MQL5 Algo Trading
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نمایش بیشتر📈 تحلیل کانال تلگرام MQL5 Algo Trading
کانال MQL5 Algo Trading (@mql5dev) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 547 053 مشترک است و جایگاه 143 را در دسته فناوری و برنامهها و رتبه 5 را در منطقه المملكة المتحدة دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 547 053 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 28 اوت, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 18 565 و در ۲۴ ساعت گذشته برابر 1 357 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 2.43% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.54% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 13 307 بازدید دریافت میکند. در اولین روز معمولاً 8 440 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 29 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند indicator, chart, mql5, candle, range تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“The best publications of the largest community of algotraders.
Subscribe to stay up-to-date with modern technologies and trading programs development.”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 29 اوت, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامهها تبدیل کردهاند.
547 053
مشترکین
+1 35724 ساعت
+5 2047 روز
+18 56530 روز
آرشیو پست ها
547 192
Adaptive Kalman Trend Filter uses a single-state Kalman estimate with process noise (Q) recalculated on every bar. Q is scaled between min and max multipliers using Kaufman’s Efficiency Ratio (ER), avoiding fixed-parameter lag versus whipsaw trade-offs. High ER raises Q and the Kalman gain, keeping the line closer to price; low ER reduces Q and increases smoothing during range conditions.
Regime bands are derived from rolling residual volatility (price minus Kalman line). Band width is the residual standard deviation times a multiplier that is further expanded as ER falls, producing tighter bands in directional markets and wider bands in chop. Color state changes are confirmed on closed bars only, so signals do not repaint.
Key inputs include base Q, measurement noise (R), ER/band lookbacks, regime threshold, and band multiplier. Typical tuning targets...
👉 Read | Freelance | @mql5dev
547 192
Quantora Trading Cost Calculator for MT5 estimates total trade cost before entry using live symbol data and user inputs. It aggregates spread, commission, and swap into a single view to reflect expected costs under current conditions.
Inputs include lot size, direction, commission per lot, and holding period. Output breaks down spread cost, commission cost, and swap impact, then totals the estimate in account currency. The cost is also shown as a percentage of account balance.
The panel displays tick size, tick value, and contract size to adapt calculations across instruments and broker settings. Works on all symbols and timeframes with automatic updates. Analysis-only utility with no order placement and no signal generation.
👉 Read | NeuroBook | @mql5dev
547 192
Quantora Spread Monitor MT5 is a real-time spread monitoring indicator for MetaTrader 5. It continuously tracks current spread and records minimum, maximum, and average values to quantify changing transaction costs over time.
A built-in history graph highlights sudden spread spikes and periods of instability. Spread levels are classified from low to extreme, with configurable thresholds to match specific risk and cost limits.
Alerts trigger when the spread exceeds a defined level, with popup, sound, and push options. A cooldown mechanism reduces repeated notifications during volatile bursts.
The dashboard presents current spread, statistics, symbol details, and server time in a compact layout. It supports all symbols, updates automatically, and is designed strictly for monitoring without trade execution or signal generation.
👉 Read | Freelance | @mql5dev
547 192
Quantora Trade Manager MT4 is a position management utility for MetaTrader 4 focused on controlling and protecting existing trades rather than generating entries. It automates routine actions including stop loss, take profit, break even, and trailing stop to reduce manual intervention and keep execution consistent.
The manager can auto-apply missing SL/TP, then move positions to break even after a configurable profit threshold. A trailing stop module can incrementally secure profit as price moves in the intended direction.
Filtering supports manual trades, all trades, or a specified Magic Number, and can run per-chart symbol or across all symbols for multi-strategy accounts. Daily protection rules allow profit targets and loss limits to trigger predefined responses. A dashboard summarizes account state, open positions, and active settings, with controls for...
👉 Read | Calendar | @mql5dev
547 192
MetaTrader 5 economic calendar access in MQL5 is split across MqlCalendarCountry, MqlCalendarEvent, and MqlCalendarValue. A unified structure can simplify consumption by grouping country metadata, event definition, and release values under one record.
