Multi-EA MT5 accounts often fail due to unmanaged interaction between strategies, not a single defective EA. Independent sizing can stack correlated exposure, synchronize stop-outs, and bypass any real account-wide daily loss limit.
A proposed architecture shifts EAs to signal-only roles. Each EA sends trade intent (symbol, side, stop, strategy id) to a central MT5 Service, RiskGate, which enforces portfolio rules and returns approved/rejected, lot size, and a reason.
RiskGate runs as a TCP server inside an MQL5 Service. EAs use a client wrapper with JSON messages, timeouts, reconnection, and deterministic fallback (reject or fixed-lot). Risk logic is isolated in a single handler method, enabling consistent limits across all strategies.
π Read | VPS | @mql5dev
#MQL5 #MT5 #EA
A proposed architecture shifts EAs to signal-only roles. Each EA sends trade intent (symbol, side, stop, strategy id) to a central MT5 Service, RiskGate, which enforces portfolio rules and returns approved/rejected, lot size, and a reason.
RiskGate runs as a TCP server inside an MQL5 Service. EAs use a client wrapper with JSON messages, timeouts, reconnection, and deterministic fallback (reject or fixed-lot). Risk logic is isolated in a single handler method, enabling consistent limits across all strategies.
π Read | VPS | @mql5dev
#MQL5 #MT5 #EA
β€20β2π2β‘1
Forex analysis often overweights indicators and patterns while underusing economic constraints. A practical alternative is estimating fair exchange rates via purchasing power parity and using that as a benchmark against market pricing.
A Python system can implement relative PPP, supplemented by independent methods: international price-level comparisons, GDP-implied rates from IMF and World Bank series, inflation-adjusted baselines, and a standardized-goods proxy. Combining outputs via weighted averaging and dynamic reweighting improves robustness.
Key engineering issues include opaque commercial datasets, stale public releases, IMF SDMX-JSON parsing, country and currency code mapping, request chunking, retries, and fallback datasets to maintain continuity when APIs fail.
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #Forex
A Python system can implement relative PPP, supplemented by independent methods: international price-level comparisons, GDP-implied rates from IMF and World Bank series, inflation-adjusted baselines, and a standardized-goods proxy. Combining outputs via weighted averaging and dynamic reweighting improves robustness.
Key engineering issues include opaque commercial datasets, stale public releases, IMF SDMX-JSON parsing, country and currency code mapping, request chunking, retries, and fallback datasets to maintain continuity when APIs fail.
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #Forex
β€21π4
Part 2 turns βfractal confirmedβ into βfractal quantifiedβ for EURUSD 5βminute data using a repeatable MMAR calibration pipeline.
It extracts the scaling function tau(q) from partition-function slopes and uses its shape to separate monofractal (linear) behavior from true multifractality (concave). A three-part decision test scores concavity, deviation from linear fit, and slope variability, acting as a gate before spending compute on MMAR.
The Hurst exponent is estimated with bias-corrected, outlier-robust R/S analysis (with a tau(q) root-finding fallback), linking market memory to strategy selection and risk scaling.
tau(q) is then mapped to the multifractal spectrum f(alpha) via a Legendre transform, and the empirical spectrum is fit against lognormal, binomial, Poisson, and gamma cascade models to choose the best MMAR generator and parameters.
π Read | AppStore | @mql5dev
#MQL5 #MT5 #AlgoTrading
It extracts the scaling function tau(q) from partition-function slopes and uses its shape to separate monofractal (linear) behavior from true multifractality (concave). A three-part decision test scores concavity, deviation from linear fit, and slope variability, acting as a gate before spending compute on MMAR.
The Hurst exponent is estimated with bias-corrected, outlier-robust R/S analysis (with a tau(q) root-finding fallback), linking market memory to strategy selection and risk scaling.
tau(q) is then mapped to the multifractal spectrum f(alpha) via a Legendre transform, and the empirical spectrum is fit against lognormal, binomial, Poisson, and gamma cascade models to choose the best MMAR generator and parameters.
