_level and account_level with reason masks.

Measurements include net floating P/L plus swap, gross floating loss, two stop quantities (entry-to-stop loss and current-to-stop giveback), equity gap vs balance, margin level, and stop coverage. N/A is used when no stops exist; missing stops can optionally block new exposure.

OrderCalcProfit is used for stop estimation, with conservative diagnostics for stale ticks, missing properties, and crossed stops. The module does not trade; the host EA owns scheduling and responses.

👉 Read | NeuroBook | @mql5dev

Linear price charts distort percentage-based trends, making straight regression channels systematically misaligned. A log-price fit keeps constant-percent growth linear in the model, then renders the result back on a standard chart as a curve with adaptive banding.

The indicator re-evaluates only on bar close and selects its own look-back by testing 19 candidate windows and choosing the highest log-price correlation, with ties resolved toward the shorter window. Invalid windows (insufficient history or non-positive prices) are skipped.

Output includes a midline plus deviation-based edges that stay a fixed percentage from the trend, zone shading by distance from the midline, and a forward projection for 6–60 bars. A status card reports direction, best window, correlation grade, growth rate per calendar time, and live distance from the midline in devia...

👉 Read | AlgoBook | @mql5dev

A practical workflow for forecasting whether EURUSD will have an unusually large 08:00–16:00 session range, using only information available at 08:00. “Large range” is defined relative to recent conditions: 25% above the mean range of the prior 20 valid target sessions.

A binary logistic regression is fit in SPSS on 2020–2023 data with two pre-session features: morning range relative to the historical scale, and the pre-session open-close move normalized by that range. The model is frozen and evaluated on a 2024 holdout.

Forecast quality is measured as probabilities, compared against constant and rolling-frequency baselines using Brier score, log loss, and calibration groups. The same probability math is reproduced in MQL5 with a numerically stable sigmoid, plus auditing rules to ensure sessions are valid and results are reproducible.

👉 Read | Forum | @mql5dev