Michael Prescott Burney / プロファイル

Version 2.02 — Stability & Performance Update
Released: June 2026

This update addresses several rendering, stability, and performance issues reported after timeframe and symbol switching. The core engine has been hardened with bounds protection, smarter redraw gating, and a layout cache system that significantly reduces CPU overhead.

Bug Fixes
Fixed: Array out of range errors in the profile engine
All bin index operations inside BuildProfileWindow are now clamped against the actual allocated array size rather than the global bin count. This eliminates the runtime crash that could occur immediately after a timeframe switch or during rapid symbol changes when internal state had not yet fully re-synchronized.

Fixed: Heatmap and HUD not drawing on certain timeframes
The indicator previously exited silently when bar history was not yet available after a timeframe switch. The HUD panel now renders independently of profile readiness, and the engine retries automatically on subsequent ticks until data is confirmed available.

Fixed: POC box and heatmap rendering outside the visible chart area
All canvas draw coordinates are now clamped to the chart bounds before any FillRectangle or TextOut call. The POC label box is now sized dynamically relative to chart width, preventing it from overflowing into the price scale.

Fixed: Stale canvas objects persisting across symbol or timeframe reloads
Bitmap label objects are now explicitly deleted before being recreated on initialization, preventing ghost overlays from appearing when the indicator reloads.

Performance Improvements
Heatmap layout cache
A layout validity check now gates the full heatmap repaint. If the chart width, height, first visible bar, visible bar count, and current bar time have not changed since the last draw, the expensive full-canvas rebuild is skipped entirely. This dramatically reduces CPU on stable charts.

Smarter redraw throttle
A g_needFullRedraw flag bypasses the refresh interval when a forced repaint is genuinely required (timeframe switch, chart resize, history load), while routine ticks continue to use the configurable minimum interval. This prevents both stale renders and unnecessary repaints.

Canvas resize guard
The heatmap and HUD canvases are only resized when the chart dimensions actually change, eliminating the repeated CCanvas::Resize calls that were visible in profiling as a top CPU consumer.

HUD decoupled from heatmap
The branded HUD panel now updates independently of the heatmap render pass. This means the panel remains visible and current even while the heatmap is waiting for history to load on a new timeframe.

Hard data guard in OnCalculate
The indicator now checks bar availability before entering the render path, preventing wasted work and suppressing spurious errors during the brief window after a timeframe switch when data is still synchronizing.

Notes
No input parameters were changed. All existing settings are fully compatible.

Visual output is identical to v2.01 on stable charts.

Users on lower-end systems or trading many symbols simultaneously should see the most noticeable improvement in responsiveness.

https://www.mql5.com/en/market/product/179802?source=Site+Profile+Seller

Hamunaptra is a free automated trading system for GBPUSD on the H1 chart, built around 50 internal strategies and a fixed 1:1 risk-reward structure on every trade.

This new build gives Hamunaptra an all-new look and feel, combining structured trade execution with a cleaner, more modern on-chart experience. It is designed for traders who want a free GBPUSD system with diversified logic, balanced trade construction, and a more professional live-chart presentation.

Core trading model

Hamunaptra is optimized for GBPUSD H1 and now uses 50 built-in strategies working inside one EA framework. This multi-strategy structure is designed to create broader market coverage while keeping all execution inside a single organized system.

All fifty strategies now operate with a 1:1 risk-reward model, meaning each trade is opened with an equal distance between stop loss and take profit. This gives the EA a cleaner and more disciplined trade-management structure, with consistency across all internal strategy logic.

The system is intended for traders who prefer a more balanced approach to automated trading rather than exaggerated target distances or unstable trade handling. By standardizing the risk-reward model across the full strategy stack, Hamunaptra is built to deliver more uniform execution behavior on GBPUSD H1.

All-new look and feel

One of the biggest upgrades in this version is the complete visual refresh. Hamunaptra now features a redesigned on-chart interface with a more advanced TradingView-style appearance, helping your live charts feel cleaner, sharper, and more premium while the EA is running.

The new dashboard style replaces plain chart text with a richer visual layout that presents important information in a much more modern way. This gives the system a more polished presentation on live charts and makes it easier to monitor activity at a glance.

New visual features

The latest build also includes the new interface additions introduced in the updated visual framework. These include a collapsible dashboard panel, live display toggles, a per-strategy breakdown section, clickable strategy-row highlighting, and enhanced trade projection visuals directly on the chart.

The collapsible panel allows you to switch between a full dashboard view and a compact minimized bar, giving you more flexibility over chart space. The settings controls make it possible to show or hide visual sections in real time, so the display can be adjusted without needing to remove and reload the EA.

The per-strategy breakdown helps you see which strategy components are currently active, while clickable rows make it easier to connect dashboard activity to the exact position shown on the chart. Together, these additions turn Hamunaptra into a more interactive and user-friendly trading tool rather than just a background automation system.

