Author
Listed:
- Panayotis Michaelides
(National Technical University of Athens (NTUA))
- Arsenios-Georgios Prelorentzos
(Foundation for Economic and Industrial Research (IOBE))
- Olivier Scaillet
(Swiss Finance Institute - University of Geneva)
- Nikolas Topaloglou
(University of Cyprus - HERMES European Center of Excellence on Computational Finance and Economics)
- Kien Tran
(University of Lethbridge)
Abstract
Digitalization of finance has rapidly transformed the global financial system by introducing new complex technologies. As digital finance grows more interconnected, we show in this work that solar geomagnetic storms, i.e., an exogenous space-weather shock, pose a systemic risk comparable to climate transition pressures, with measurable consequences for Bitcoin (BTC) mining. BTC mining, an energy intensive process reliant on stable electricity and continuous network connectivity, faces increasing risks from solar storms, i.e., geomagnetic disturbances, capable of disrupting power grids and digital infrastructure. This study introduces a novel stepby- step ANN based causality test, leveraging Artificial Neural Networks (ANNs) to examine the nonlinear and dynamic causal relationship between solar storms and BTC mining activity. In this context, we formally establish consistency, asymptotic normality and other useful properties of the proposed ANN estimator. Using daily data from 09/2014 to 01/2023, our multi-horizon analysis identifies statistically significant short-, medium-, and long-term effects, revealing that severe solar storms immediately destabilize networks, delaying transaction confirmations and reducing BTC activity. Furthermore, we quantify the economic significance of these disruptions. During 2015 alone, geomagnetic storms were associated with a cumulative reduction of nearly 3 million BTC in trading activity, equivalent to an estimated value of around 883 million. The findings position solar storms as a critical but overlooked risk factor in digital finance, with implications for cryptocurrency market stability, mining infrastructure resilience, and regulatory oversight.
Suggested Citation
Panayotis Michaelides & Arsenios-Georgios Prelorentzos & Olivier Scaillet & Nikolas Topaloglou & Kien Tran, 2026.
"Natural Hazards and Financial Activity: Evidence from Solar Storms Impact on BTC Mining,"
Swiss Finance Institute Research Paper Series
26-02, Swiss Finance Institute.
Handle:
RePEc:chf:rpseri:rp2602
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JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
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