A data envelopment analysis and local partial least squares approach for identifying the optimal innovation policy direction

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Built-in challenges within the supervisory architecture of the Eurozone

We analyse a sample of significant European financial intermediaries that fall under the Single Supervisory Mechanism, which is part of the existing institutional supervisory architecture of the Eurozone. Theory suggests that herding among financial intermediaries raises cross-sectional correlations and has negative implications for systemic risk. Empirically, herding behaviours are associated with clusters identifying commonalities in asset allocations and risk strategies. By adopting a novel clustering approach, we analyse whether some pre-determined classifications and criteria associated with the current supervisory framework can capture financial intermediaries’ herding behaviour. We find that simple classifications and criteria, which are less likely to be policy-biased, can be more efficient than complex ones when it comes to identifying commonalities posing the highest threats to systemic risk. The findings confirm the need for a macro- rather than micro-prudential approach to financial supervision by highlighting the importance of using a supervisory toolkit that includes indicators with a stronger cross-sectional and network dimension. Our methodology can serve as a final consistency check for quantitative-based classifications and criteria employed by supervisory authorities. © 2021, The Author(s), under exclusive licence to Springer Nature Limited

Cyclic stroke mortality variations follow sunspot patterns

Mapping time-structures is a burgeoning scientific field enriching the (P4) medicine models. Local evidence in Mediterranean populations is underinvestigated. The Censed stroke-related death events (D) in the largest East-Mediterranean port (Piraeus), during (1985-1989), when local population had diet and genetic homogeneity-been interrupted by the immigration into Greece in 1990s, and Sunspot numbers indexed by Wolf numbers (Rz) (1944-2004), were evaluated using Fast Fourier Analysis and Singular Spectrum Analysis in MATLAB. D were turned with fluctuations >35% in Rz. A non-anthropogenic 6.8 days cycle was recognized. This study may be taken into consideration in future public health planning and chronotherapy evaluations. © 2020 Geronikolou S et al

Built-in challenges within the supervisory architecture of the Eurozone

We analyse a sample of significant European financial intermediaries that fall under the Single Supervisory Mechanism, which is part of the existing institutional supervisory architecture of the Eurozone. Theory suggests that herding among financial intermediaries raises cross-sectional correlations and has negative implications for systemic risk. Empirically, herding behaviours are associated with clusters identifying commonalities in asset allocations and risk strategies. By adopting a novel clustering approach, we analyse whether some pre-determined classifications and criteria associated with the current supervisory framework can capture financial intermediaries’ herding behaviour. We find that simple classifications and criteria, which are less likely to be policy-biased, can be more efficient than complex ones when it comes to identifying commonalities posing the highest threats to systemic risk. The findings confirm the need for a macro- rather than micro-prudential approach to financial supervision by highlighting the importance of using a supervisory toolkit that includes indicators with a stronger cross-sectional and network dimension. Our methodology can serve as a final consistency check for quantitative-based classifications and criteria employed by supervisory authorities