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MQL5 Algo Trading

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📈 نظرة تحليلية على قناة تيليجرام MQL5 Algo Trading

تُعد قناة MQL5 Algo Trading (@mql5dev) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 576 215 مشتركاً، محتلاً المرتبة 139 في فئة التكنولوجيات والتطبيقات والمرتبة 5 في منطقة المملكة المتحدة.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 576 215 مشتركاً.

بحسب آخر البيانات بتاريخ 28 أكتوبر, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 13 563، وفي آخر 24 ساعة بمقدار 571، مع بقاء الوصول العام مرتفعاً.

حالة التحقق: غير موثّقة
معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 2.09‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.40‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
وصول المنشورات: يحصل كل منشور على متوسط 12 063 مشاهدة. وخلال اليوم الأول يجمع عادةً 8 057 مشاهدة.
التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 40.
الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل indicator, chart, mql5, candle, range.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“The best publications of the largest community of algotraders. Subscribe to stay up-to-date with modern technologies and trading programs development.”

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 29 أكتوبر, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.

576 424

المشتركون

+57124 ساعات

+2 6087 أيام

+13 56330 أيام

12 063

عرض المشاهدات

~ 8 05724 ساعات

~ 9 49548 ساعات

2.09%

معدل المشاركة

~ 10

المشاركات في اليوم

Ads index

beta

أرشيف المشاركات

576 215

Perplexity AI is being used to accelerate development of rule-based trading systems by generating code drafts, test cases, and documentation for common patterns such as trend filters, mean reversion triggers, and risk controls. Output still requires strict validation: confirm indicator math, verify order sizing, and reconcile bar indexing to avoid lookahead. A production-ready setup typically includes deterministic backtests, walk-forward checks, and Monte Carlo analysis on execution assumptions. Logging, parameter constraints, and fail-safe handling for connectivity and rejected orders are mandatory. AI assistance can reduce iteration time, but strategy quality remains dependent on data hygiene, robust statistics, and disciplined change control. 👉 Read | Signals | @mql5dev

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A new indicator package is available featuring a “Good Tendency Estimator” combined with coloured candlesticks. The estimator is designed to quantify directional bias and highlight potential transitions in trend conditions, while the candle colouring provides a fast visual filter for momentum and regime changes. Typical usage focuses on aligning entries with the estimator’s direction and using colour shifts as confirmation or early warning. Key points to validate during testing include behaviour in low-volatility ranges, sensitivity to parameter changes, repainting risks, and performance across symbols and timeframes. 👉 Read | Freelance | @mql5dev

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Multi-period indicators with shifted lines require converting the shift into the current chart’s bar scale. A 1-bar shift on H4 becomes 4 bars on H1, and buffer copying must start from a shift-adjusted reference index to align values correctly. Library updates: buffer shift setters now allow shifts on calculated buffers, and calculated buffer copy uses the line shift with an inverted sign to select the correct source start. Indicator factory methods (MA/AMA/DEMA/TEMA/VIDYA/Bands/Alligator, etc.) compute shiftBars = shift * periodBarRatio, pass that to the native handle, and apply the same shift to drawn and calculated buffers. Common logic was consolidated: standard line types were normalized across indicators, universal preparation/clearing paths were reduced to 1/2/3-line cases, and a buffer-clear routine prevents artefacts from inactive indicators... 👉 Read | AppStore | @mql5dev

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Market structure can be quantified by tracking sequences of higher highs/higher lows or lower highs/lower lows, and flagging when that pattern changes. This indicator applies fixed swing rules and prints non-repainting labels. Swing highs/lows are confirmed only after N candles close to the right (default N=5), so markings appear with a delay and never shift. Each confirmed swing is classified as HH/LH versus the prior swing high, and HL/LL versus the prior swing low. Break logic supports BOS and CHoCH. BOS is triggered when a candle closes beyond the last swing in the current trend direction and is drawn as a dashed line. CHoCH is triggered when a candle closes beyond the last swing against the active trend and is drawn as a solid line. Break detection can use close (default) or wick. Inputs include swing strength, bars to scan (default 3000), disp... 👉 Read | CodeBase | @mql5dev

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Spread Monitor is a lightweight information indicator for MetaTrader 5 that shows the current spread in pips in real time. The data is presented as a compact on-chart panel with colour-coded status markers and a level bar for quick visual assessment. Designed for low overhead and continuous monitoring, it helps track spread changes during varying liquidity conditions and around news-driven volatility. 👉 Read | CodeBase | @mql5dev

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A refreshed design-oriented market price view has been released, focused on clearer trend visibility and a cleaner chart presentation. Deployment requires adding a bitmap asset. Download Mr.Wave.zip, extract surfer.bmp, and place it in the platform’s Images directory so the interface renders as intended. If the image is missing or stored in a different path, the UI will fall back to a blank placeholder or fail to display the visual element, which can lead to inconsistent layout across installations. 👉 Read | Quotes | @mql5dev

