CPPI in MetaTrader 5 is a position sizing rule, not a buy/sell signal. It maps current equity to a floor, a cushion, and a multiplier-based target exposure, then scales a long position up or down without forecasts or indicators.
MT5 changes two assumptions. The “safe” leg is just being flat, with no bond yield compounding the floor. Rebalancing is discrete per tick and typically gated by a rebalance band to reduce spread cost.
Implementation is split into stateless math (four formulas), a trading engine that handles lot rounding, netting vs hedging reduction, and cash-lock behavior, plus an indicator that runs a price-only simulation and cannot reproduce real equity history.
Key risks remain: gap breaches versus 1/m, cash-lock persistence, and minimum lot constraints on small accounts.
👉 Read | CodeBase | @mql5dev
MT5 changes two assumptions. The “safe” leg is just being flat, with no bond yield compounding the floor. Rebalancing is discrete per tick and typically gated by a rebalance band to reduce spread cost.
Implementation is split into stateless math (four formulas), a trading engine that handles lot rounding, netting vs hedging reduction, and cash-lock behavior, plus an indicator that runs a price-only simulation and cannot reproduce real equity history.
Key risks remain: gap breaches versus 1/m, cash-lock persistence, and minimum lot constraints on small accounts.
👉 Read | CodeBase | @mql5dev
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Manual PDF edits do not scale. Any byte shift breaks /Length, xref offsets, and startxref. Viewers may repair, render blank, or refuse the file, since the format does not validate those numbers.
The core rule is simple: file-describing numbers must be derived from the bytes already written, never maintained as literals. Current position equals buffer Length(); stream size equals content buffer Length().
CPdfBuffer owns a growable uchar array with doubling capacity, cheap reuse via Clear(), ASCII token output, PDF-safe number formatting, and fixed-width xref entry padding. Save writes only used length to avoid trailing zeros.
CPdfWriter allocates object numbers, records each object offset from buffer Length() at BeginObject(), supports forward references, and emits xref from observed offsets. Finish fails if allocated objects were never written or if nesting is ...
👉 Read | Calendar | @mql5dev
The core rule is simple: file-describing numbers must be derived from the bytes already written, never maintained as literals. Current position equals buffer Length(); stream size equals content buffer Length().
CPdfBuffer owns a growable uchar array with doubling capacity, cheap reuse via Clear(), ASCII token output, PDF-safe number formatting, and fixed-width xref entry padding. Save writes only used length to avoid trailing zeros.
CPdfWriter allocates object numbers, records each object offset from buffer Length() at BeginObject(), supports forward references, and emits xref from observed offsets. Finish fails if allocated objects were never written or if nesting is ...
👉 Read | Calendar | @mql5dev
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Candlesticks show price movement, but not where volume accumulated. A volume-at-price profile solves that by producing reproducible levels: point of control, value area bounds, and volume split above/below current price.
An MQL5 indicator can approximate volume distribution per bar using tick or real volume, with two allocation policies: spread volume across the bar range or concentrate it at the close with a neighbor split. A rolling window is binned into horizontal price levels, then POC and value area are computed and published to six buffers for EAs and alerts.
Visualization includes a heatmap behind candles plus a live side profile with tagged levels. Performance is handled via ring-buffer column storage, cached base-layer rendering, alpha blending, and selective redraw on viewport changes.
👉 Read | CodeBase | @mql5dev
An MQL5 indicator can approximate volume distribution per bar using tick or real volume, with two allocation policies: spread volume across the bar range or concentrate it at the close with a neighbor split. A rolling window is binned into horizontal price levels, then POC and value area are computed and published to six buffers for EAs and alerts.
Visualization includes a heatmap behind candles plus a live side profile with tagged levels. Performance is handled via ring-buffer column storage, cached base-layer rendering, alpha blending, and selective redraw on viewport changes.
