We aim to identify the key drivers of capital depletion under the adverse scenario by reverse engineering the EU-wide stress tests. Our sample consists of the banks that participated in the 2016, 2018 and 2021 EU-wide stress tests. We use three separate sets of variables, namely the bank-specific indicators, the macroeconomic parameters, and the banks’ exposures per loan portfolio. The results demonstrate that banks that are more profitable, more efficient, smaller, more exposed to corporate clients, less exposed to governments and having booked more impairments beforehand experience lower capital depletion under the adverse scenario. In addition, high rates of inflation imply more severe capital reductions, while high GDP leads to mild capital depletion. The asset mix on banks' balance sheets significantly affects the impact of stress test under the adverse scenario. Results are robust to alternative econometric approaches and provide important implications for both supervisors and banks. 

We investigate the effects of non-synchronous trading on volatility spillover for the G-7 equity markets during the Eurozone sovereign debt crisis (ESDC) and the Covid-19 pandemic crisis. For data synchronisation we utilise ΜΑ(1) adjusted return series to estimate the Baba-Engle-Kraft-Kroner (BEKK) and the dynamic conditional correlation (DCC) models. We also consider the use of realised kernels as explanatory variables in the variance equation. In this set up, the contagion effects during crises periods are more perceptible, as the spikes are easier to interpret. We also check the robustness of our main results by applying, wavelet coherence analysis to G-7 major equity indices with realised kernels, as well as local Gaussian correlations (LGC). Our findings suggest the empirical significance of the synchronisation effects for the US and the other G-7 equity markets. We also conclude that realised kernels is an effective tool for mitigating non-synchronous effects. These results underline the significance of quantifying the synchronisation effects in equity markets as well as international portfolio diversification strategies.

Motivated by the increasing demand for alternative assets that can contribute to reducing portfolio risk under inflationary environments, this paper examines the volatility spillovers between collateralized loan obligations (CLOs) and various assets used for protection against inflation, including equities, bonds, crude oil, commodities, gold, bitcoin, shipping and real estate. The applied methodology comprehends the time-varying parameter vector autoregressive (TVP-VAR) model of Antonakakis et al (2020), which relies on the classical Diebold and Yilmaz (2012) approach, for the period from January 1, 2012 to December 31, 2021. The empirical findings show moderate levels of dynamic connectedness; albeit several external shocks, such as the oil price plummet, the US-China trade war and COVID-19, strengthened the interconnection among the assets. Equities, commodities, bitcoin, real estate and gold form the net senders of spillovers, whereas bonds, shipping, CLOs and crude oil absorb the spread shocks. Moreover, we evaluate the hedging ability of CLOs within a portfolio of inflation hedges by estimating hedge ratios and optimal weights by utilizing conditional variance estimations (DCC). Our results indicate that CLOs possess impeccable hedging ability, as the short position in their volatility provides high hedging effectiveness for all investors holding long-positions in the volatility of the remaining assets. Our analysis highlights the importance of CLOs and their relevance to portfolio diversification.