PropGuard MT5 is a chart-window indicator focused on prop-style risk constraints: Daily Loss Limit and Overall Max Drawdown. It converts configured limits into a live price boundary (“Dead-Line”) derived from current equity, open positions on the active symbol, and tick value/tick size.
The indicator draws a single effective Dead-Line based on the stricter of the daily or overall limit, with optional separate daily and overall lines. A dashboard panel reports balance/equity, allowed loss, minimum equity levels, net long/short lots, active rule, and remaining buffer in currency and points with a configurable warning threshold.
Trailing and fixed drawdown modes are supported. Trailing uses daily/overall peak equity; non-trailing uses start-of-day balance (approximation in v1.00) and a manual start-capital reference.
Safety states include hiding lines ...
👉 Read | AppStore | @mql5dev
#MQL5 #MT5 #Indicator
The indicator draws a single effective Dead-Line based on the stricter of the daily or overall limit, with optional separate daily and overall lines. A dashboard panel reports balance/equity, allowed loss, minimum equity levels, net long/short lots, active rule, and remaining buffer in currency and points with a configurable warning threshold.
Trailing and fixed drawdown modes are supported. Trailing uses daily/overall peak equity; non-trailing uses start-of-day balance (approximation in v1.00) and a manual start-capital reference.
Safety states include hiding lines ...
👉 Read | AppStore | @mql5dev
#MQL5 #MT5 #Indicator
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Educational use only; not trading advice. EURUSD backtests under the stated conditions were unprofitable.
Strategy logic uses New York local time. The first 4H candle defines the initial high/low range. After that candle closes, the system waits for a 5-minute close outside the range, then a 5-minute close back inside. Close above high then back inside triggers a sell signal. Close below low then back inside triggers a buy signal.
A time filter invalidates signals if price remains above the high or below the low for more than 75 minutes, intended to avoid late entries after an extended move.
Correct broker time configuration is required. Parameters include winter/summer server GMT offsets, server switch dates for summer and winter time, and lot size. A single DST or offset mismatch can shift the entire session alignment.
👉 Read | Quotes | @mql5dev
#MQL5 #MT5 #Strategy
Strategy logic uses New York local time. The first 4H candle defines the initial high/low range. After that candle closes, the system waits for a 5-minute close outside the range, then a 5-minute close back inside. Close above high then back inside triggers a sell signal. Close below low then back inside triggers a buy signal.
A time filter invalidates signals if price remains above the high or below the low for more than 75 minutes, intended to avoid late entries after an extended move.
Correct broker time configuration is required. Parameters include winter/summer server GMT offsets, server switch dates for summer and winter time, and lot size. A single DST or offset mismatch can shift the entire session alignment.
👉 Read | Quotes | @mql5dev
#MQL5 #MT5 #Strategy
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Wick Rejection Scanner Dashboard is an MT5 indicator that scans multiple symbols and timeframes for upper/lower wick rejection candles and shows results in an on-chart dashboard. It targets price-action workflows that need watchlist coverage without opening many charts. The module is a scanner and visualizer only and does not execute trades.
Signals are generated from configurable rejection rules: dominant wick percentage, minimum candle range, minimum body size, opposite-wick cap, optional ATR volatility gating, and optional trend-context scoring to reduce weak in-range setups.
Core functions include Market Watch or custom symbol lists, timeframe selection with optional M15/H4 passes, ranked sorting (recent, wick %, strength), age display, and click-to-switch chart navigation. Optional chart markers and labels are available with caps for performance...
👉 Read | Signals | @mql5dev
#MQL5 #MT5 #Indicator
Signals are generated from configurable rejection rules: dominant wick percentage, minimum candle range, minimum body size, opposite-wick cap, optional ATR volatility gating, and optional trend-context scoring to reduce weak in-range setups.
Core functions include Market Watch or custom symbol lists, timeframe selection with optional M15/H4 passes, ranked sorting (recent, wick %, strength), age display, and click-to-switch chart navigation. Optional chart markers and labels are available with caps for performance...
