47 lines
1.9 KiB
Markdown
47 lines
1.9 KiB
Markdown
# NetworkMomentum
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A research paper's network-momentum trend-following strategy, implemented
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entirely in MQL5.
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Companion code for the MQL5 article: https://www.mql5.com/en/articles/23763
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## What it does
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Momentum does not stay inside one market. If A reliably leads B, then A's trend
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carries information about B's next move. The strategy trades that spillover.
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Three pieces make it work. Derivative Dynamic Time Warping detects lead-lag
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relationships between markets, comparing shapes rather than levels. A convex
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optimisation then learns a weighted graph from those relationships, so the
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network is fitted rather than hand-drawn. Momentum is propagated across that
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graph and turned into a signal.
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Returns are volatility-scaled before any of this, so a loud market does not
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dominate the network for the wrong reason.
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`NM_Native.mq5` is the Expert Advisor. The article covers the Strategy Tester
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results, including where the approach struggles.
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## Layout
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```
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Include/NetworkMomentum/NM_Config.mqh configuration
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Include/NetworkMomentum/NM_Matrix.mqh matrix helpers
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Include/NetworkMomentum/NM_Data.mqh multi-symbol data handling
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Include/NetworkMomentum/NM_Symbols.mqh the basket
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Include/NetworkMomentum/NM_Momentum.mqh volatility scaling and oscillators
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Include/NetworkMomentum/NM_DDTW.mqh derivative dynamic time warping
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Include/NetworkMomentum/NM_GraphLearner.mqh convex graph learning
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Include/NetworkMomentum/NM_Engine.mqh ensemble, propagation, signal
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Include/NetworkMomentum/NM_Live.mqh chart-side layer
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Experts/NetworkMomentum/NM_Native.mq5 the Expert Advisor
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```
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Put every basket symbol in Market Watch before running, since the EA pulls
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history for all of them.
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## Disclaimer
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Educational code. Past behaviour of any model or dataset says nothing about
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future results. Test on your own data and broker conditions before drawing
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conclusions.
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