π Read | AppStore | @mql5dev
#MQL5 #MT5 #AlgoTrading
β€33π8
Inside Bar detection has been automated for traders who rely on price action breakouts. The indicator scans charts for Inside Bar structures and classifies the result as bullish, bearish, or neutral based on the small candleβs open/close relationship.
Once confirmed, it plots a projection rectangle from the mother candleβs high/low and extends it forward by a configurable number of bars. Optional labels are printed next to each zone, with controls to keep only the last N patterns to reduce chart load.
Alerting supports popup, sound, mobile push, and optional email. Visual settings include automatic direction-based colors or manual overrides, plus optional rectangle fill. Designed to run on any symbol and timeframe, with non-repainting signals fixed after bar close and processing optimized to recent/visible candles.
π Read | Freelance | @mql5dev
#MQL5 #MT5 #Indicator
Once confirmed, it plots a projection rectangle from the mother candleβs high/low and extends it forward by a configurable number of bars. Optional labels are printed next to each zone, with controls to keep only the last N patterns to reduce chart load.
Alerting supports popup, sound, mobile push, and optional email. Visual settings include automatic direction-based colors or manual overrides, plus optional rectangle fill. Designed to run on any symbol and timeframe, with non-repainting signals fixed after bar close and processing optimized to recent/visible candles.
π Read | Freelance | @mql5dev
#MQL5 #MT5 #Indicator
β€22π4π2π₯1
A momentum-based candle coloring method can improve visibility of market direction and price activity by classifying each bar into four states.
Bullish momentum is shown in green (0.0), bearish momentum in red (1.0), and weak or no momentum in gray (2.0). A separate state flags news impact via candle expansion in silver (3.0), helping isolate unusually large ranges from routine movement.
The default momentum period is 4, tuned to detect sharper momentum shifts with minimal lag. This setup is suitable for quick visual triage before validating signals with volume, volatility, and session context.
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #Indicator
Bullish momentum is shown in green (0.0), bearish momentum in red (1.0), and weak or no momentum in gray (2.0). A separate state flags news impact via candle expansion in silver (3.0), helping isolate unusually large ranges from routine movement.
The default momentum period is 4, tuned to detect sharper momentum shifts with minimal lag. This setup is suitable for quick visual triage before validating signals with volume, volatility, and session context.
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #Indicator
β€23β‘5π2
MetaEditor in MetaTrader 5 is closer to a full IDE than a code editor, built around an iterative workflow: debug logic, measure performance, then package and protect the final EX5. The article emphasizes replacing adβhoc Print logging with step-by-step debugging on real or historical ticks and hardware-level profiling to pinpoint bottlenecks.
A practical Bollinger Bands signal indicator is used to demonstrate disciplined rule handling: reversal vs breakout modes, single active trade until TP/SL, reversal on opposite close, and strict session filters (skip early hours, avoid the last hour, forced end-of-day close) with clear on-chart visualization.
Key engineering practices include organizing work as an MQPROJ project with centralized properties, clean compilation with zero warnings, reusable debug.tpl chart templates, and repeatable Debug/Profile ...
π Read | VPS | @mql5dev
#MQL5 #MT5 #AlgoTrading
A practical Bollinger Bands signal indicator is used to demonstrate disciplined rule handling: reversal vs breakout modes, single active trade until TP/SL, reversal on opposite close, and strict session filters (skip early hours, avoid the last hour, forced end-of-day close) with clear on-chart visualization.
Key engineering practices include organizing work as an MQPROJ project with centralized properties, clean compilation with zero warnings, reusable debug.tpl chart templates, and repeatable Debug/Profile ...
