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The paper studies salient features of systemic risk in a sample of 22 European (EU and non-EU) countries during January 2010–March 2016. Building on a novel dataset and conducting an empirical horse race, we determine pivotal systemic risk measures for the sample countries. SRISK and volatility indicator tend to lead other metrics, followed by leverage. In contrast to the conventional wisdom, composite systemic risk measures aggregated with the aid of principal and independent component analysis perform worse. The leading systemic risk measures exhibit a high degree of connectedness. The VIX index, TED spread, the Composite Index of Systemic Stress (CISS) and long-term interest rates underlie their dynamics. Two clusters within the sample are identified, with CISS and long-term interest rates being crucial to distinguish between them. There is only scarce evidence for causal linkages between systemic risk and industrial production in the sample countries, based on the concurring results of standard and nonparametric Granger causality tests. [ABSTRACT FROM AUTHOR]

In the paper we suggest the use of amplitude correlation coefficients (ACCs) and phase-locking values (PLVs) in examining business cycle synchronization. The quantities are calculated on the basis of instantaneous amplitudes and phase differences, which are computed here with the help of the non-decimated discrete analytic wavelet transform. We show that the coefficients constitute an interesting add-in to the statistical apparatus of examining business cycle synchronization. The PLVs correct the information provided by the coherency and correlation coefficients for the influence of amplitude changes and are of use in examining phase synchronization of business cycles, which is important in forecasting the effectiveness of a common monetary policy. By contrast, the ACCs are based solely on amplitude information and have the interpretation of phase-adjusted correlation coefficients, which can be used to evaluate stabilization policies or to forecast these policies' effectiveness. The methodology is applied to examine cyclical synchronization of 20 European Union (EU) countries. We show, among other things, that during the run-up to the euro both amplitude and phase synchronization increased, with the former tending to change more rapidly. Furthermore, for the new EU members an EU effect is identified in both types of cyclical synchronization with the euro area. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this paper is to do an empirical analysis assessing whether banks highly involved into trading activities show specific business model choices. Key factors in the analysis are a proper measure for trading activities and a consistent classification of banks in terms of business choices. Design/methodology/approach – We investigate three measures for trading activities proposed by regulators in the context of bank structural reform in Europe. Through robust statistics we identify the key trading players and classify banks into a limited number of business model clusters, relying on a set of balance sheet and income statement indicators. Findings – Using a sample of 100 European banks in 2007-2012, results show that the measures identify similar, but not identical, sets of banks highly involved into trading. The measure proposed by the European Commission selects fewer banks and is more consistent over time. The business model analysis identifies six rather stable clusters, from small-medium retail-focused banks to very large investment groups. The measures coherently identify as key trading players the largest investment groups and select very few retailed focused banks. Differences among measures arise for very large retail-diversified and medium/large wholesale banks. Originality/value – These results could feed the debate on which measures for trading regulators could consider depending on the target of the reform they would implement. For instance we show that the measure proposed by the European Commission selects less well capitalized retail-diversified banks compared to the others. [ABSTRACT FROM AUTHOR]