👉 Read | CodeBase | @mql5dev
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This part upgrades an MT5 news filter from “all High events are equal” to a tiered, rule-driven system that handles releases with longer market impact, like rate decisions plus statements and press conferences.
Events are classified once through a shared function used by both the live economic calendar and the Strategy Tester CSV, removing duplicated logic and keeping backtests aligned with live trading.
A new ordered tier scale preserves the calendar’s levels and adds a Special tier above High. Each event now carries its own before/after window, so Special events can pause trading longer without widening every High release.
Special handling is defined as data: a rule table (optionally overridden via CSV) matches events by currency plus name/code (substring or exact), can promote/demote tiers, and can override windows. A companion script prints the broker’...
👉 Read | Signals | @mql5dev
Events are classified once through a shared function used by both the live economic calendar and the Strategy Tester CSV, removing duplicated logic and keeping backtests aligned with live trading.
A new ordered tier scale preserves the calendar’s levels and adds a Special tier above High. Each event now carries its own before/after window, so Special events can pause trading longer without widening every High release.
Special handling is defined as data: a rule table (optionally overridden via CSV) matches events by currency plus name/code (substring or exact), can promote/demote tiers, and can override windows. A companion script prints the broker’...
👉 Read | Signals | @mql5dev
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Building an MEXC Futures integration in MQL5 starts with a reusable REST layer: configure MetaTrader 5 to allow WebRequest() calls to https://api.mexc.com, then centralize GET request execution, HTTP handling, JSON deserialization, and validation of the common success/code/message fields.
JSON parsing is based on the CJAVal library, extended to make type conversion safe. The key improvement is overloads that validate JSON types before assigning outputs, preventing “missing field becomes 0” bugs. Numeric handling also avoids silent precision loss by only converting integers to double when they are exactly representable.
With these components, public endpoints can be added incrementally by writing only endpoint-specific parsing. The first example uses /api/v1/contract/ping to fetch server time (ms Unix), useful for clock alignment and time-sensitive trad...
👉 Read | Calendar | @mql5dev
JSON parsing is based on the CJAVal library, extended to make type conversion safe. The key improvement is overloads that validate JSON types before assigning outputs, preventing “missing field becomes 0” bugs. Numeric handling also avoids silent precision loss by only converting integers to double when they are exactly representable.
With these components, public endpoints can be added incrementally by writing only endpoint-specific parsing. The first example uses /api/v1/contract/ping to fetch server time (ms Unix), useful for clock alignment and time-sensitive trad...
👉 Read | Calendar | @mql5dev
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MetaTrader 5 can calculate many indicators internally via Technical Indicator Functions, so custom indicator code often only needs handle setup and CopyBuffer into an output buffer.
A minimal iMA-based indicator can match the platform MA, while still allowing runtime changes to color, line style, thickness, and applied price through standard indicator inputs.
CopyBuffer parameters matter. By limiting the copied range, the MA can be rendered only for the last N bars, producing a rolling segment tied to the MA period.
To avoid recompiles, MA period/type/price should be exposed as input parameters with clear labels. A common visual glitch comes from uninitialized or stale buffer values when copying partial ranges; buffer management is required to prevent artifacts.
👉 Read | VPS | @mql5dev
A minimal iMA-based indicator can match the platform MA, while still allowing runtime changes to color, line style, thickness, and applied price through standard indicator inputs.
CopyBuffer parameters matter. By limiting the copied range, the MA can be rendered only for the last N bars, producing a rolling segment tied to the MA period.
To avoid recompiles, MA period/type/price should be exposed as input parameters with clear labels. A common visual glitch comes from uninitialized or stale buffer values when copying partial ranges; buffer management is required to prevent artifacts.
👉 Read | VPS | @mql5dev
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Single-neuron models still hit hard limits: some simple-looking patterns (like XOR) cannot be learned without changing the architecture. The article reframes a neuron as linear regression and focuses on why scaling inputs and training loops quickly raises runtime and resource use, especially when code must be rewritten for every new parameter.