👉 Read | Signals | @mql5dev
#MQL5 #MT5 #Indicator
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The article extends a DoEasy/MQL5 UI concept: each “animation frame” draws on a form while preserving the pixels underneath, so moving, updating, or deleting visuals cleanly restores the original background.
A new base CFrame class centralizes shared state (IDs, coordinates, anchors, last offsets) and embeds the pixel-copy/restore logic previously kept inside the form. Two derived frames specialize rendering: CFrameText for text and CFrameQuad for shapes built on CCanvas primitives.
The rectangle frame adds per-primitive bounding-box calculations (dot, vertical/horizontal segments, free lines, polylines) to save only the affected area. Support code is improved with frame/figure enums, array min/max helpers that avoid “-1 means error” ambiguity, and anchor-based methods to compute saved-rectangle offsets for both text and images.
👉 Read | AppStore | @mql5dev
#MQL5 #MT5 #AlgoTrading
A new base CFrame class centralizes shared state (IDs, coordinates, anchors, last offsets) and embeds the pixel-copy/restore logic previously kept inside the form. Two derived frames specialize rendering: CFrameText for text and CFrameQuad for shapes built on CCanvas primitives.
The rectangle frame adds per-primitive bounding-box calculations (dot, vertical/horizontal segments, free lines, polylines) to save only the affected area. Support code is improved with frame/figure enums, array min/max helpers that avoid “-1 means error” ambiguity, and anchor-based methods to compute saved-rectangle offsets for both text and images.
👉 Read | AppStore | @mql5dev
#MQL5 #MT5 #AlgoTrading
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News Spread Risk Dashboard is a lightweight chart-overlay indicator that monitors the live Ask–Bid difference and flags conditions where spread expansion can undermine entries, exits, and risk controls. It targets periods commonly associated with widening spreads: high-impact news, rollover, session transitions, and low-liquidity opens.
The panel displays Current, Min/Max/Avg spread over a rolling window, plus a status line showing Stable or RISK with the triggering reason. Background color changes when warning logic is met to keep the signal visible without clutter.
Two trigger modes are supported. Relative spike detection warns when Current ≥ Avg × multiplier, adapting to each symbol’s typical spread. Absolute thresholds warn when Current ≥ fixed limit, including per-instrument lists (for example, EURUSD:3.0, XAUUSD:30.0).
Display can be Smart A...
👉 Read | Quotes | @mql5dev
#MQL5 #MT5 #Indicator
The panel displays Current, Min/Max/Avg spread over a rolling window, plus a status line showing Stable or RISK with the triggering reason. Background color changes when warning logic is met to keep the signal visible without clutter.
Two trigger modes are supported. Relative spike detection warns when Current ≥ Avg × multiplier, adapting to each symbol’s typical spread. Absolute thresholds warn when Current ≥ fixed limit, including per-instrument lists (for example, EURUSD:3.0, XAUUSD:30.0).
Display can be Smart A...
👉 Read | Quotes | @mql5dev
#MQL5 #MT5 #Indicator
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Playground EA is a five-version MQL5 Expert Advisor set (v1.00–v1.04) built for testing Fair Value Gap encroachment and, in later builds, liquidity targeting. The code is explicitly experimental, not optimized, and intended for learning and controlled testing.
All versions share the same core entry rule: buy on a candle close above the FVG encroachment point and sell on a close below. Position management is primarily dollar-based profit and loss thresholds, with optional filters such as minimum gap size and trend alignment.
Version changes are incremental. v1.00 combined encroachment and liquidity scalping but had functional issues. v1.01 removed liquidity features and stabilized execution. v1.02 added Silver Bullet time windows and Draw On Liquidity targets, but had configuration and timing problems. v1.03 refactored for parallel mode execution and corrected se...
👉 Read | Docs | @mql5dev
#MQL5 #MT5 #EA
All versions share the same core entry rule: buy on a candle close above the FVG encroachment point and sell on a close below. Position management is primarily dollar-based profit and loss thresholds, with optional filters such as minimum gap size and trend alignment.