Free system for GBPUSD H1

Hamunaptra is offered as a free EA for traders who want to explore a diversified GBPUSD H1 trading system with modern chart visuals and a fully updated presentation. It combines 50 strategies, a fixed 1:1 risk-reward structure, and an all-new dashboard experience in one complete package.

If you are looking for a free GBPUSD robot with a fresh interface, organized trade logic, and a more professional chart-side experience, Hamunaptra is built to deliver exactly that.

https://www.mql5.com/en/market/product/125260?source=Site+Profile+Seller#

Lorentzian Classification EA for MetaTrader 5
Lorentzian Classification EA is a machine-learning-based Expert Advisor for MetaTrader 5 designed to classify market conditions and automate trade execution using a structured confirmation process. It combines Lorentzian Distance K-Nearest Neighbors (KNN) classification with kernel regression trend confirmation, then applies multiple market filters and configurable trade management rules before opening a position.

The system was built for traders who want a more adaptive, data-driven approach than fixed-rule indicators alone. Instead of relying on a single signal source, the EA evaluates a multi-feature market state, compares it to historical patterns, and uses confluence logic to reduce weak or low-quality entries.

https://www.mql5.com/en/market/product/180639?source=Site+Profile+Seller

Core Trading Concept
The logic of the EA begins with the SuperTrend indicator, which uses ATR-based volatility bands to identify bullish and bearish market phases. A lower factor creates tighter bands and faster reactions, while a higher factor creates wider bands and slower but more selective signals. The main challenge with a traditional SuperTrend is that one fixed factor rarely performs well in all market conditions.

To solve this, SuperTrend AI Clustering calculates a full range of SuperTrend variations using user-defined factor values. Each variation is tracked with a performance score that reflects how effectively that factor has aligned with recent price movement. These performance scores are then processed through a K-Means clustering model, which separates them into three groups representing weaker, average, and stronger recent performance.

The EA then selects the target cluster and calculates an adaptive factor from that group. This adaptive factor drives the final SuperTrend used for trade logic, trailing behavior, and dashboard display. In practical terms, the Expert Advisor is always trying to work with the SuperTrend sensitivity that best matches the current market environment.

https://www.mql5.com/en/market/product/180711?source=Site+Market+My+Products+Page#description

SuperTrend AI Clustering Expert Advisor for MetaTrader 5
SuperTrend AI Clustering is an adaptive trend-following Expert Advisor for MetaTrader 5 designed to adjust itself to changing market conditions. Instead of using one fixed SuperTrend multiplier, the EA evaluates multiple factor values at the same time, measures their recent performance, applies K-Means clustering, and selects the factor group that is currently performing best. This creates a dynamic SuperTrend model that can respond to different volatility regimes and market structures without requiring constant manual reconfiguration.

The system is built for traders who want an automated approach to trend-following with a strong focus on adaptability, structured risk control, and transparent on-chart information. It can be used on forex pairs, metals, indices, cryptocurrencies, commodities, and other symbols available in MetaTrader 5. The Expert Advisor is compatible with multiple timeframes, from lower-timeframe intraday trading to higher-timeframe swing and position trading.

https://www.mql5.com/en/users/michael4308/seller

Filter stack for trade qualityAfter the classifier generates a directional bias, the signal must pass through a configurable filter stack before a trade can be opened. Available filters include a volatility filter, regime filter, ADX filter, EMA trend filter, SMA trend filter, session filter, spread filter, and kernel filter.
The volatility filter is designed to block trades during abnormal spikes, while the regime filter helps distinguish trending conditions from flat market structure. The EMA and SMA filters can be used to keep trades aligned with the broader trend, and the ADX filter can restrict entries to periods with sufficient directional strength.
This layered structure is useful because one condition alone is rarely enough in live markets. The EA is designed so that classification, trend alignment, volatility control, and execution filters can work together rather than depend on a single trigger.

https://www.mql5.com/en/market/product/180639?source=Site+Profile+Seller

Lorentzian Classification EA for MetaTrader 5
Lorentzian Classification EA is a machine-learning-based Expert Advisor for MetaTrader 5 designed to classify market conditions and automate trade execution using a structured confirmation process. It combines Lorentzian Distance K-Nearest Neighbors (KNN) classification with kernel regression trend confirmation, then applies multiple market filters and configurable trade management rules before opening a position.

The system was built for traders who want a more adaptive, data-driven approach than fixed-rule indicators alone. Instead of relying on a single signal source, the EA evaluates a multi-feature market state, compares it to historical patterns, and uses confluence logic to reduce weak or low-quality entries.

https://www.mql5.com/en/market/product/180639?source=Site+Profile+Seller

Risk Management
Reversion Apex EA includes a full risk-control engine rather than simple signal execution. It supports automatic risk-% position sizing, fixed-lot mode, ATR-based or fixed stop loss and take profit, break-even protection, trailing stop management, and optional RSI cross-back exits. It also includes daily loss protection, maximum drawdown guards, profit target control, spread filtering, session filtering, and one-entry-per-bar logic for more disciplined live trading.

https://www.mql5.com/en/market/product/180327?source=Site+Market+My+Products+Page#description

Included set file profiles
The EA is delivered with seven pre-configured set file profiles to provide structured starting points for different trading styles and time horizons. These profiles include M15 Scalping, M30 Intraday, H1 Swing, H4 Position, D1 Long-Term, H1 XAUUSD Gold Specialist, and H4 Conservative / Prop Account.