It then derives gradient descent from the least-squares error, showing how separate partial updates handle weight and bias. A MetaTrader 5 implementation trains a 1-in/1-out neuron with both linear regression and gradient descent and compares results: regression converges faster, while gradient descent can yield a slightly better weight estimate, with error behavior differing by method.
Practical takeaway for algo trading code: optimization is workload-dependent; choose the training approach based on data shape and performa...
👉 Read | NeuroBook | @mql5dev
It then derives gradient descent from the least-squares error, showing how separate partial updates handle weight and bias. A MetaTrader 5 implementation trains a 1-in/1-out neuron with both linear regression and gradient descent and compares results: regression converges faster, while gradient descent can yield a slightly better weight estimate, with error behavior differing by method.
Practical takeaway for algo trading code: optimization is workload-dependent; choose the training approach based on data shape and performa...
👉 Read | NeuroBook | @mql5dev
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A GPL-3.0 MT4 port of the “Chandelier Exit” indicator, kept line-by-line with the original logic and default inputs (ATR Period 22, Multiplier 3.0, extremums from Close enabled). ATR is computed as multiplier × ATR(length) using Wilder RMA seeded by an SMA.
Long stop is highest(close/high, length) minus ATR and only ratchets upward while the prior close remains above the prior stop. Short stop is lowest(close/low, length) plus ATR and only ratchets downward while the prior close remains below the prior stop. Direction flips to long when price closes above the previous short stop, and to short when it closes below the previous long stop; otherwise state is preserved.
MT4 additions include a signal statistics panel with spread/commission-aware figures, optional session filter with shading and end-of-session close, tooltipped trade marks, alerts, and EA...
👉 Read | Calendar | @mql5dev
Long stop is highest(close/high, length) minus ATR and only ratchets upward while the prior close remains above the prior stop. Short stop is lowest(close/low, length) plus ATR and only ratchets downward while the prior close remains below the prior stop. Direction flips to long when price closes above the previous short stop, and to short when it closes below the previous long stop; otherwise state is preserved.
MT4 additions include a signal statistics panel with spread/commission-aware figures, optional session filter with shading and end-of-session close, tooltipped trade marks, alerts, and EA...
👉 Read | Calendar | @mql5dev
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A Trade Replay Tool for MetaTrader 5 is outlined as an MQL5 indicator that combines candle-by-candle playback with automatic reconstruction of historical trades.
Key additions over a basic bar replay include adjustable playback speed, anchor-based range selection (single or dual anchor), and trade synchronization. Historical deals within the selected interval are retrieved and converted into replay records preserving entry/exit time, direction, price, volume, SL, and TP.
The workflow covers initialization (buffers, UI, timer), event-driven control via OnChartEvent(), interactive anchor movement, deal extraction from account history, progressive candle reveal, and paper-position lifecycle management. Playback uses UI controls and hotkeys (Ctrl +/- for speed, Shift+E for dual-anchor mode), then restores the chart state when replay is disabled.
👉 Read | Docs | @mql5dev
Key additions over a basic bar replay include adjustable playback speed, anchor-based range selection (single or dual anchor), and trade synchronization. Historical deals within the selected interval are retrieved and converted into replay records preserving entry/exit time, direction, price, volume, SL, and TP.
The workflow covers initialization (buffers, UI, timer), event-driven control via OnChartEvent(), interactive anchor movement, deal extraction from account history, progressive candle reveal, and paper-position lifecycle management. Playback uses UI controls and hotkeys (Ctrl +/- for speed, Shift+E for dual-anchor mode), then restores the chart state when replay is disabled.
👉 Read | Docs | @mql5dev
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An MT4 line-by-line port of the TradingView “Range Filter Buy and Sell 5min” (open-source). Core logic matches the original: Smoothed range = EMA(EMA(|close − close[1]|, period), 2×period−1) × multiplier, with EMA seeding via SMA consistent with ta.ema.