Version changes are incremental. v1.00 combined encroachment and liquidity scalping but had functional issues. v1.01 removed liquidity features and stabilized execution. v1.02 added Silver Bullet time windows and Draw On Liquidity targets, but had configuration and timing problems. v1.03 refactored for parallel mode execution and corrected se...
👉 Read | Docs | @mql5dev
#MQL5 #MT5 #EA
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Complex indicators with 70+ buffers and 30+ plots often fail on maintainability due to manual SetIndexBuffer numbering. A small change in draw order, such as moving a filling background behind a candle plot, can force renumbering dozens of bindings and recalculating plot-to-buffer offsets, including extra color buffers.
A wrapper class named CPlotManager is used to automate plot hierarchy and buffer allocation. Plots are added in the required draw order, while the class computes indices, binds buffers, and applies styling without large property blocks for colors and widths.
Typical usage keeps the indicator properties limited to total plot and buffer counts, includes the helper file, then creates the manager in OnInit() and registers plots sequentially. Z-order changes become a simple reordering of add calls.
👉 Read | NeuroBook | @mql5dev
#MQL5 #MT5 #Indicator
A wrapper class named CPlotManager is used to automate plot hierarchy and buffer allocation. Plots are added in the required draw order, while the class computes indices, binds buffers, and applies styling without large property blocks for colors and widths.
Typical usage keeps the indicator properties limited to total plot and buffer counts, includes the helper file, then creates the manager in OnInit() and registers plots sequentially. Z-order changes become a simple reordering of add calls.
👉 Read | NeuroBook | @mql5dev
#MQL5 #MT5 #Indicator
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Session Daylight Gradient is an ambient session-awareness indicator for MetaTrader 5 that replaces large session boxes with a low-noise background gradient. The color progression reflects typical market behavior across Pacific, Asia, London, the London/NY overlap, and the NY fade into Pacific, keeping price action readable via adjustable opacity and smoothing.
Optional session event markers add compact labels and separators for session opens/closes and overlap boundaries. Optional “sunrays” highlight scheduled timestamps from a simple list to flag news windows without switching to a calendar.
Timezone handling supports UTC, broker/server time, or PC local time, with a manual DST hour shift for alignment corrections. Performance is managed by drawing objects only for the visible chart range plus a buffer, with guidance to reduce visual load on very lo...
👉 Read | VPS | @mql5dev
#MQL5 #MT5 #Indicator
Optional session event markers add compact labels and separators for session opens/closes and overlap boundaries. Optional “sunrays” highlight scheduled timestamps from a simple list to flag news windows without switching to a calendar.
Timezone handling supports UTC, broker/server time, or PC local time, with a manual DST hour shift for alignment corrections. Performance is managed by drawing objects only for the visible chart range plus a buffer, with guidance to reduce visual load on very lo...
👉 Read | VPS | @mql5dev
#MQL5 #MT5 #Indicator
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Probability theory is presented as a practical framework for trading that replaces intuition with measurable risk: expected value, event likelihoods, percentiles, and clearly defined acceptance of uncertainty.
The article models market behavior through event spaces, distinguishing non-overlapping vs overlapping states, and shows how probabilities must sum to 1 in an exhaustive partition. For continuous outcomes, it switches to random variables and probability density, where event probabilities come from integrating regions.
Random walk is used as a baseline: with symmetric stops and no costs, expectancy trends to zero; with spreads/fees, negative. That baseline still helps compute risk metrics like lifetime and path-dependent event odds.
It then builds toward probability trees via the total probability formula, treating “hypotheses” as nested even...
👉 Read | Signals | @mql5dev
#MQL5 #MT5 #AlgoTrading
The article models market behavior through event spaces, distinguishing non-overlapping vs overlapping states, and shows how probabilities must sum to 1 in an exhaustive partition. For continuous outcomes, it switches to random variables and probability density, where event probabilities come from integrating regions.
Random walk is used as a baseline: with symmetric stops and no costs, expectancy trends to zero; with spreads/fees, negative. That baseline still helps compute risk metrics like lifetime and path-dependent event odds.
It then builds toward probability trees via the total probability formula, treating “hypotheses” as nested even...