π Read | VPS | @mql5dev
#MQL5 #MT5 #AlgoTrading
β€21π4
Eagle Strategy (ES) is a two-phase metaheuristic for optimizing trading EA parameters when classic methods stall in local optima. It alternates wide exploration with targeted refinement to handle rugged fitness landscapes efficiently.
Global search uses LΓ©vy flights: mostly small moves with occasional long jumps, generated via Mantegnaβs method. A fast Gamma implementation (Lanczos approximation) keeps LΓ©vy sampling practical for iterative optimizers.
When a promising region is found, ES switches to local exploitation using a Firefly-style search inside a hypersphere around the current best. Attractiveness depends on solution quality and decays with distance, enabling controlled convergence without losing diversity.
An MQL5 class design ties it together: phase switching, stagnation detection, adaptive step sizing, boundary handling, and parameter knobs ...
π Read | Quotes | @mql5dev
#MQL5 #MT5 #AlgoTrading
Global search uses LΓ©vy flights: mostly small moves with occasional long jumps, generated via Mantegnaβs method. A fast Gamma implementation (Lanczos approximation) keeps LΓ©vy sampling practical for iterative optimizers.
When a promising region is found, ES switches to local exploitation using a Firefly-style search inside a hypersphere around the current best. Attractiveness depends on solution quality and decays with distance, enabling controlled convergence without losing diversity.
An MQL5 class design ties it together: phase switching, stagnation detection, adaptive step sizing, boundary handling, and parameter knobs ...
π Read | Quotes | @mql5dev
#MQL5 #MT5 #AlgoTrading
β€32π2π2
MQL5 Wizard workflow extends beyond entry signals; money management often decides whether a strategy survives forward walks. A volume-based sizing model was implemented using a Fenwick Tree (Binary Indexed Tree) to query cumulative OBV structure in O(log n), avoiding long moving-average windows and latency.
Four sizing modes were tested: Linear, Conservative (sqrt damping, 1.25x cap), Aggressive (downscale weak structure, up to 3.0x), and Mean-Reversion (invert ratio, up to 2.0x). Fenwick-only forward walk on EURUSD (H4) produced a net loss (-$773.82) and profit factor 0.39, largely due to reacting to exhaustion spikes.
Adding an on-chart 1D CNN inference gate (conv+ReLU+global average pooling+dense+sigmoid) reduced trade frequency and throttled exposure on chaotic volume shapes. In the same framework, the combined model turned the forward walk sl...
π Read | NeuroBook | @mql5dev
#MQL5 #MT5 #AlgoTrading
Four sizing modes were tested: Linear, Conservative (sqrt damping, 1.25x cap), Aggressive (downscale weak structure, up to 3.0x), and Mean-Reversion (invert ratio, up to 2.0x). Fenwick-only forward walk on EURUSD (H4) produced a net loss (-$773.82) and profit factor 0.39, largely due to reacting to exhaustion spikes.
Adding an on-chart 1D CNN inference gate (conv+ReLU+global average pooling+dense+sigmoid) reduced trade frequency and throttled exposure on chaotic volume shapes. In the same framework, the combined model turned the forward walk sl...
π Read | NeuroBook | @mql5dev
#MQL5 #MT5 #AlgoTrading
β€13π3π3
Financial ML pipelines leak information because labels overlap in time and regimes change, so classic train/validate/test splits overstate performance. This design blocks leakage with a strict 60/20/20 temporal partition: an outer-training zone for all iteration, an inner-validation checkpoint for accept/reject, and a final test opened exactly once via a programmatic gate.
Hyperparameters are chosen inside nested CV using PurgedWalkForwardCV (purging + embargo) and Mastersβ 1-SE rule, selecting the simplest configuration statistically tied with the best. The outer loop then estimates performance on folds the search never sees, supporting both walk-forward and CPCV, with careful index handling.
Probability calibration is done correctly using out-of-fold predictions generated after selection, fitting isotonic calibration only on predictions from models that never t...