The range filter remains fixed until price exceeds it by more than the smoothed range, then steps to maintain that distance. Direction counters drive long/short conditions, with Buy/Sell printed once per side change using the original CondIni behavior. Target bands are filter ± range, with original-style bar coloring.
MT4 additions include a signal statistics panel (trades, win rate, net after spread/commission, profit factor, losing streak, drawdown, cost per trade), optional session filter with shading and end-of-session close, tooltipped trade marks, alerts, and iCustom buffers (5 Buy, 6 Sell, 11 f...
👉 Read | VPS | @mql5dev
The range filter remains fixed until price exceeds it by more than the smoothed range, then steps to maintain that distance. Direction counters drive long/short conditions, with Buy/Sell printed once per side change using the original CondIni behavior. Target bands are filter ± range, with original-style bar coloring.
MT4 additions include a signal statistics panel (trades, win rate, net after spread/commission, profit factor, losing streak, drawdown, cost per trade), optional session filter with shading and end-of-session close, tooltipped trade marks, alerts, and iCustom buffers (5 Buy, 6 Sell, 11 f...
👉 Read | VPS | @mql5dev
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MetaTrader 5 indicators fall into two groups: built-ins callable directly from MQL5, and custom indicators used to encode a specific market rule set.
A common requirement is bundling multiple moving averages into one indicator so they can be added and removed as a unit, without templates.
A naive implementation scales poorly: repeated input blocks, per-MA handle/buffer declarations, duplicated init/release code, and manual changes to plot/buffer counts that risk chart glitches.
Refactoring focuses on compiler-assisted structure: consolidate repeated calls, move fixed MA parameters into const structure instances, and use const arrays of structs. In MQL5, const applies to the declared instance, not the struct type, and struct initializer order must match member order to avoid silent misconfiguration.
👉 Read | Quotes | @mql5dev
A common requirement is bundling multiple moving averages into one indicator so they can be added and removed as a unit, without templates.
A naive implementation scales poorly: repeated input blocks, per-MA handle/buffer declarations, duplicated init/release code, and manual changes to plot/buffer counts that risk chart glitches.
Refactoring focuses on compiler-assisted structure: consolidate repeated calls, move fixed MA parameters into const structure instances, and use const arrays of structs. In MQL5, const applies to the declared instance, not the struct type, and struct initializer order must match member order to avoid silent misconfiguration.
👉 Read | Quotes | @mql5dev
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A line-by-line MT4 port of QuantNomad’s “UT Bot Alerts” (Pine v4, 2020), preserving the original behavior from HPotter and Yo_adriiiiaan. ATR matches Pine’s atr(c): Wilder RMA seeded with an SMA, without using the built-in iATR.
Trailing stop follows the original recursive update: it ratchets upward while price remains above the stop, ratchets downward while below, and resets to price ± Key Value × ATR on a cross. Buy triggers when the source crosses above the stop; Sell triggers on the inverse. Bar coloring stays consistent: green above, red below. Optional Heikin Ashi source uses HA close = (O+H+L+C)/4. Defaults: Key Value 1, ATR Period 10, HA off.
MT4 additions include a plotted trailing-stop line, an on-chart signal statistics panel, trade markers for counted trades, and alerts on new signals. Trades execute on the bar after a signal, reverse on ...
👉 Read | Freelance | @mql5dev
Trailing stop follows the original recursive update: it ratchets upward while price remains above the stop, ratchets downward while below, and resets to price ± Key Value × ATR on a cross. Buy triggers when the source crosses above the stop; Sell triggers on the inverse. Bar coloring stays consistent: green above, red below. Optional Heikin Ashi source uses HA close = (O+H+L+C)/4. Defaults: Key Value 1, ATR Period 10, HA off.
MT4 additions include a plotted trailing-stop line, an on-chart signal statistics panel, trade markers for counted trades, and alerts on new signals. Trades execute on the bar after a signal, reverse on ...
