The article examines the interplay between Bitcoin, Fintech, energy consumption, and CO2 emissions, emphasizing the chaotic, nonlinear, and regime-dependent dynamics among these variables. While the study introduces advanced methods such as TAR-TR-GARCH–copula causality, several methodological and interpretive shortcomings raise concerns about its robustness. For instance, the reliance on entropy, chaos, and fractionality measures lacks thorough validation of assumptions, particularly in the presence of nonlinear stationarity and unit root behavior. The integration of datasets spanning diverse timeframes introduces potential biases, as discrepancies in data interpolation and adjustments for holidays and weekends are insufficiently addressed. Similarly, causality claims between Bitcoin, Fintech, and environmental factors appear overstated, with evidence often limited to correlation rather than established causal mechanisms.
Moreover, the study overlooks key contextual factors, such as regional variations in energy use or the differing technological impacts of Bitcoin mining operations. The environmental implications, including CO2 emissions attributed to Bitcoin and Fintech activities, are presented without considering broader systemic factors, such as renewable energy integration or shifts in mining technologies. The paper’s policy recommendations, advocating eco-friendly technologies for digital finance, remain inadequately supported by actionable insights into feasibility or implementation pathways.
Significant discrepancies also arise in the reported tail dependencies and volatility patterns across regimes. For example, the interpretation of contagion effects and asymmetries lacks critical examination of model sensitivity and threshold parameter robustness, raising doubts about the generalizability of results. While the authors claim evidence of chaos and long-term dependence, the chaotic dynamics inferred from Lyapunov exponents and entropy measures could reflect noise or model overfitting rather than inherent system complexity.
The paper’s methodological framework would benefit from greater scrutiny, including expanded tests for robustness, validation of key results against field data, and cross-referencing findings with established studies. Addressing these limitations and incorporating a broader set of sustainability and policy variables could enhance its relevance to decision-makers. Future research should prioritize practical frameworks for mitigating energy and environmental impacts in Fintech, integrating empirical insights and regional nuances into the analysis for a more grounded understanding of the digital finance ecosystem’s sustainability challenges.