π Read | AlgoBook | @mql5dev
#MQL5 #MT5 #AI
Hyperparameters are chosen inside nested CV using PurgedWalkForwardCV (purging + embargo) and Mastersβ 1-SE rule, selecting the simplest configuration statistically tied with the best. The outer loop then estimates performance on folds the search never sees, supporting both walk-forward and CPCV, with careful index handling.
Probability calibration is done correctly using out-of-fold predictions generated after selection, fitting isotonic calibration only on predictions from models that never t...
π Read | AlgoBook | @mql5dev
#MQL5 #MT5 #AI
β€35π9π1π1
A utility script can be used to display full trading account information in one place, including balances, equity, margin figures, account currency, leverage, and server identifiers. This helps reduce manual checks and supports faster validation during setup and support cases.
Operational guidance is required before deployment. If account information is restricted or unavailable for a client, the script may fail or return partial fields depending on permissions and broker settings.
Email handling should be defined explicitly. Decide whether the email is added as an input parameter, read from platform settings, or stored in an external config, and ensure no sensitive account data is sent without consent and audit logging.
π Read | Forum | @mql5dev
#MQL4 #MT4 #script
Operational guidance is required before deployment. If account information is restricted or unavailable for a client, the script may fail or return partial fields depending on permissions and broker settings.
Email handling should be defined explicitly. Decide whether the email is added as an input parameter, read from platform settings, or stored in an external config, and ensure no sensitive account data is sent without consent and audit logging.
π Read | Forum | @mql5dev
#MQL4 #MT4 #script
β€17π2π1
Retail momentum tools such as MACD and RSI are constrained by their moving-average design. Any averaging process requires past samples, which introduces persistent phase lag. By the time a reversal signal prints, faster execution systems have often already reduced exposure, leaving late liquidity to absorb the shift.
Some proprietary approaches model price as a kinematic series using discrete derivatives rather than smoothed oscillators. First derivative estimates provide velocity (dP/dt). Second derivative estimates provide acceleration (dV/dt), tracking how quickly velocity is changing.
A common exhaustion condition appears when acceleration turns negative while velocity remains positive. This configuration indicates weakening impulse before price direction changes. In automation, acceleration can be used as a gating filter to block breakout ent...
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #AlgoTrading
Some proprietary approaches model price as a kinematic series using discrete derivatives rather than smoothed oscillators. First derivative estimates provide velocity (dP/dt). Second derivative estimates provide acceleration (dV/dt), tracking how quickly velocity is changing.
A common exhaustion condition appears when acceleration turns negative while velocity remains positive. This configuration indicates weakening impulse before price direction changes. In automation, acceleration can be used as a gating filter to block breakout ent...
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #AlgoTrading
β€15π3π1π1
This article builds a real-time flag pattern detector for MetaTrader 5 that replaces visual guesswork with repeatable rules. It validates continuation flags using ATR-normalized pole strength, capped retracement, bounded consolidation length, and breakout confirmation, while rejecting weak or overlapping setups.
The MQL5 design is fully graphical: no indicator buffers, only chart objects. Once confirmed, it draws the pole, an adaptive slanted channel from internal highs/lows, a shaded consolidation box, breakout arrow, and labels, with optional alerts.
Efficiency comes from a two-phase OnCalculate flow: one-time historical scan, then incremental updates using prev_calculated, tracking forming patterns separately from already-drawn ones to keep charts clean and processing fast on lower timeframes.
π Read | NeuroBook | @mql5dev
#MQL5 #MT5 #Indicator
The MQL5 design is fully graphical: no indicator buffers, only chart objects. Once confirmed, it draws the pole, an adaptive slanted channel from internal highs/lows, a shaded consolidation box, breakout arrow, and labels, with optional alerts.
Efficiency comes from a two-phase OnCalculate flow: one-time historical scan, then incremental updates using prev_calculated, tracking forming patterns separately from already-drawn ones to keep charts clean and processing fast on lower timeframes.