👉 Read | Signals | @mql5dev
#MQL5 #MT5 #AlgoTrading
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ASZ (Adaptive Structure ZigZag) is an open-source market structure analyzer built as an update to the classic ZigZag/fractal approach. It targets common issues in fixed-threshold ZigZags that lag during fast moves and generate excess noise in slow markets.
The logic relies on a hybrid threshold driven by ATR. In higher volatility, the swing-detection threshold expands to reduce noise. In lower volatility ranges, it contracts to capture smaller structural changes. Swing validation scans 3–14 bars to the left and confirms using a fixed number of right-side bars.
ASZ is not a signal indicator and does not produce buy/sell entries. It is designed to mark highs, lows, and break-of-structure with deterministic behavior. Once confirmed, swing points do not repaint. Performance is optimized with caching, and a state machine enforces strict high/low alternation to ...
👉 Read | Forum | @mql5dev
#MQL5 #MT5 #Indicator
The logic relies on a hybrid threshold driven by ATR. In higher volatility, the swing-detection threshold expands to reduce noise. In lower volatility ranges, it contracts to capture smaller structural changes. Swing validation scans 3–14 bars to the left and confirms using a fixed number of right-side bars.
ASZ is not a signal indicator and does not produce buy/sell entries. It is designed to mark highs, lows, and break-of-structure with deterministic behavior. Once confirmed, swing points do not repaint. Performance is optimized with caching, and a state machine enforces strict high/low alternation to ...
👉 Read | Forum | @mql5dev
#MQL5 #MT5 #Indicator
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MetaTrader 5 can use sockets from MQL5, but socket calls are blocked inside indicators to protect chart calculation performance. The solution splits responsibilities: an indicator provides the isolated chat UI, while an Expert Advisor handles network I/O and embeds the indicator binary.
A small connection class wraps socket lifecycle, validates the handle, and implements simple text send/receive. Reads are non-blocking with a short timeout and only return complete messages when a newline delimiter is detected, making message framing explicit and pushing protocol responsibility to the server.
The EA bridges everything with timer-driven polling (OnTimer) and custom chart events (OnChartEvent), passing incoming socket data to the indicator and forwarding user messages back to the socket. The article also notes event spoofing risks and why real deployme...
👉 Read | Docs | @mql5dev
#MQL5 #MT5 #AlgoTrading
A small connection class wraps socket lifecycle, validates the handle, and implements simple text send/receive. Reads are non-blocking with a short timeout and only return complete messages when a newline delimiter is detected, making message framing explicit and pushing protocol responsibility to the server.
The EA bridges everything with timer-driven polling (OnTimer) and custom chart events (OnChartEvent), passing incoming socket data to the indicator and forwarding user messages back to the socket. The article also notes event spoofing risks and why real deployme...
👉 Read | Docs | @mql5dev
#MQL5 #MT5 #AlgoTrading
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This part connects an MT5 chart control panel to backend logic using event-driven code. Instead of polling in OnTick, user actions are handled in OnChartEvent, filtering for object-click events and checking sparam to confirm the Send button was pressed.
Once validated, the handler reads the prompt from the input control and performs an HTTP call via WebRequest. The request is built with a model URL, API key, JSON content-type header, and a JSON body, then encoded to a UTF-8 char array (with the trailing null removed) to match WebRequest requirements.
It also establishes basic response handling: capturing headers/body, enforcing timeouts, reporting errors, and converting the returned byte array back into a string for later JSON parsing and panel display.
👉 Read | Freelance | @mql5dev
#MQL5 #MT5 #AlgoTrading
Once validated, the handler reads the prompt from the input control and performs an HTTP call via WebRequest. The request is built with a model URL, API key, JSON content-type header, and a JSON body, then encoded to a UTF-8 char array (with the trailing null removed) to match WebRequest requirements.
It also establishes basic response handling: capturing headers/body, enforcing timeouts, reporting errors, and converting the returned byte array back into a string for later JSON parsing and panel display.
