Authors

Ntebogang Dinah Moroke

Abstract

Conventional financial risk systems treat physical infrastructure as a fixed, frictionless background, an assumption that breaks down when electricity supply becomes binding. Markets then enter metabolic arrest : information-processing capacity collapses under a documented inversion between cross-asset correlation and entropy. TENSORnet (Temporal Entropy-aware Network for Systemic Onset Recognition) is a thermodynamically motivated protocol that fuses a VIX-calibrated inhibitory gate, grounded in Landauer’s energy-information bound, with cross-asset Shannon entropy. Rather than assuming architectural value, this study directly tests whether the protocol provides classification value beyond infrastructure-stage information alone. TENSORnet—applied to 2,838 JSE trading days (January 2015–April 2026) across seven asset classes under South Africa’s load-shedding crisis, using a three-way train/validation/test split motivated by the documented escalation history (Stage 4 first occurred February 2019)—achieves F1 = 99.55% and AUC = 0.9996 on the held-out test period (2020–2026, 1,581 days) at the primary Stage 3+ definition; a DeLong test finds this statistically indistinguishable from infrastructure-stage information alone ( p = 0.326 ) . Ablation confirms that the gate is load-bearing relative to purely market-based alternatives (AUC collapses to 0.568 without it; GARCH and network-connectedness achieve AUC ≤ 0.62), and the entropy layer outperforms a volatility-based substitute and a gradient-boosted benchmark under matched small-sample conditions, though it does not exceed the stage information itself. A cross-scale divergence signal, proposed as an advance-warning mechanism, is directly tested and does not survive (95% false alarm rate)—reported as a negative result. The densification paradox is empirically supported and confirmed via permutation testing against a mechanical-artefact null: rising cross-asset correlation accompanies falling entropy under infrastructure stress ( r = − 0.468 at Stage 4+ vs. r = − 0.184 at Stage 0, p < 0.001 )—this study’s most robust independent finding. A port-Hamiltonian neural ODE extension specifies an unvalidated conceptual pathway for future research. This study offers a disciplined example of testing, rather than assuming, whether a thermodynamically motivated architecture provides value beyond simpler alternatives, reporting results honestly where they complicate the original hypothesis.

Citation

  • Journal: Frontiers in Physics
  • Year: 2026
  • Volume: 14
  • Issue:
  • Pages: 1943577
  • Publisher: Frontiers Media SA
  • DOI: 10.3389/fphy.2026.1943577

BibTeX

@article{Moroke_2026,
  title={{TENSORnet: a thermodynamically motivated entropy protocol for infrastructure-induced metabolic arrest detection in cross-asset financial networks}},
  volume={14},
  ISSN={2296-424X},
  DOI={10.3389/fphy.2026.1943577},
  journal={Frontiers in Physics},
  publisher={Frontiers Media SA},
  author={Moroke, Ntebogang Dinah},
  year={2026}
}

Download the bib file

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