NetworkMomentum

A research paper's network-momentum trend-following strategy, implemented entirely in MQL5.

Companion code for the MQL5 article: https://www.mql5.com/en/articles/23763

What it does

Momentum does not stay inside one market. If A reliably leads B, then A's trend carries information about B's next move. The strategy trades that spillover.

Three pieces make it work. Derivative Dynamic Time Warping detects lead-lag relationships between markets, comparing shapes rather than levels. A convex optimisation then learns a weighted graph from those relationships, so the network is fitted rather than hand-drawn. Momentum is propagated across that graph and turned into a signal.

Returns are volatility-scaled before any of this, so a loud market does not dominate the network for the wrong reason.

NM_Native.mq5 is the Expert Advisor. The article covers the Strategy Tester results, including where the approach struggles.

Layout

Include/NetworkMomentum/NM_Config.mqh        configuration
Include/NetworkMomentum/NM_Matrix.mqh        matrix helpers
Include/NetworkMomentum/NM_Data.mqh          multi-symbol data handling
Include/NetworkMomentum/NM_Symbols.mqh       the basket
Include/NetworkMomentum/NM_Momentum.mqh      volatility scaling and oscillators
Include/NetworkMomentum/NM_DDTW.mqh          derivative dynamic time warping
Include/NetworkMomentum/NM_GraphLearner.mqh  convex graph learning
Include/NetworkMomentum/NM_Engine.mqh        ensemble, propagation, signal
Include/NetworkMomentum/NM_Live.mqh          chart-side layer
Experts/NetworkMomentum/NM_Native.mq5        the Expert Advisor

Put every basket symbol in Market Watch before running, since the EA pulls history for all of them.

Disclaimer

Educational code. Past behaviour of any model or dataset says nothing about future results. Test on your own data and broker conditions before drawing conclusions.