👉 Read | Freelance | @mql5dev
#MQL5 #MT5 #AlgoTrading
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CPI Mini-Candles for MT5 adds a pressure layer to candlesticks using Closing Location Value: where the close sits inside the bar’s high–low range. This yields a normalized CPI in [-1, +1], exposing cases like “red-but-bullish” or “green-but-weak” that candle color can’t explain.
The indicator overlays mid-anchored mini-candles on closed bars only. Marker direction shows buy/sell pressure, height scales with |CPI| (clamped for readability), and five zones (strong/mild/neutral) drive color mapping. Optional arrows mark strong-pressure bars with a configurable offset.
Alerts are state-based to avoid noise: events fire on transitions (not persistence), mainly when entering strong zones, with optional strong exits and sign flips. The MQL5 design uses DRAW_COLOR_CANDLES with synthetic OHLC buffers plus separate arrow plots, includes range gating, and keeps...
👉 Read | CodeBase | @mql5dev
#MQL5 #MT5 #Indicator
The indicator overlays mid-anchored mini-candles on closed bars only. Marker direction shows buy/sell pressure, height scales with |CPI| (clamped for readability), and five zones (strong/mild/neutral) drive color mapping. Optional arrows mark strong-pressure bars with a configurable offset.
Alerts are state-based to avoid noise: events fire on transitions (not persistence), mainly when entering strong zones, with optional strong exits and sign flips. The MQL5 design uses DRAW_COLOR_CANDLES with synthetic OHLC buffers plus separate arrow plots, includes range gating, and keeps...
👉 Read | CodeBase | @mql5dev
#MQL5 #MT5 #Indicator
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FFC Data Feeder is a utility Expert Advisor used to download economic calendar data for the FFC Calendar indicator. It is not a trading system and does not place or manage orders. The EA exists because MQL4 indicators cannot call the secure WebRequest API directly.
The feeder runs in the background on a single chart, retrieves data via native WebRequest, and stores it locally for the indicator to render across charts. This avoids enabling DLL imports while keeping the data path consistent.
One-time configuration requires enabling WebRequest in Tools -> Options -> Expert Advisors, then adding https://nfs.faireconomy.media/ to the allowed URL list. Run one instance on an empty chart, verify connection status on the dashboard, then attach the FFC 2.0 Calendar indicator to any chart. Free and open source as part of the MQL Trading Tools suite.
👉 Read | Forum | @mql5dev
#MQL4 #MT4 #EA
The feeder runs in the background on a single chart, retrieves data via native WebRequest, and stores it locally for the indicator to render across charts. This avoids enabling DLL imports while keeping the data path consistent.
One-time configuration requires enabling WebRequest in Tools -> Options -> Expert Advisors, then adding https://nfs.faireconomy.media/ to the allowed URL list. Run one instance on an empty chart, verify connection status on the dashboard, then attach the FFC 2.0 Calendar indicator to any chart. Free and open source as part of the MQL Trading Tools suite.
👉 Read | Forum | @mql5dev
#MQL4 #MT4 #EA
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Part 5 extends a dual WaveTrend crossover indicator into a full chart UI: a fast oscillator generates entry candidates, while a slower one optionally filters trades to reduce noise.
Signals now form “boxes” around crossover bars and wait for a price breakout before confirming direction. Boxes can auto-extend using average candle size, making the breakout logic adapt to volatility instead of fixed ranges.
Rendering moves beyond standard plots by using the MQL5 Canvas library. Gradient “fog” overlays visualize trend strength with smooth interpolation, while signals can be shown as triangles or labeled bubbles.
Risk tools are integrated directly into the indicator: dynamic TP/SL levels are computed from candle-size multipliers or percentage moves, then drawn as lines and summarized in an on-chart table, updated only on new signals for efficient redraws.
👉 Read | Signals | @mql5dev
#MQL5 #MT5 #Indicator
Signals now form “boxes” around crossover bars and wait for a price breakout before confirming direction. Boxes can auto-extend using average candle size, making the breakout logic adapt to volatility instead of fixed ranges.
Rendering moves beyond standard plots by using the MQL5 Canvas library. Gradient “fog” overlays visualize trend strength with smooth interpolation, while signals can be shown as triangles or labeled bubbles.