π Read | NeuroBook | @mql5dev
#MQL5 #MT5 #Indicator
β€20π€©2β1π1π1
MMAR volatility forecasting pipeline applied to EURUSD 5-minute data moves from fitted multifractal parameters into a full compound process X(t)=B_H[theta(t)]. The build combines a multiplicative cascade for multifractal trading time and Davies-Harte FBM for long-memory increments, with interpolation used to evaluate FBM on the deformed time grid.
Forecasting uses 1,000 Monte Carlo runs, regenerating cascade and FBM each time, then aggregating horizon volatility with mean, dispersion, and confidence bounds. Cascade depth is selected as k=ceil(log2(forecast_length+1)) and output is truncated to the required horizon.
A baseline GARCH(1,1) is fit on identical training data via arch with rescale enabled. Multi-step comparison follows simulation-based forecasting (ugarchsim-style) to match MMARβs horizon statistic, then both are evaluated against realized ...
π Read | NeuroBook | @mql5dev
#MQL5 #MT5 #AlgoTrading
Forecasting uses 1,000 Monte Carlo runs, regenerating cascade and FBM each time, then aggregating horizon volatility with mean, dispersion, and confidence bounds. Cascade depth is selected as k=ceil(log2(forecast_length+1)) and output is truncated to the required horizon.
A baseline GARCH(1,1) is fit on identical training data via arch with rescale enabled. Multi-step comparison follows simulation-based forecasting (ugarchsim-style) to match MMARβs horizon statistic, then both are evaluated against realized ...
π Read | NeuroBook | @mql5dev
#MQL5 #MT5 #AlgoTrading
β€32π1
Manual multi-timeframe checks in Market Watch require repeated chart switching and subjective scoring. At scale, the workflow becomes slow and inconsistent, with missed alignment signals across symbols and timeframes.
CMultiTimeframeMatrix provides a deployable dashboard for MT5: a symbols x timeframes matrix with per-cell composite scoring (trend slope + momentum β volatility) scaled near [-100, +100]. Blue/red intensity reflects bullish/bearish bias, while the numeric score remains visible.
Delivered as a reusable .mqh module plus a thin host EA. Updates run on a timer with differential refresh, re-entrancy protection, performance warnings, and an βMβ hotkey to toggle visibility.
π Read | Freelance | @mql5dev
#MQL5 #MT5 #EA
CMultiTimeframeMatrix provides a deployable dashboard for MT5: a symbols x timeframes matrix with per-cell composite scoring (trend slope + momentum β volatility) scaled near [-100, +100]. Blue/red intensity reflects bullish/bearish bias, while the numeric score remains visible.
Delivered as a reusable .mqh module plus a thin host EA. Updates run on a timer with differential refresh, re-entrancy protection, performance warnings, and an βMβ hotkey to toggle visibility.
π Read | Freelance | @mql5dev
#MQL5 #MT5 #EA
β€29π10π1
Tool placement on MetaTrader 5 charts typically ends with limited cursor feedback and no fast inspection path for dense price action. Default crosshair behavior is fixed and lacks magnification and measurement support.
Part 32 adds a crosshair manager for MQL5 sidebars: layered reticle ticks, full-width/height lines, and axis labels that report exact time and price. A circular magnifier renders zoomed candles, wicks, bid/ask lines, and a local price label without changing chart zoom.
Double-click enables measure mode with an anchor, diagonal connector (Bresenham), and live stats for bars, pips, and raw price delta. The system uses eleven new canvases, hides on sidebar hover, and refreshes cleanly on theme and tool changes.
π Read | NeuroBook | @mql5dev
#MQL5 #MT5 #AlgoTrading
Part 32 adds a crosshair manager for MQL5 sidebars: layered reticle ticks, full-width/height lines, and axis labels that report exact time and price. A circular magnifier renders zoomed candles, wicks, bid/ask lines, and a local price label without changing chart zoom.