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Mean reversion triggers can be gated by a convergence indicator count to reduce noise. This setting defines how many independent signals must align before a reversion event is allowed to fire. A lower threshold such as 5 increases trade frequency and can react earlier, but typically raises the false-positive rate in ranging conditions with weak confirmation. A higher threshold such as 9 is more selective and may improve signal quality, but can delay entries and miss shorter reversals. Practical selection depends on symbol volatility, timeframe, and the number and correlation of indicators feeding the convergence check. 👉 Read | Forum | @mql5dev

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This article shows how to build market-pattern models in MetaTrader 5 using CatBoost, focusing on a small, well-chosen feature set instead of endless hand-tuned trading rules. The goal is to reduce overfitting caused by optimizing many inequalities across symbols and periods. A practical pipeline is outlined: generate predictors and a binary target directly from an MQL5 Expert Advisor, export samples to CSV, train CatBoost via a standalone exe (no Python/R), then run the trained model in MT5 using a CatBoost interpreter class. Feature engineering emphasizes context: time features, price position vs. key levels, volatility, and oscillator values across multiple timeframes, sampled at several bar offsets to capture dynamics. The baseline signal is a simple MA-cross trend entry; ML is used to filter false entries in flat markets while keeping implementation ac... 👉 Read | Quotes | @mql5dev

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MA Crossover EA is an automated strategy that places trades when two moving averages intersect. It supports any instrument and timeframe, with configurable fast and slow MA periods. Trade logic is limited to one open position at a time. A BUY is opened when the fast moving average crosses above the slow moving average. A SELL is opened when the fast moving average crosses below the slow moving average. Risk controls include optional Stop Loss and Take Profit levels defined in pips. Execution can be restricted to bar-close signals via a TradeOnNewBar setting to reduce intra-bar noise. Key inputs typically include lot size, FastMAPeriod, SlowMAPeriod, StopLoss, TakeProfit, and a MagicNumber for trade identification. Validation in a strategy tester and parameter optimisation per symbol are recommended before live use. 👉 Read | VPS | @mql5dev

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MarketInfo is an information script for MetaTrader 5 that logs key telemetry for the active instrument and outputs a chart comment for quick review. It reports current Bid, Ask, and spread in pips, along with symbol parameters such as minimum and maximum lot size, lot step, and price digits. Volatility is calculated using ATR for a configurable period. The script also shows the time remaining until the current bar closes to support timing-sensitive execution and monitoring. For a user-defined number of recent bars, it aggregates high, low, average close, average volume, and average range. A simple classification marks the current state as upward, downward, or sideways based on recent price behavior. 👉 Read | Docs | @mql5dev

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A risk-check script estimates worst-case gap losses for all open positions ahead of weekend or holiday closures. It sums the projected losses and compares them with the remaining room under the next trading day’s daily loss limit. Output includes the next day’s limit in account currency, the floating loss carried over, and per-position details: symbol, side, lots, configured gap for its group, and the loss that gap implies. A final verdict flags OK or TOO MUCH, including a per-position reduction amount. Key point: stop-loss orders do not cap gap risk, since fills occur at the first available price after the gap. Inputs cover account size (or current balance), daily loss limit and safety margin, whether carried floating loss counts against the next day, per-asset gap percentages (FX, metals, indices, crypto, other), and symbol group matching via name fr... 👉 Read | Signals | @mql5dev

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MTF Trend Context [Vian] is a compact MT5 panel that reports trend state across five selected timeframes and summarizes alignment as ALL BULLISH/BEARISH, MOSTLY BULLISH/BEARISH, or MIXED. Trend classification uses a single EMA rule per timeframe: Bullish when Close > Fast EMA > Slow EMA, Bearish when Close < Fast EMA < Slow EMA, Neutral otherwise. Default EMA lengths are 20 and 50, both configurable with Slow required to remain greater than Fast. Each row is evaluated on the most recently closed bar of its own timeframe (shift 1), avoiding the current forming candle. Data readiness is validated before display; missing history or incomplete EMA calculations are shown as N/A rather than inferred. Presets cover Scalping, Intraday, and Swing, plus a five-timeframe Custom set. If any row is N/A, alignment is not upgraded and remains MIXED with a count of... 👉 Read | Freelance | @mql5dev

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Expert Advisors tag trades with a magic number. Magic Number Scorecard groups closed account trades by magic number to produce one result line per EA; magic 0 represents manual trading. This provides a fast view of which systems generate net results versus volume. Per magic number, the report includes trades, wins, losses, win rate, gross profit, gross loss, profit factor, net profit, average trade, best and worst trade, maximum drawdown based on the closed-trade equity curve, and symbols traded. Rows are sorted by net profit. Counting rules: one trade equals one closed position. All related deals are aggregated, including profit, swap, commission on entry and exit, and fees. Partial closes still count as one trade. Ownership is taken from the opening deal’s magic number, so manual closes remain attributed to the originating EA. Open or partially open positio... 👉 Read | Freelance | @mql5dev