Risk tools are integrated directly into the indicator: dynamic TP/SL levels are computed from candle-size multipliers or percentage moves, then drawn as lines and summarized in an on-chart table, updated only on new signals for efficient redraws.
👉 Read | Signals | @mql5dev
#MQL5 #MT5 #Indicator
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A Python trading simulator is being aligned with MetaTrader 5 semantics by implementing order_send as a single entry point for all trade operations. The request payload mirrors MqlTradeRequest fields and routes actions to either MT5 or a local tester mode.
In tester mode, pending orders, positions, and deals are stored in containers, with explicit handling for open, close, modify, delete, and history logging. Close requests validate bid/ask pricing rules and require opposing order types.
Request validation is centralized in a TradeValidators class: lot constraints, margin checks, entry price validity, stops level, SL/TP direction, max volume, max orders, and freeze level rules. A CTrade wrapper calls the simulator’s overridden order_send, enabling MT5-like trade APIs for strategy testing workflows.
👉 Read | Forum | @mql5dev
#MQL5 #MT5 #AlgoTrading
In tester mode, pending orders, positions, and deals are stored in containers, with explicit handling for open, close, modify, delete, and history logging. Close requests validate bid/ask pricing rules and require opposing order types.
Request validation is centralized in a TradeValidators class: lot constraints, margin checks, entry price validity, stops level, SL/TP direction, max volume, max orders, and freeze level rules. A CTrade wrapper calls the simulator’s overridden order_send, enabling MT5-like trade APIs for strategy testing workflows.
👉 Read | Forum | @mql5dev
#MQL5 #MT5 #AlgoTrading
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In the MetaTrader 5 beta build 5540, we have improved ONNX integration in MQL5:
• ONNX models now run significantly faster on graphics cards with CUDA support.
• New flags have been added for GPU management and logging.
• The library installation workflow has been changed: it is now installed only on the first launch of an ONNX-based program, rather than together with the platform.
In addition, we refined the rendering of text and analytical objects on charts using the Blend2D engine introduced in the previous update. Trading reports have also been improved, and the strategy tester has been made more robust.
The web version of the platform has received several improvements as well. When adjusting stop levels on the chart, you can now see an approximate profit or loss in monetary terms. The display of certain trading data has also been corrected.
Read more…
• ONNX models now run significantly faster on graphics cards with CUDA support.
• New flags have been added for GPU management and logging.
• The library installation workflow has been changed: it is now installed only on the first launch of an ONNX-based program, rather than together with the platform.
In addition, we refined the rendering of text and analytical objects on charts using the Blend2D engine introduced in the previous update. Trading reports have also been improved, and the strategy tester has been made more robust.
The web version of the platform has received several improvements as well. When adjusting stop levels on the chart, you can now see an approximate profit or loss in monetary terms. The display of certain trading data has also been corrected.
Read more…
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The article refactors an MT5 auto-optimization workflow to swap strategies cleanly, moving from SimpleVolumes to SimpleCandles while keeping library code independent from project code. The key change is separating “what varies per strategy” from the reusable project-creation and database plumbing.
A reliability bug is fixed in the optimization results database: concurrent tester agents can trigger “database locked” insert failures. The solution adds retry logic with an attempt counter and short random backoff to SQL execution paths, plus a shared flag to detect errors and decide whether to commit or roll back transactions.
Developer ergonomics improve via redesigned loop macros that preserve debuggability and by documenting how to extend strategy inputs (example: max spread gate) end-to-end: tester inputs, init-string serialization, constructor parsing, ...
👉 Read | Quotes | @mql5dev
#MQL5 #MT5 #AlgoTrading
A reliability bug is fixed in the optimization results database: concurrent tester agents can trigger “database locked” insert failures. The solution adds retry logic with an attempt counter and short random backoff to SQL execution paths, plus a shared flag to detect errors and decide whether to commit or roll back transactions.
Developer ergonomics improve via redesigned loop macros that preserve debuggability and by documenting how to extend strategy inputs (example: max spread gate) end-to-end: tester inputs, init-string serialization, constructor parsing, ...
