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Do tail events in the oil market trigger extreme responses by the clean-energy financial market (and vice versa)? This paper investigates the relationship between oil price and clean-energy stock with a novel methodology, namely extreme events study. The aim is to investigate an asymmetry effect between the response to good versus bad days. The results show how the two markets influence each other more negatively, i.e., extreme negative events significantly impact the other market. Furthermore, we document how the impact of the shock transmitted by oil prices to clean-energy stocks is less than the amount of shock transmitted oppositely. These findings have important implications for investor and renewable energy policies.

Purpose The purpose of this paper is to study the evolution of financial contagion between Eurozone banks, observing the credit default swaps (CDSs) market during the period 2009–2017. Design/methodology/approach The authors use a dynamic spatial Durbin model that enables to explore the direct and indirect effects over the short and long run and the transmission channels of the contagion. Findings The results show how contagion emerges through physical and financial market links between banks. This finding implies that a bank can fail because people expect other related financial institutions to fail as well (self-fulfilling crisis). The study provides statistically significant evidence of the presence of credit risk spillovers in CDS markets. The findings show that equity market dynamics of “neighbouring” banks are important factors in risk transmission. Originality/value The research provides a new contribution to the analysis of EZ banking risk contagion, studying CDS spread determinants both under a temporal and spatial dimension. Considering the cross-dependence of credit spreads, the study allowed to verify the non-linearity between the probability of default of a debtor and the observed credit spreads (credit spread puzzle). The authors provide information on the transmission mechanism of contagion and, on the effects among the largest banks. In fact, through the study of short- and long-term impacts, direct and indirect, the paper classify banks of systemic importance according to their effect on the financial system.

China has accelerated its banking sector reform in recent years, paying particular attention to non-performing loans (NPLs). The paper’s scope is to analyse the relationship between NPLs and macroeconomic variables in China using quarterly data from 2008/Q1 to 2021/Q1 applying wavelet analysis, which allows the study to scan both short- and long-term causal relationships and connections. The analysis produces interesting results. The GDP does not appear to be as important and as much of a driving force in the dynamics of NPLs as in other emerging countries. On the other hand, inflation shows a highly dynamic dependence on NPLs as it varies over time; however, the most interesting data is the relationship between NPLs and economic policy uncertainty. In the short term, the variables are in phase. In the long term, an increase of EPU has a reduction effect on NPLs, indicating that it affects commercial bank loan sizes by reducing enterprise demand for and bank supply of credit resources.