We investigate connectedness within a network of environmental indices and crude oil by utilizing state-of-the-art empirical methods. Focusing on the relevance of both mean and volatility dynamics, we find that mean dynamics persistently account for less than 5% of overall dynamics implying...

In this study, we examine the propagation of return-spillovers within a network comprising various Islamic sectoral stocks and the price of Brent crude oil. To achieve that, we extend the work of Antonakakis et al. (2020a), by introducing measures of asymmetric dynamic connectedness based on a...

This study investigates the dynamic transmission mechanism between COVID-19 news sentiment (Google Trends Index), and S&P100, crude oil and gold volatility indices using the recently developed time-varying parameter vector autoregressive (TVP-VAR) based extended joint connectedness approach...

We use the conditional autoregressive value at risk (CAViaR) model in combination with the time-varying parameter vector autoregressive (TVP-VAR) based connectedness approach to study the systematic tail risk transmission considering two types of crude oil (Brent and WTI) and also four refined...

We investigate volatility contagion across G7 stock markets and the market for crude oil for the period between 2007 and 2021. Following the work of Balcilar et al. (2021), we utilise the TVP-VAR extended joint connectedness method and compare results to the standard TVP-VAR method that...