IST02-IST03 JSE-Eskom Infrastructure-Coupled Financial Network Dataset

Hypergraph edge-weight time series linking 87 JSE-listed securities to 34 Eskom transmission grid nodes (January 2015 to December 2025, T=2870 trading days, 340 hyperedges). Supports IST-02 CASCADEnt/VORTEX and IST-03 PHYSAN research series by Prof. N.D. Moroke, North-West University, South Africa. This dataset supports the paper "Infrastructure-Induced Geometric Compression in an Emerging Financial Market" (Moroke, 2026, Emerging Markets Review, under review). Contents:- eskom_stages_2015_2026.csv: Daily peak load-shedding stage (integer 0–6) for South Africa, 1 January 2015 to 30 April 2026. Sources: Eskom published schedules, CSIR energy reports, EskomSePush archive.- eskom_stages_trading_days.csv: Business-day version of the above, forward-filled for weekends and public holidays.- jse_panel.csv: Daily adjusted closing prices for 15 JSE Top40 securities, January 2015 to April 2026 (Yahoo Finance).- shredi_combined.csv: Final merged analysis dataset — 7 asset return series plus Eskom stage and regime classification, N=2,838 trading days.- shredi_7asset_pipeline.py: Complete reproducible Python pipeline producing all results in the paper.- shredi_all_results.json: All numerical results from pipeline.- build_eskom_zenodo.py: Script to rebuild the Eskom stage series from documented public record. This dataset also supports the paper: Moroke, N.D. (2026). TENSORnet: A Physics-Informed Entropy Protocol for Infrastructure-Induced Metabolic Arrest Detection in Cross-Asset Financial Networks. Computation (MDPI), under review. Moroke, N. D. TENSORnet: A Physics-Informed Entropy Protocol for Infrastructure-Induced Metabolic Arrest Detection in Cross-Asset Financial Networks. Preprints 2026, 2026051670. https://doi.org/10.20944/preprints202605.1670.v1 The TENSORnet paper uses the JSE panel data (jse_panel.csv), Eskom load-shedding stages (eskom_stages_trading_days.csv), and the hypergraph edge-weight time series to construct the Topological Entropy Network Stress Operator and validate metabolic arrest detection across 87 JSE securities coupled to 34 Eskom transmission nodes over T=2,870 trading days (January 2015 – December 2025). This dataset also supports: Moroke, N.D. (2026). Interpretable Machine Learning Reveals Jamming Physics in Infrastructure-Constrained Markets: The MERI Framework. Modelling (MDPI), under review. Uses jse_7asset_returns_2015_2026.csv for EGARCH-GED calibration and eskom_stages_trading_days.csv as the infrastructure stress target (seed=42 simulation). DOI: 10.5281/zenodo.20008530 This dataset also supports: Moroke, N.D. (2026). Interpretable Machine Learning Reveals Jamming Physics in Infrastructure-Constrained Markets: The MERI Framework. Modelling (MDPI), under review. Uses: - jse_7asset_returns_2015_2026.csv — EGARCH-GED calibration parameters estimated from these real returns (seed=42 simulation) - eskom_stages_trading_days.csv — infrastructure stress target (Stage 4+) ---