A provider pattern standardizes access through Get(), Exists(), Next(), and Previous(), with filters for time range, currency, country code, and importance. Next/Previous rely on bounded lookahead/lookback windows to keep calls predictable.
Strategy Tester limitations require alternative sources since calendar APIs can fail in backtests. Exporting live calendar data to CSV enables deterministic testing, while a SQLite backend scales to large history sets and supports SQL filtering. Optional in-memory caching reduces repeated DB latency during optimizations.
👉 Read | VPS | @mql5dev
547 192
Moving-average inputs were extended with statistical signal processing to reduce market noise, using Independent Components Analysis (ICA) as a blind source separation step.
Pipeline used SMA-filtered OHLC data with 5-day lags, exported from MQL5 (49 columns) and modeled in Python. A surrogate target based on future SMA change aligned with raw return direction about 81% of the time, and showed improved classification accuracy as lags increased, unlike raw returns.
FastICA on 24 SMA/lag features peaked near 18 components and plateaued after ~13; 12 components were retained to control complexity. KMeans on the ICA manifold showed mostly uniform error rates, with one small, unreliable low-error cluster.
Models were tuned via RandomizedSearchCV, exported to ONNX, then loaded in an MQL5 EA alongside indicators and trade management.
👉 Read | NeuroBook | @mql5dev
547 192
Differential Search Algorithm (DSA), proposed by Pinar Civicioglu (2012), targets continuous optimization as an alternative to PSO and DE. It maintains a population and updates candidates through directed moves with controlled randomness.
Per iteration, each agent picks a direction via B-DSA (permutation), S-DSA (top-N sampling), E1-DSA (single random leader), or E2-DSA (best leader). Step magnitude uses Gamma-distributed scaling, allowing occasional large jumps and negative steps.
A coordinate mask restores selected dimensions to previous values, then greedy selection keeps only improved candidates. Typical implementation separates Init, Moving, Revision, plus direction generation, mask creation, scale factor (Gamma RNG), and boundary control.
👉 Read | Forum | @mql5dev
547 192
Financial time series work increasingly depends on probabilistic forecasts, not point estimates. Longer horizons amplify error accumulation, volatility sensitivity, and compute costs, especially under regime shifts driven by earnings, macro data, and geopolitics.
K²VAE combines Koopman linearization, Kalman-style online correction, and a VAE for scenario generation. Tokens are built from multivariate patches to capture cross-asset interactions, then mapped into an observable space where a learned Koopman operator rolls dynamics forward.
Residuals from the linear rollout feed KalmanNet via control inputs, producing updated state and covariance per step. The decoder samples multiple future trajectories, returning distributions with confidence intervals suited for risk-aware trading and portfolio sizing.
👉 Read | VPS | @mql5dev
547 192
Look-ahead bias remains a primary reason ML trading models fail on non-stationary live data. It appears when labels are derived from future price movement, producing inflated backtests, weak out-of-sample results, and low robustness due to overfitting.
A proposed alternative is oscillator-based labeling that avoids future information. Labels are generated from overbought/oversold thresholds with an added “do not trade” zone, enabling cleaner cross-validation and simpler decision boundaries.
Key limitations persist: oscillator selection and parameterization, poor behavior in trends, and instrument dependence. Adding profitability checks can smooth equity curves but reintroduces look-ahead.
Implementation details include Numba-accelerated indicator calculation, threshold-to-label mapping, optional profitability filtering, and ONNX export for deploymen...
👉 Read | Freelance | @mql5dev
547 192
Broker Session Schedule Inspector for MT5 reads the weekly trading-session schedule directly from the connected broker, without using predefined London, New York, or other global session templates.
The script can be run against the current chart symbol, a comma-separated custom list, or all visible Market Watch symbols. For each symbol it enumerates sessions returned by SymbolInfoSessionTrade, checks whether current server time is inside a scheduled window, and identifies the next open or close transition. Trade mode and synchronization status are also reported.
Midnight-crossing sessions are marked with (+1d). If the broker does not provide schedule data, the output returns SCHEDULE_UNAVAILABLE rather than generating fallback hours. Optional CSV snapshots with timestamps can be written to the terminal Common Files folder.
