This study investigates the effectiveness of forecasting energy commodity prices using Artificial Intelligence-based models that account for the transition to cleaner energy sources during periods of significant market instability, such as the …
Amidst rising concerns over climate change, the global shift from oil-powered vehicles to lithium-powered electric vehicles marks a critical pivot in the energy sector. This transition holds profound implications for the traditional dominance of oil …
This paper analyzes the returns and volatility connectedness between oil prices and Eurozone sector returns during the global financial crisis. We employ the TVP-VAR frequency connectedness approach with daily data of Brent prices and 18 Eurozone …
This study investigates the dynamic connectedness between equity and cryptocurrency markets using the Granger Causality Network and the Wavelet Coherence approaches. Using time series data from July 2021 to January 2023, results indicate that the …
This research aims to investigate the propagation of extreme downside risk, commonly referred to as tail risk, within commodity markets using an innovative CAViaR-based connectivity model. We also evaluate the influence of various crises, including …