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CNewsFilter provides a single decision point for EAs: whether the current time falls into a configured news blackout window. It reads the built-in MT5 economic calendar, filters by selected currencies and minimum importance, and blocks trading minutes before and after each release. Integration focuses on a small API: SetCurrenciesFromSymbol(symbol) for base/profit/margin currencies, or SetCurrencies("USD,EUR"). Use SetImportance(low/moderate/high) and SetWindow(before, after). IsNewsTime() returns true inside the window. CurrentEvent() and NextEvent() expose event name, currency, and time for UI panels. Total() and Event(i) return the loaded events sorted by time. SetRefresh(seconds) and SetLookAhead(hours) control cache refresh and horizon. Operational notes: no web requests, DLLs, or terminal permissions. Times are trade-server time (TimeTradeServer()). O... 👉 Read | VPS | @mql5dev

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MultiIndicatorDivergence adds a compact divergence panel that aggregates signals across timeframes, from M1 through monthly. The panel compares price action against multiple indicators to flag disagreements commonly used as early reversal warnings. Each cell represents an indicator such as RSI, MACD, plus additional oscillators. Color output is simplified: green indicates potential upward pressure, red indicates potential downward pressure, and dark indicates no actionable divergence at the moment. A higher count of the same color suggests broader indicator alignment. Layout includes six columns covering the current bar and the prior five bars, enabling quick verification of whether divergence is emerging, persisting, or fading. This is a decision-support aid and does not replace risk controls. 👉 Read | Signals | @mql5dev

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The Pro version targets development teams that require tighter control over execution and a broader toolset for building, testing, and deploying automated trading logic. Key additions typically include advanced debugging and profiling, richer configuration for strategy parameters, and extended options for managing data feeds and symbol specifications. Deployment workflows are expanded with more granular environment separation and improved logging for incident review. Licensing is generally structured for commercial usage, with clearer terms around redistribution, support coverage, and long-term maintenance. Suitable for production setups where reproducibility, auditability, and predictable updates matter. 👉 Read | Forum | @mql5dev

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A multi-indicator trading strategy combines RSI, Parabolic SAR, Heiken-Ashi, Stochastic, CCI, Williams %R, and Bulls/Bears Power to align trend, momentum, and reversal signals. Trend filtering is typically handled by Heiken-Ashi candles and SAR direction. Momentum confirmation can be taken from RSI and Stochastic crossing key levels, while CCI and Williams %R help detect overbought/oversold conditions and short-term exhaustion. Bulls and Bears Power are often used to validate whether buyers or sellers are gaining control, reducing reliance on any single indicator. Practical implementation usually requires strict entry rules, a volatility-aware stop, and limits on conflicting signals to avoid overfitting. 👉 Read | AppStore | @mql5dev

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Static prompts in LLM-driven Expert Advisors fail because market regimes change faster than manual prompt iteration cycles. Metaprompting treats the prompt as a trainable component. A separate optimizer LLM generates prompt revisions, tests them against realized trade outcomes, and promotes the best version to production. A practical architecture splits responsibilities: an execution agent returns BUY/SELL plus confidence from OHLCV and indicators; an evaluator converts closed-trade results into metrics (directional accuracy, profit factor, R-multiple, flat rate); a meta-LLM updates the prompt on schedule or when metrics degrade. MQL5 can call a local Python service over WinHTTP without third-party DLLs. Example backtest (EURUSD M15, Mar–Apr 2026) showed 99 trades, 1.35 profit factor, 2.77 Sharpe, and low drawdown, with limits noted around data l... 👉 Read | VPS | @mql5dev

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Math engines are often treated as drop-in equivalents. A benchmark using an 8-16-8-1 MLP forward pass compared three MQL5 paths: native matrix/vector double, ALGLIB CMatrixDouble, and ONNX Runtime via OnnxRun(). Weights and test vectors were generated once in Python using float64, then reused unchanged. Each engine ran the same inputs, with outputs checked against the Python float64 reference and latency measured per call in microseconds, including p95 and p99. Results show native and ALGLIB matching the reference to machine precision, while the ONNX path degrades accuracy and time due to its default float32 tensors and explicit input casts. The harness is diagnostic only and contains no trading logic. 👉 Read | Quotes | @mql5dev

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Builds a session volume profile for MT5 from tick data, not bar-based TPO, so aggregation is accurate but performance-critical. The design keeps OnCalculate incremental and shifts all drawing to an OnTimer loop with three states: full rebuild after session-bound edits, full redraw on chart moves or new volume maxima, and partial updates for live ticks. State is stored in hash-based buckets for O(1) access, plus an update set to redraw only touched price levels. Bucket sizing can be ATR-driven or manual. Rendering uses pixel-space OBJ_RECTANGLE_LABEL bars for precise proportional widths, with draggable start/end vlines, multi-instance IDs to avoid object collisions, and an optional POC line that tracks the highest-volume price. 👉 Read | Calendar | @mql5dev