The H4 Position profile is the primary recommended starting point because the underlying Lorentzian framework was originally designed and tested around higher intraday to swing-style timeframes. The other profiles are intended for traders who prefer faster execution, gold-specific tuning, long-term trend participation, or lower-risk funded-account style operation.

These profiles are not presented as fixed final settings. They are designed as structured baselines that traders can further test and refine for their own broker conditions, symbols, and execution style.

https://www.mql5.com/en/market/product/180639?source=Site+Profile#

Feature-driven market classification
The EA supports up to five simultaneous features in its classification model. The default configuration uses RSI, WaveTrend, CCI, ADX, and a second RSI with different settings so the algorithm can analyze momentum, deviation, cycle behavior, and trend strength from multiple angles.

Each feature is configurable, allowing the user to tailor the behavior of the classifier to different symbols and timeframes. This makes the EA suitable for traders who want to keep the default research-based structure while still being able to optimize the input profile for their own market selection.

Because the feature set is part of the similarity calculation, changing feature periods or types directly affects how the system interprets historical market states. This gives advanced users room to perform optimization and walk-forward validation without changing the overall architecture of the strategy.

https://www.mql5.com/en/market/product/180639?source=Site+Profile#

Kernel regression confirmation
To avoid acting on raw classification output alone, the EA includes a kernel regression confirmation layer. It uses Rational Quadratic and Gaussian kernel estimates to evaluate trend alignment and to confirm whether a KNN signal is supported by the current directional structure of the market.

If the kernel filter is enabled, long signals require bullish kernel alignment and short signals require bearish kernel alignment. This extra confirmation step is intended to reduce false signals, especially during ranging or unstable conditions.

The same kernel logic can also be used for dynamic exit management. When enabled, trades may be closed based on kernel crossover behavior instead of using only a fixed holding model.

https://www.mql5.com/en/market/product/180639?source=Site+Market+My+Products+Page#description

Core idea behind the system
At the center of the EA is a Lorentzian Distance classifier. For each new closed bar, the system builds a feature vector from technical measurements such as RSI, WaveTrend, CCI, and ADX, then compares the current market state to historical data in order to find similar patterns. Based on how those similar patterns resolved in the past, the classifier produces a directional prediction score.

The Lorentzian Distance approach is used because it compresses large feature differences more gracefully than standard Euclidean distance. In practical terms, this makes the similarity calculation more resistant to outliers and volatility spikes that often distort financial data.

The KNN engine can scan up to 2,000 historical bars, evaluate neighbors using the Lorentzian metric, and generate a bullish or bearish vote based on the outcomes of the nearest historical matches. The resulting prediction score helps determine whether current conditions favor a long or short setup.

https://www.mql5.com/en/market/product/180639?source=Site+Market+My+Products+Page

Lorentzian Classification EA for MetaTrader 5
Lorentzian Classification EA is a machine-learning-based Expert Advisor im releasing soon for MetaTrader 5 designed to classify market conditions and automate trade execution using a structured confirmation process. It combines Lorentzian Distance K-Nearest Neighbors (KNN) classification with kernel regression trend confirmation, then applies multiple market filters and configurable trade management rules before opening a position.

The system was built for traders who want a more adaptive, data-driven approach than fixed-rule indicators alone. Instead of relying on a single signal source, the EA evaluates a multi-feature market state, compares it to historical patterns, and uses confluence logic to reduce weak or low-quality entries.

Trading logic
The Expert Advisor evaluates the market on each closed bar. It rebuilds the Quantum Delta Wave, detects fresh structural divergence around recent pivots, and can require extreme-zone confirmation before allowing an entry.

Buy setup: bullish divergence, where price makes a lower low while the wave makes a higher low in oversold territory
Sell setup: bearish divergence, where price makes a higher high while the wave makes a lower high in overbought territory
Entry style: selective, rule-based, and designed to avoid overtrading

https://www.mql5.com/en/users/michael4308/seller

Best use case
DeltaPulse Auto is intended for traders who want an automated divergence strategy with clear risk boundaries, structured trade management, and preset-based deployment across multiple market types.

https://www.mql5.com/en/market/product/180330?source=Site+Profile+Seller

Reversion Apex EA combines a clear mean-reversion entry model with professional trade management and built-in account safeguards. It is designed for traders who want a cleaner, more controlled approach to automated trading on MetaTrader 5.

https://www.mql5.com/en/market/product/180327?source=Site+Market+My+Products+Page#description