👉 Read | Quotes | @mql5dev
#MQL5 #MT5 #AlgoTrading
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Adaptive VWAP Institutional v1.0.0 is a VWAP indicator for MetaTrader 5 built with HFT and professional asset management constraints in mind, emphasizing consistent session logic and data-quality controls.
Asset class detection uses a multi-step verification flow (crypto, forex, metals, stocks, indices) to apply appropriate reset policies. Session handling includes DST-aware timezone calculations using Zeller’s Congruence, plus 17:00 New York rollover support for forex, gold, and energy.
Data conditioning adds median-volume sampling to reduce the impact of bad ticks and volume spikes. Session state persistence is handled via disk caching across restarts and timeframe changes. Core execution is optimized for O(n) behavior suitable for VPS deployments.
An on-chart diagnostic panel reports distance to VWAP (%), accumulated volume, bar count, and active tim...
👉 Read | Signals | @mql5dev
#MQL5 #MT5 #Indicator
Asset class detection uses a multi-step verification flow (crypto, forex, metals, stocks, indices) to apply appropriate reset policies. Session handling includes DST-aware timezone calculations using Zeller’s Congruence, plus 17:00 New York rollover support for forex, gold, and energy.
Data conditioning adds median-volume sampling to reduce the impact of bad ticks and volume spikes. Session state persistence is handled via disk caching across restarts and timeframe changes. Core execution is optimized for O(n) behavior suitable for VPS deployments.
An on-chart diagnostic panel reports distance to VWAP (%), accumulated volume, bar count, and active tim...
👉 Read | Signals | @mql5dev
#MQL5 #MT5 #Indicator
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A script is available for pulling cryptocurrency quotes from Binance and showing them in a custom symbol group inside MT5.
Enable WebRequest in Terminal Settings under Advisors and add https://api.binance.com to the allowed URLs. Copy BinanceQuotesDownloader into the terminal’s Scripts directory and run it from the Navigator.
Open View -> Symbols, then Custom -> Binance to select required instruments. Create charts via File -> New Chart -> Custom -> Binance.
Quote loading status is reported in the Experts tab. Once populated, the custom symbols can be used with indicators and standard chart analysis workflows.
👉 Read | NeuroBook | @mql5dev
#MQL5 #MT5 #script
Enable WebRequest in Terminal Settings under Advisors and add https://api.binance.com to the allowed URLs. Copy BinanceQuotesDownloader into the terminal’s Scripts directory and run it from the Navigator.
Open View -> Symbols, then Custom -> Binance to select required instruments. Create charts via File -> New Chart -> Custom -> Binance.
Quote loading status is reported in the Experts tab. Once populated, the custom symbols can be used with indicators and standard chart analysis workflows.
👉 Read | NeuroBook | @mql5dev
#MQL5 #MT5 #script
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A remote Python risk manager for MetaTrader 5 turns risk control into an always-on service, designed to protect accounts during volatility and human error. It focuses on the math behind drawdowns: deeper losses require disproportionately larger returns to recover, so limits must be enforced early.
The system connects via the MT5 Python API and checks account state every ~18 seconds. It tracks balance/equity drawdown, daily and weekly loss caps, and margin level, then can automatically close all positions and block further trading when thresholds are breached.
Implementation emphasizes reliability: a PyQt5 GUI for configuration and live metrics, multithreading to keep monitoring responsive, SQLite for state/history, autosave for restart safety, plus weekly HTML reports for post-trade analysis and iteration across multiple accounts.
👉 Read | CodeBase | @mql5dev
#MQL5 #MT5 #RiskMgmt
The system connects via the MT5 Python API and checks account state every ~18 seconds. It tracks balance/equity drawdown, daily and weekly loss caps, and margin level, then can automatically close all positions and block further trading when thresholds are breached.
Implementation emphasizes reliability: a PyQt5 GUI for configuration and live metrics, multithreading to keep monitoring responsive, SQLite for state/history, autosave for restart safety, plus weekly HTML reports for post-trade analysis and iteration across multiple accounts.
👉 Read | CodeBase | @mql5dev
#MQL5 #MT5 #RiskMgmt
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