👉 Read | Freelance | @mql5dev
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Fixed-weight neural nets often look solid in backtests but fade in live trading once regimes shift. The article proposes tracking degradation with concrete metrics (Hit Rate, Network Health, long/short bias, 10-bar precision) so performance loss is detected early, not blamed on tester noise.
Instead of periodic retraining, it uses continuous online adaptation: a 100x100 toroidal cellular automaton where each of 10,000 “weights” is an agent updated every bar from 50 normalized features plus neighbor influence and evolution rules. Losing cells switch strategies or get reinitialized, while profitable cells gain voting authority.
A separate 10-bar binary predictor maintains a confusion matrix and cross-checks direction before a lightweight grid EA translates confidence into step sizing, reversals, and exits. The key gain is observable, real-time adapt...
👉 Read | CodeBase | @mql5dev
Instead of periodic retraining, it uses continuous online adaptation: a 100x100 toroidal cellular automaton where each of 10,000 “weights” is an agent updated every bar from 50 normalized features plus neighbor influence and evolution rules. Losing cells switch strategies or get reinitialized, while profitable cells gain voting authority.
A separate 10-bar binary predictor maintains a confusion matrix and cross-checks direction before a lightweight grid EA translates confidence into step sizing, reversals, and exits. The key gain is observable, real-time adapt...
👉 Read | CodeBase | @mql5dev
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AlgoFX is a trend-following indicator for MetaTrader 5 focused on identifying pullback zones within an established trend. It was built with XAUUSD in mind, but can be applied to any symbol and timeframe. It does not output entries, stops, or targets; it only marks areas of interest and leaves execution to the user.
Trend state is derived from EMA 50 and EMA 200. Uptrend requires EMA 50 above EMA 200 with EMA 200 rising; downtrend requires the opposite with EMA 200 falling. Otherwise the panel reports no clear trend. Zones are ATR-depth pullbacks around EMA 50 with candle-close confirmation, optionally filtered by RSI and spaced via a cooldown.
Zones are calculated on closed candles only, so historical marks match live behavior. An on-chart risk panel shows trend, balance or equity, risk per trade, ATR-based lot sizing with tick value and broker const...
👉 Read | AppStore | @mql5dev
Trend state is derived from EMA 50 and EMA 200. Uptrend requires EMA 50 above EMA 200 with EMA 200 rising; downtrend requires the opposite with EMA 200 falling. Otherwise the panel reports no clear trend. Zones are ATR-depth pullbacks around EMA 50 with candle-close confirmation, optionally filtered by RSI and spaced via a cooldown.
Zones are calculated on closed candles only, so historical marks match live behavior. An on-chart risk panel shows trend, balance or equity, risk per trade, ATR-based lot sizing with tick value and broker const...
👉 Read | AppStore | @mql5dev
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Session indicators that require broker server time tend to break on DST changes and when switching brokers. This session tool defines Asia, London, and New York in their local market times, then converts to broker server time automatically, including the mismatched UK vs US DST transition weeks. An optional overlap marks when London and New York are both open.
Sessions are drawn as high/low boxes or full-height shading, with the overlap as a dashed outline. A top-right panel reports the current state (“NOW”), highlights active sessions in green, and shows countdowns to the next open or close. Box hover reveals exact server-time start and end.
Configuration includes server time mode (auto, NY-close model, or manual UTC offset), display controls (history, styles, labels, colors, max timeframe), and per-session toggles, times, and colors. Strategy Teste...
👉 Read | Forum | @mql5dev
Sessions are drawn as high/low boxes or full-height shading, with the overlap as a dashed outline. A top-right panel reports the current state (“NOW”), highlights active sessions in green, and shows countdowns to the next open or close. Box hover reveals exact server-time start and end.
Configuration includes server time mode (auto, NY-close model, or manual UTC offset), display controls (history, styles, labels, colors, max timeframe), and per-session toggles, times, and colors. Strategy Teste...
