IST02-IST03 JSE-Eskom Infrastructure-Coupled Financial Network Dataset
Description
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.
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).
Series information (English)
Derived empirical series and replication code supporting the paper "METRIC: Trophic Cascade Governance of Resource-Constrained Layered Hypergraphs" (Moroke, 2026, Scientific Reports, under revision).
CONTENTS
--------
METRIC_daily_derived_series.csv — 4,018 daily observations (January 2015 – December 2025) of six derived variables computed from the JSE transaction hypergraph: Fiedler eigenvalue λ₂(t), realised volatility σ_t, Shannon entropy S(t), Von Neumann entropy S_VN(t), Trophic Collapse Index TCI(t), Betti-1 cycle count β₁(t), network density ρ(t), arrest coefficient α(t), and governance regime classification. These are the series underlying all main-text tables and figures.
01_download_jse_data.py — Python script to reconstruct the 87 JSE equity price series (2015–2025) from Yahoo Finance using yfinance. Raw prices cannot be redistributed by the authors under Yahoo Finance terms; this script allows any researcher to reconstruct the identical inputs.
02_basic_stats.py — Python script computing descriptive statistics, ADF/KPSS stationarity tests, ARCH-LM, Ljung-Box, Granger causality tests, per-ticker return statistics, correlation matrix, and four publication-quality figures (replicates paper Figure 2).
DATA SOURCES
------------
JSE equity prices: Yahoo Finance (via yfinance). Run 01_download_jse_data.py to reconstruct.
Eskom load-shedding stages: beyarkay/eskom-calendar (https://github.com/beyarkay/eskom-calendar) and NERSA (https://www.nersa.org.za).
SARB ZAR/USD exchange rate: https://www.resbank.co.za
SARB OTC derivative data: subject to regulatory confidentiality; aggregate statistics reported in Supplementary Table S1 of the paper.
NOTE ON MANUSCRIPT CODE
------------------------
The TGN-Hypergraph model code will be deposited here upon formal acceptance of the manuscript, consistent with journal policy.
Notes
This repository contains the analysis pipeline and supporting datasets for the manuscript "HK-DeepIV: Heat-Kernel Causal Identification and Early-Warning Signals for Curvature-Induced Interference in Financial Correlation Networks," submitted to Frontiers in Big Data (Big Data Networks section).
Data: daily price panel for 66 Johannesburg Stock Exchange (JSE) tickers, 2015–2025 (2,832 trading days), paired with hourly Eskom load-shedding stage records, 2022–2025 (35,064 hours, no gaps).
Code: a four-stage Python pipeline — data cleaning, statistical diagnostics (stationarity, normality, autocorrelation, ARCH/GARCH), the full HK-DeepIV training procedure (heat-kernel diffusion, two-stage gradient-blocked causal estimation, Fiedler/Ricci curvature diagnostics), and baseline comparator training (Flat DeepIV, GCN+IV).
All causal identification results in the associated manuscript are reproducible from this repository given the included data and scripts, run in the order documented in README.md.
Files
eskom_stage_2022_2025(2).csv
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Additional details
Additional titles
- Alternative title (English)
- METRIC: Trophic Cascade Governance of Resource-Constrained Layered Hypergraphs — Derived Dataset and Replication Code
- Subtitle (English)
- HK-DeepIV: Analysis Code and Supporting Data for Heat-Kernel Causal Identification in JSE Financial Correlation Networks
Related works
- Is supplement to
- Dataset: 10.5281/zenodo.18925609 (DOI)
Dates
- Available
-
2026-05-25
Software
- Repository URL
- https://github.com/ntebo40/METRIC
- Programming language
- Python
- Development Status
- Active
References
- Moroke, N.D. (2026). METRIC: Trophic Cascade Governance of Resource-Constrained Layered Hypergraphs. Scientific Reports (under revision). Zenodo dataset: https://doi.org/10.5281/zenodo.18925609