Double-click enables measure mode with an anchor, diagonal connector (Bresenham), and live stats for bars, pips, and raw price delta. The system uses eleven new canvases, hides on sidebar hover, and refreshes cleanly on theme and tool changes.
π Read | NeuroBook | @mql5dev
#MQL5 #MT5 #AlgoTrading
β€21π¨βπ»4β1π1
MetaTrader 5 custom symbols shift charts from broker-defined timeframes and quote feeds to locally managed market data. A custom symbol is a terminal object with its own tick history, contract specification, and Strategy Tester support, stored under the terminalβs Custom base directory and separated in Market Watch.
Core MQL5 APIs cover lifecycle (CustomSymbolCreate/Delete, SymbolSelect), history writes (CustomTicksAdd/Replace, CustomRatesUpdate), and contract properties (CustomSymbolSet*). Limitations include no MQL5 Cloud optimization, dependency on cross rates for margin/profit, and fixed symbol properties during a test run.
Typical uses include time-independent bars (Renko, Range, Equal-Volume) built via tick aggregation and written with CustomRatesUpdate plus tick emulation, and synthetic instruments (spreads, baskets) requiring tick synchroni...
π Read | AlgoBook | @mql5dev
#MQL5 #MT5 #AlgoTrading
Core MQL5 APIs cover lifecycle (CustomSymbolCreate/Delete, SymbolSelect), history writes (CustomTicksAdd/Replace, CustomRatesUpdate), and contract properties (CustomSymbolSet*). Limitations include no MQL5 Cloud optimization, dependency on cross rates for margin/profit, and fixed symbol properties during a test run.
Typical uses include time-independent bars (Renko, Range, Equal-Volume) built via tick aggregation and written with CustomRatesUpdate plus tick emulation, and synthetic instruments (spreads, baskets) requiring tick synchroni...
π Read | AlgoBook | @mql5dev
#MQL5 #MT5 #AlgoTrading
β€35π3π1
John Ehlers documented the Hilbert Oscillator in Rocket Science For Traders (pp. 90β91). The indicator is commonly used to flag major turning points by analyzing the relationship between two plotted lines.
A typical interpretation is trend confirmation on crossovers: when the blue line crosses above the red line, an uptrend bias is indicated; the reverse crossover signals a potential downtrend bias.
The MetaTrader 5 implementation adds zero-line color states for immediate signals. A green state above the zero line is treated as a buy condition, while a red state below the zero line is treated as a sell condition.
The MetaTrader 4 variant is not included. Source code and the download are distributed via a Telegram channel referenced in the profile.
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #Indicator
A typical interpretation is trend confirmation on crossovers: when the blue line crosses above the red line, an uptrend bias is indicated; the reverse crossover signals a potential downtrend bias.
The MetaTrader 5 implementation adds zero-line color states for immediate signals. A green state above the zero line is treated as a buy condition, while a red state below the zero line is treated as a sell condition.
The MetaTrader 4 variant is not included. Source code and the download are distributed via a Telegram channel referenced in the profile.
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #Indicator
β€31π4π3
MetaTrader 5 optimizations often mislead by rewarding a single best pass. A sharp peak in Profit Factor or Sharpe can be pure curve-fit; robust systems show a plateau where nearby parameter values stay acceptable. The goal shifts from βbest numberβ to understanding the full optimization surface: sensitivity, degradation rate, and stable zones.
Optimization Frames turn the tester into a telemetry pipeline. Each pass can send custom metrics from OnTester via FrameAdd, then be parsed in OnTesterPass or reliably reprocessed in OnTesterDeinit, even with delayed batches from distributed agents.
A simple, event-driven EA (EMA crossover gated by RSI mode-change events, ATR-based SL/TP) keeps the surface interpretable. Frames log internal quality metrics like trigger-to-trade conversion and profit per signal, then export to CSV for Python analysis (pivot ta...