👉 Read | Forum | @mql5dev
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Pending Panel is a chart-based execution EA for MT5 focused on fast placement of pending orders: Buy Limit, Sell Limit, Buy Stop, and Sell Stop. Order volume and entry distance are adjusted from on-chart controls, avoiding parameter edits and recompiles. Optional SL/TP can be attached at placement.
The EA supports OCO pairing, cancelling the opposing order when one triggers, plus bulk removal of all pending orders created by the tool. A live on-panel list shows current pending orders with type, volume, price, and SL/TP. Implementation is dependency-free, using only the standard library.
Broker constraints are handled via automatic detection of STOPS_LEVEL and filling mode, but behaviour should be validated on a demo due to broker-specific FREEZE_LEVEL rules and execution differences. The tool does not generate signals and manages only orders with its own m...
👉 Read | AlgoBook | @mql5dev
The EA supports OCO pairing, cancelling the opposing order when one triggers, plus bulk removal of all pending orders created by the tool. A live on-panel list shows current pending orders with type, volume, price, and SL/TP. Implementation is dependency-free, using only the standard library.
Broker constraints are handled via automatic detection of STOPS_LEVEL and filling mode, but behaviour should be validated on a demo due to broker-specific FREEZE_LEVEL rules and execution differences. The tool does not generate signals and manages only orders with its own m...
👉 Read | AlgoBook | @mql5dev
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Garch.mqh implements maximum-likelihood estimation for GARCH-family volatility models on return series and produces multi-step variance forecasts. Output includes parameter estimates with classic and Bollerslev-Wooldridge robust standard errors, log-likelihood with AIC/BIC, per-period conditional variance, persistence, and shock half-life. No DLL is required; covariances use the MQL5 matrix type.
Supported specifications cover zero or constant mean, and variance models GARCH(1,1), GJR-GARCH(1,1,1), and EGARCH(1,1,1). Innovations can be Normal, standardized Student t, or GED with estimated shape. Initialization uses an EW variance from the first 75 residuals and variance bounds aligned to EWMA, matching common reference behavior for identical parameters.
Optimization is staged: unconstrained BFGS on a free parametrization, bounded Nelder-Mead, then bound...
👉 Read | Freelance | @mql5dev
Supported specifications cover zero or constant mean, and variance models GARCH(1,1), GJR-GARCH(1,1,1), and EGARCH(1,1,1). Innovations can be Normal, standardized Student t, or GED with estimated shape. Initialization uses an EW variance from the first 75 residuals and variance bounds aligned to EWMA, matching common reference behavior for identical parameters.
Optimization is staged: unconstrained BFGS on a free parametrization, bounded Nelder-Mead, then bound...
👉 Read | Freelance | @mql5dev
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A chart indicator quantifies two recurring outcomes for each new bar: whether price trades above the prior high and whether it trades below the prior low. It scans the visible history, groups cases by the prior candle direction (bullish vs bearish), and computes how far beyond the previous high/low price typically extends.
On the active bar it renders up to five levels above and five below, starting at the prior high/low. Each level shows a 0–100% track plus a filled segment and printed percentage, based on the share of comparable historical bars that reached that distance. Level spacing defaults to 0.5x ATR(14) from closed bars, or can be set as percent-of-price; levels remain stable while the current candle forms.
Probabilities are recomputed on every bar so older, unreached levels decay naturally. A panel reports favored-side hit rate over all bar...
👉 Read | Calendar | @mql5dev
On the active bar it renders up to five levels above and five below, starting at the prior high/low. Each level shows a 0–100% track plus a filled segment and printed percentage, based on the share of comparable historical bars that reached that distance. Level spacing defaults to 0.5x ATR(14) from closed bars, or can be set as percent-of-price; levels remain stable while the current candle forms.
