History of MQL5.community development

We build a trade throttle for MQL5 EAs using a token bucket with a priority queue to control order submission rate. Tokens refill at a configurable per‑second rate, allowing short bursts up to capacity and then enforcing sustained throughput. When the bucket is empty, requests are queued and later released by priority with FIFO tiebreaks. This keeps execution within safe limits without discarding valid signals under load.

This article implements an MQL5 custom indicator that detects Larry Williams Oops gap reversals and marks bullish and bearish arrows on the chart. It details configurable gap and validity thresholds, same-bar or later confirmation, first-fill-only logic, historical backfilling, and incremental updates so signals remain consistent on both history and newly completed bars.

A practical bridge from the options market into MetaTrader 5 for gold. We compute near-the-money implied volatility by solving Black-Scholes from quoted prices, compare it with 30-day realized volatility, and use the ratio as a regime proxy. A Python feed publishes the value, an MQL5 script consumes it with WebRequest, and a background service keeps a panel current and alerts on changes. Source code for all parts is provided.

MQL5 lacks native unit testing, so utility bugs in lot sizing, pip value, and normalization often slip into production. This article presents a zero‑dependency framework built from preprocessor assertion macros, interface‑based suites, and a central runner/formatter. It runs as a script in OnStart, executes deterministic tests, and prints pass/fail summaries to the Experts tab to catch rounding, boundary, and error-handling defects before deployment.

We invite you to learn about the K²VAE framework and how the proposed approaches can be integrated into a trading system. You will learn how the hybrid Koopman–Kalman–VAE approach helps build adaptive and interpretable models. The article concludes with practical results from using the implemented solutions.

We build a rolling price channel by fitting the 0.1, 0.5 and 0.9 conditional quantile lines via IRLS with pinball loss, packaged as a reusable class and two MetaTrader 5 indicators. We verify in-sample coverage, examine quantile crossing, and compare the channel width with ATR, Bollinger and regression widths on matched horizons. Tests in the Strategy Tester show the edges are descriptive, while the normalized width works as a volatility/regime feature.

In this article, we refine a moving average crossover strategy with a momentum candle filter and an immediate retracement bar confirmation. When both conditions are met, a pending stop order is placed using a pivot-based stop loss and a 2R take profit. The complete MQL5 Expert Advisor code, finite-state-machine logic, and chart annotations are detailed.

Bollinger Band mean reversion degrades in trending regimes when ADX is high and bandwidth expands. We separate direction from trade selection with a two‑stage meta‑labeling pipeline: a gradient‑boosted secondary classifier trained with PurgedKFold on band‑specific features (BBP, BBB, bandwidth regime) outputs action probabilities that drive probability‑based bet sizing. The MQL5 implementation loads the ONNX model and applies position sizing within a two‑EA architecture to filter low‑quality band touches.

This article presents a circuit breaker for MQL5 that monitors combined daily P&L (realized plus floating) on every tick and compares it to a configured loss limit. On breach, it closes positions, cancels pending orders, and activates a HALTED state that blocks further order submission in the EA until server‑time midnight. The package provides a chart dashboard, a demo Expert Advisor, a verification script, and notes on extending the halt signal across EAs.