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #AlgoTrading
Optimization Frames turn the tester into a telemetry pipeline. Each pass can send custom metrics from OnTester via FrameAdd, then be parsed in OnTesterPass or reliably reprocessed in OnTesterDeinit, even with delayed batches from distributed agents.
A simple, event-driven EA (EMA crossover gated by RSI mode-change events, ATR-based SL/TP) keeps the surface interpretable. Frames log internal quality metrics like trigger-to-trade conversion and profit per signal, then export to CSV for Python analysis (pivot ta...
π Read | CodeBase | @mql5dev
#MQL5 #MT5 #AlgoTrading
β€38π11β‘3π3π€¨3
A moving average bands width metric can be used to monitor volatility conditions. The indicator focuses on band width rather than price direction, treating contraction and expansion as volatility signals.
This implementation adds one visual change: periods when band width reaches extreme lows are highlighted in red. These low-width zones can flag unusually compressed conditions, where volatility expansion may follow.
Practical use is non-directional. It can support trade context by identifying congestion, then monitoring for potential trend change after compression, or trend continuation when a range resolves into a directional move.
π Read | Calendar | @mql5dev
#MQL5 #MT5 #Indicator
This implementation adds one visual change: periods when band width reaches extreme lows are highlighted in red. These low-width zones can flag unusually compressed conditions, where volatility expansion may follow.
Practical use is non-directional. It can support trade context by identifying congestion, then monitoring for potential trend change after compression, or trend continuation when a range resolves into a directional move.
π Read | Calendar | @mql5dev
#MQL5 #MT5 #Indicator
β€29π2
DoEasy library tick support moved from single tick objects to per-symbol tick series lists, with default retention set to the current day and an option to store multiple days. Lists are intended for faster search, comparison, and repeated access than ad-hoc CopyTicks calls.
Core updates include new library messages, a retention-days constant, and a fix in the timeseries code path to delete bar objects when insertion fails to prevent leaks. Select.mqh gained tick-oriented search/sort helpers and overloads to fetch ticks by index, time, or millisecond timestamp.
A new tick series class builds an array-backed list of tick objects, loads history via CopyTicksRange() from the computed day boundary, and supports queries such as highest Ask and lowest Bid. Next step is a multi-symbol tick collection with real-time list updates.
π Read | Docs | @mql5dev
#MQL5 #MT5 #AlgoTrading
Core updates include new library messages, a retention-days constant, and a fix in the timeseries code path to delete bar objects when insertion fails to prevent leaks. Select.mqh gained tick-oriented search/sort helpers and overloads to fetch ticks by index, time, or millisecond timestamp.
A new tick series class builds an array-backed list of tick objects, loads history via CopyTicksRange() from the computed day boundary, and supports queries such as highest Ask and lowest Bid. Next step is a multi-symbol tick collection with real-time list updates.
π Read | Docs | @mql5dev
#MQL5 #MT5 #AlgoTrading
β€39π4π2π2
An updated Moving Average Bands variant has been published with clearer, signal-oriented behavior. The extension adds a practical ruleset that derives trade signals directly from band values, making the use case more explicit than the earlier release.
The recommended workflow uses band color changes as an actionable state indicator. These transitions can be mapped to initial entries, re-entries after pullbacks, and early exit candidates when conditions reverse.
This approach keeps the logic on-chart and reduces reliance on external filters, while remaining transparent enough to audit and adjust for different instruments and timeframes.
π Read | Freelance | @mql5dev
#MQL5 #MT5 #Indicator
The recommended workflow uses band color changes as an actionable state indicator. These transitions can be mapped to initial entries, re-entries after pullbacks, and early exit candidates when conditions reverse.
This approach keeps the logic on-chart and reduces reliance on external filters, while remaining transparent enough to audit and adjust for different instruments and timeframes.
π Read | Freelance | @mql5dev
#MQL5 #MT5 #Indicator
β€65π13π5π€2