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...

In this study, we propose a novel quantile frequency connectedness approach that enables the investigation of propagation mechanisms by virtue of the quantile and frequency. This approach allows to analyze different frequencies given a particular quantile or analyze different quantile...

In this study, we enhance the dynamic connectedness measures originally introduced by Diebold and Yılmaz (2012, 2014) with a time-varying parameter vector autoregressive model (TVP-VAR) which predicates upon a time-varying variance-covariance structure. This framework allows to capture possible...

In this paper, we estimate an asymmetric frequency TVP-VAR frequency connectedness model and further employ aggregated connectedness measures in order to identify whether cryptocurrencies drive investor sentiment. We find pronounced and time-varying interconnectedness within the cryptocurrency...

In this study, we introduce a novel framework of partial connectedness measures with which we investigate contagion dynamics between different types of oil price shocks and exchange rates. On general principles, oil price shocks are persistent net transmitters of shocks within the network....