Inputs include symbol scope, custom...
👉 Read | AppStore | @mql5dev
547 192
Round Trip Cost Reconciler is a free, read-only MT5 utility that generates two CSV outputs for trade cost accounting. One file contains filtered deal records. The second aggregates buy/sell deals by DEAL_POSITION_ID to produce position-level round-trip figures.
Partial fills are consolidated into volume-weighted entry and exit prices. Commission, swap, and fee remain separated from gross trading result, enabling cleaner reconciliation of broker-recorded costs versus PnL.
Reports include deal/order/position identifiers, symbol, magic number, direction, entry type, timestamps, price/volume, broker profit and costs, total entry/exit volume, weighted prices, gross result, total costs, net result, deal count, and lifecycle status.
Lifecycle states: COMPLETE, OPEN_OR_INCOMPLETE, EXCESS_EXIT, and COMPLEX_REVERSAL (INOUT reversals are not simplified).
Setup: compile t...
👉 Read | Calendar | @mql5dev
547 192
Stop Geometry Visualizer for MT5 is a free, read-only indicator that renders broker Stops Level and Freeze Level as chart references.
It displays current Bid, Ask, spread, Stops/Freeze values in points and price distance, plus upper/lower geometry references for Buy Stop, Sell Stop, Buy Stop Loss, and Sell Stop Loss. Optional freeze reference lines can be enabled. It also reports tick size, volume min/step/max, and filling-mode flags.
A timer-based refresh is configurable via InpRefreshSeconds. Visibility of stop/freeze references and change logging is controlled by inputs, along with line color settings. When a broker reports zero Stops or Freeze, lines are omitted and the dashboard explicitly shows zero.
No orders are placed, modified, or deleted. Lines are diagnostic only; final validation should use the current broker state and OrderCheck.
👉 Read | Docs | @mql5dev
547 192
Trade Transaction Trace Logger is a read-only MT5 Expert Advisor designed to diagnose the lifecycle of orders, deals, and positions. It records OnTradeTransaction events in arrival order to a local CSV file and can optionally mirror a compact line to the Experts Journal.
Captured fields include a monotonic event sequence with server time, transaction type, symbol, resolved magic number, and order/deal/position tickets. It also logs order type and state, deal type, price, trigger, SL/TP, volume, plus request action and server retcode/comment. If an event lacks context, the core attempts resolution via request data, live orders, order history, deal history, or current positions.
Configuration covers symbol scope (chart or all), magic filtering (-1 or exact), CSV filename, Common Files storage, and Journal printing. The module sends no trade requests, uses no DLL/W...
👉 Read | AppStore | @mql5dev
547 192
Session Sweep Reversal Detector flags intraday reversals around completed session boundaries. It plots the finished session high/low as forward reference lines, then monitors post-session price action for a liquidity sweep.
A sweep requires price to breach the frozen high/low by more than a configurable buffer, then close back inside the range within a limited number of bars. Breaches that fail to reverse in time are treated as breakouts and ignored.
Signals are shown as arrows: bullish when the session low is swept and price closes back above it, bearish when the session high is swept and price closes back below it. Key inputs include session start/end hours, sweep buffer in pips, reversal bar limit, and the number of prior sessions displayed. Most relevant on M5–M30, commonly aligned to London or New York hours on major FX pairs.
👉 Read | VPS | @mql5dev
547 192
Broker Execution Diagnostics MT5 is a read-only script that reports symbol constraints commonly linked to invalid volume, invalid stops, and inconsistent risk calculations.
Output includes digits, point, tick size, tick value, current spread (points), min/max/step volume, and a conservative normalized volume for a requested size. It also reports stops and freeze levels in points and price distance, plus trade mode and execution mode values. Optional checks cover entry-to-Stop-Loss distance and an OrderCalcProfit estimate in account currency.
Inputs: InpRequestedVolume for normalization, optional InpEntryPrice and InpStopLossPrice for distance and P/L checks, plus InpShowOnChart to print the report on-chart.
