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Environmental, social, and governance (ESG) factors are increasingly analysed to identify the risks and opportunities in contemporary economies. The banking sector influences the whole economy through the credit channel and balances its stability. The interplay of these elements motivated our main question, whether ESG scores impact European financial stability, measured for the banking sector. To this aim, we employ the cross-quantilogram methodology, which explores dependences at all levels of the distributions of two random variables. To determine the quantile dependence, we resort to methods of measuring systemic risk (Marginal Expected Shortfall—MES, CoVaR, and ΔCoVaR) for all commercial banks listed on European stock exchanges. While our approach provides a dashboard for analysis of the dependence of financial stability on ESG pillars, our findings indicate that such a connection is valid and cannot be identified with standard approaches that explore average distribution levels. We also document the differences in these impacts across the ESG pillars.

In this article, we aim to study systemic risk spillovers for European energy companies and to determine the spillover network of the energy sector with other economic sectors. To examine the spillovers within the energy sector, we employ three systemic risk measures. We then embed the results of these models into a Diebold–Yilmaz framework. Moreover, we consider an entropy procedure to extract a Bayesian formulation of its systemic risk spillover. This allows us to determine which company in our sample contributes the most to systemic risk, which company is the most vulnerable to systemic risk, and the place of the energy sector within risk networks. Our results reveal the fact that all companies manifest enhanced spillovers during 2008, early 2009, and 2020. These episodes are associated with the dynamics of the global financial crisis and the pandemic crisis. We notice that specific companies are risk drivers in the sector in both times of market turbulence and calm. Lastly, we observe that several economic sectors such as banks, capital goods, consumer services, and diversified financials generate relevant spillovers towards the energy sector.

We investigate the dynamics of systemic risk of European companies using an approach that merges paradigmatic risk measures such as Marginal Expected Shortfall, CoVaR, and Delta CoVaR, with a Bayesian entropy estimation method. Our purpose is to bring to light potential spillover effects of the entropy indicator for the systemic risk measures computed on the 24 sectors that compose the STOXX 600 index. Our results show that several sectors have a high proclivity for generating spillovers. In general, the largest influences are delivered by Capital Goods, Banks, Diversified Financials, Insurance, and Real Estate. We also bring detailed evidence on the sectors that are the most pregnable to spillovers and on those that represent the main contributors of spillovers.

The pattern of financial cycles in the European Union has direct impacts on financial stability and economic sustainability in view of adoption of the euro. The purpose of the article is to identify the degree of coherence of credit cycles in the countries potentially seeking to adopt the euro with the credit cycle inside the Eurozone. We first estimate the credit cycles in the selected countries and in the euro area (at the aggregate level) and filter the series with the Hodrick–Prescott filter for the period 1999Q1–2020Q4. Based on these values, we compute the indicators that define the credit cycle similarity and synchronicity in the selected countries and a set of entropy measures (block entropy, entropy rate, Bayesian entropy) to show the high degree of heterogeneity, noting that the manifestation of the global financial crisis has changed the credit cycle patterns in some countries. Our novel approach provides analytical tools to cope with euro adoption decisions, showing how the coherence of credit cycles can be increased among European countries and how the national macroprudential policies can be better coordinated, especially in light of changes caused by the pandemic crisis.

Concerns to setting an appropriate overall macroprudential policy framework have taken shape at local, regional, and global level since the onset of the global financial crisis. At regional level, a particular case is that of the European Union, given the national-supranational relationship specific to this economic region. The article aims to identify the macroprudential policy condition of the Euro Area candidate countries, by using an index built on some criteria that describe on the one hand, the capacity of macroprudential policy governance and the “activism” of macroprudential authority, and, on the other hand, the degree of compliance with the European Systemic Risk Board (ESRB) recommendations for national macroprudential authorities, given that the countries under review are member states of the European Union. Our findings show that the Euro Area candidate countries have quite different macroprudential policy features, both in terms of its governance and in terms of the “convergence” towards ESRB recommendations. Although the analysis should be extended by adding other relevant criteria, we can assert that it offers an overview of the potential role of the national macroprudential policy as a shock-absorber instrument in the perspective of a future accession to the Euro Area.

The academic literature in the field of financial stability has been developing intensively, especially after the last European financial crisis, spurring the development of various algorithms that spawned different statistical gauges. While many of these indicators gained traction within the industry both from the perspective of financial investors and from the regulators' angle, they are tailored to reveal different facets of the complex idea of stability. This paper investigates the extent to which the spillover measure constructed by Diebold and Yilmaz (2012) is impacted by the long-term component of dynamic conditional correlations computed with MIDAS DCC GARCH methodology. We apply this analysis to the sectoral indices that are components of the European STOXX 600 index and show the correlation pairs with the higher impact on the spillover index.