Codes
TransactionCostCollector — Broker Cost Profiling Script for MetaTrader 5
Triple-barrier labeling pipelines frequently use an arbitrary constant (0.5–1.0%) or a legacy spread assumption as the min_ret threshold. A threshold set below the actual round-trip transaction cost causes the pipeline to label cost-driven noise as tradeable signal. The labeled dataset then
Fixed-Width Fractional Differencing (FFD) for MetaTrader 5
MQL5 implementation of the fixed-width fractional differencing (FFD) method from López de Prado's Advances in Financial Machine Learning (Chapter 5). Transforms a non-stationary price series into a stationary one while preserving maximum historical memory; output cross-validates against the Python
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Feature Engineering for ML (Part 9): Structural Break Tests in Python for MetaTrader 5
We present a production‑ready implementation of AFML Chapter 17 structural break tests. The module includes Chu-Stinchcombe-White (one-/two-sided), Chow-type DFC, SADF across six models (linear, quadratic, sm poly 1, sm poly 2, sm exp, sm power), plus QADF (q, v) and CADF (q), returning bar-indexed
Feature Engineering for ML (Part 8): Entropy Features in MQL5 for MetaTrader 5
An MQL5 port of four entropy estimators — Shannon, Plug-In, Lempel-Ziv, and Kontoyiannis — operating on the intrabar tick-rule sequence. CopyTicksRange() limits data to the broker's cached tick window, so features apply to recent bars only. The implementation encodes bid-direction ticks from
MetaTrader 5 Machine Learning Blueprint (Part 18): Sequential Bootstrap, Corrected — Clone, Class Erasure, and the Comparison Toolkit for MetaTrader 5
The article diagnoses two defects that neutralize sequential bootstrap during cross‑validation: type erasure of SequentiallyBootstrappedBaggingClassifier and a fold‑level shape mismatch from cloning full samples info sets. It retains the classifier's identity, adds find seq bagging to re‑inject
Feature Engineering for ML (Part 7): Entropy Features in Python for MetaTrader 5
The article provides production-ready entropy estimators (Shannon, plug-in, Lempel–Ziv, Kontoyiannis) operating on tick-rule–encoded sequences. It resolves three correctness and performance issues in the original code, verifies outputs against chapter references, and extends encoding with quantile
Meta-Labeling the Classics (Part 2): Filtering and Sizing ADX Trades for MetaTrader 5
The DI crossover often triggers in ranges where +DI and -DI oscillate without persistence. We build a two-layer hybrid: Optuna's TPE optimizes a regime gate over ADXR threshold, DI lookback, and minimum DI separation to maximize signal precision on a held-out window, then a Random Forest uses eleven
Beyond the Clock (Part 3): Building an Indicator Window for Alternative Bars in MQL5 for MetaTrader 5
AlternativeBarsViewer is a subwindow indicator that renders all ten alternative bar types as color‑coded candles using the same CBarConstructor hierarchy as BarBuilderEA, ensuring identical bars. It supports three data sources (real ticks, synthetic OHLC ticks, or the EA's CSV) and two render modes
Feature Engineering for ML (Part 6): Microstructural Features in MQL5 for MetaTrader 5
The article introduces CMicrostructureFeatures, an MQL5 class for bar‑level microstructure features: Roll spread/impact, Corwin‑Schultz spread and sigma, Kyle's Lambda, Amihud's ILLIQ, and Hasbrouck's Lambda. Calculations rely solely on OHLCV using rolling windows. It clarifies the implications of
Feature Engineering for ML (Part 5): Microstructural Features in Python for MetaTrader 5
This article implements the Chapter 19 microstructure suite in afml.features.microstructure and explains a two-layer design for OHLCV-only and tick-augmented workflows. We cover Roll and Corwin–Schultz spread/volatility, Kyle's, Amihud's, and Hasbrouck's lambdas, VPIN, and bar‑level imbalance
MetaTrader 5 Machine Learning Blueprint (Part 17): CPCV Backtesting — From Python Model to Tick-Level Evidence for MetaTrader 5
We bridge Python-native artifacts to MQL5 for tick-accurate CPCV backtesting. The export script converts the ONNX model, calibrator, feature spec, and path masks to flat files, while the expert advisor rebuilds features, performs ONNX inference with calibration, and trades on real ticks. The
Position Management: Scaling Into Winners With A Falling-Risk Pyramid for MetaTrader 5
We introduce CPyramidBridge, a thin MQL5 layer that maps bet-sizing results to CPyramidEngine. The bridge applies probability to initial lot sizing, enforces a capacity-aware entry gate, promotes add-ons from dynamic divergence, adapts the trailing stop to reserve estimates, and syncs signals on
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Hello, I have been wondering if notifications for article writing could be arranged so that all alerts regarding one article are grouped. It would make it easier to parse when one has multiple articles in progress and reduce unseen messages