Usage: compile in MetaEditor, attach to the target symbol, and read results in Experts log or chart comment. No orders are sent or modified. Sui...
👉 Read | Forum | @mql5dev
547 192
MetaTrader 5 positions are isolated, which makes basket-level risk control awkward when trades are correlated. The article solves this with CBasketManager: positions are grouped by a basket ID stored in POSITION_COMMENT using a simple “BASKET:ID” convention, enabling basket-wide P&L tracking and coordinated exits.
The design separates concerns cleanly: a scanner aggregates state into a single CBasketInfo snapshot (sum P&L, long/short volume, volume-weighted pips, distance to stop), an executor handles order sends and closes legs safely in reverse order, and a stop registry enforces a unified equity threshold via a callback so risk logic stays decoupled from execution.
Practical details target real brokers: filling mode is resolved from SYMBOL_FILLING_MODE to avoid common retcode failures, symbols like gold are configurable and selected early to ensure prope...
👉 Read | VPS | @mql5dev
547 192
SuperTrend is a volatility-band indicator rendered as a single line that flips sides by trend. It combines ATR with a ratchet that preserves prior band state, so each bar depends on the stored state of the previous bar.
Most “repainting” reports are state-management faults: closed bars changing due to broken recursion, series/normal indexing mismatches, or buffer history being reset. In MT5 this is amplified by call-based execution, so recursive state must persist across calls.
A robust approach uses calculation buffers (sUp, sDn, sTrend) instead of manually resized arrays, creates the ATR handle once in OnInit, and copies ATR data defensively. Live updates typically reprocess only the forming bar and the last closed bar.
Arrows should be delayed until reversals are no longer at risk of being invalidated by the next ticks.
👉 Read | CodeBase | @mql5dev
547 192
The project evolves from a basic FastAPI + Jinja2 MT5 process controller into a terminal manager that can surface live trading-account metrics in the UI. Hard-coded terminal paths are replaced by startup-selectable configuration, preparing the app for real deployments with many instances.
A new endpoint (/instances/{name}) returns per-terminal status as JSON, with request handlers organized into a dedicated controller class. The UI is refined using Bootstrap and jQuery, enabling simple periodic polling to refresh terminal data without manual page reloads.
Account and terminal characteristics are read via the MetaTrader5 Python library by connecting to a specific terminal executable (portable mode), using a short initialize() timeout to avoid blocking on disconnected terminals, then querying terminal_info(), account_info(), and last_error() before ...
👉 Read | VPS | @mql5dev
547 192
LightGTS tokenizes time series by FFT-based period patching, then applies flexible projection to handle variable-length cycles. Transformer Encoder blocks consume these tokens, and Periodical Parallel Decoding emits the forecast in one pass, with a resize stage preserving periodic consistency.
Rotary Positional Encoding replaces additive position vectors by rotating Q/K coordinate pairs. It is parameter-free, requires even embedding size, and improves relative shift handling under variable windowing.
An OpenCL RoPE implementation maps work-items over (D/2, tokens, variables), uses float2 pairs, precomputed sin/cos tables, and minimizes global reads. A backward kernel applies the inverse rotation to propagate gradients.
In MQL5, a CNeuronRoPE wrapper validates even dimensions, builds a cos/sin matrix once on CPU, and queues forward/backward kernels. Encoder...
👉 Read | VPS | @mql5dev
547 192
Bonobo Optimizer (BO) is a population-based optimization method published in 2021 by Amit Kumar Das and Dilip Kumar Pratihar. Each individual represents a candidate solution, with an alpha individual tracking the current best.
Core mechanics use fission-fusion subgroups and three update strategies: randomized mating toward alpha plus a subgroup partner (scab/scsb may exceed 1), low-probability extra-group mating using boundary extremes with heavy-tailed beta coefficients, and consortship mating with a direction flag based on relative fitness and exp(-rand) decay.
Selection applies a strict acceptance rule: always accept improvements, otherwise accept with small probability to retain diversity. Parameters adapt via positive/negative phases, shifting subgroup size, randomized mating rate, and extra-group probability.
A reference implementation (C_AO_B...
👉 Read | Quotes | @mql5dev