Probabilities are recomputed on every bar so older, unreached levels decay naturally. A panel reports favored-side hit rate over all bar...
👉 Read | Calendar | @mql5dev
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VpsToolkit (VpsToolkit.mqh) is a lightweight include for EAs running 24/7 on an MQL5 VPS or a local PC. It adds no trading logic and is used by calling only the needed functions. A demo EA shows integration and focuses on production issues: concurrent runs on VPS and PC, duplicate orders after timeouts, restarts resetting state, trades closed while the EA was offline, and VPS-only logs.
Core functions include run-location gating (VT_ActiveHere), trading permission diagnostics (VT_CanTrade), and safer market execution (VT_OpenMarket returning OK/FAIL/UNKNOWN and verifying results after timeouts). It also provides restart-safe initialization (VT_Init/VT_Ready), history-based daily stats (VT_TradesToday), detection of positions closed while offline (VT_ClosedWhileOff), restart counters and announcement throttling, and append-only UTF-8 CSV logging with daily counter...
👉 Read | AppStore | @mql5dev
Core functions include run-location gating (VT_ActiveHere), trading permission diagnostics (VT_CanTrade), and safer market execution (VT_OpenMarket returning OK/FAIL/UNKNOWN and verifying results after timeouts). It also provides restart-safe initialization (VT_Init/VT_Ready), history-based daily stats (VT_TradesToday), detection of positions closed while offline (VT_ClosedWhileOff), restart counters and announcement throttling, and append-only UTF-8 CSV logging with daily counter...
👉 Read | AppStore | @mql5dev
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An ICT-style dealing range indicator calculates the current leg from confirmed swing points and plots premium/discount structure with non-repainting logic. The range starts at the older of the last confirmed swing high/low, then expands as new highs or lows print until a new confirmed swing resets it. Swings require N candles on both sides (default 10), confirmed only after right-side closes.
Rendered levels include equilibrium (50%), premium and discount zones, plus OTE as the 62%–79% band with a 70.5% line. Direction is classified as up leg when the low precedes the high, otherwise down leg, placing OTE in the expected zone per ICT conventions. Optional retracements and standard deviation projections are supported.
IPDA reference ranges (20/40/60 completed trading days) are plotted with merged labels for equal levels. Alerts fire on candle close fo...
👉 Read | Quotes | @mql5dev
Rendered levels include equilibrium (50%), premium and discount zones, plus OTE as the 62%–79% band with a 70.5% line. Direction is classified as up leg when the low precedes the high, otherwise down leg, placing OTE in the expected zone per ICT conventions. Optional retracements and standard deviation projections are supported.
IPDA reference ranges (20/40/60 completed trading days) are plotted with merged labels for equal levels. Alerts fire on candle close fo...
👉 Read | Quotes | @mql5dev
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CMECalendar.mqh provides rule-based session halts for CME Globex equity index futures in New York time, aimed at EAs that must exit before the daily stop or avoid trading on short sessions. It covers regular 17:00 halts, full closures (New Year’s Day, Good Friday, Christmas), 13:00 early halts on major US holidays, 13:15 halts on 3 July, the day after Thanksgiving, and 24 December, plus the 09:15 Good Friday halt when it coincides with the US jobs report. Holiday observance shifts are handled, and Good Friday is computed via the Gregorian Easter algorithm.
Unpredictable one-offs are handled through a small CME_SPECIAL_DAYS string. All functions use New York dates/times; server time must be converted using the broker offset.
CMECalendarScan.mq5 validates the rules against M1 history by finding the last real trade per day, accounting for stray weekend/after-h...
👉 Read | Forum | @mql5dev
Unpredictable one-offs are handled through a small CME_SPECIAL_DAYS string. All functions use New York dates/times; server time must be converted using the broker offset.
CMECalendarScan.mq5 validates the rules against M1 history by finding the last real trade per day, accounting for stray weekend/after-h...
👉 Read | Forum | @mql5dev
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