The global energy crisis and rising climate concerns are encouraging transition to a more sustainable economy. Replacing carbon-fossil fuels with renewable energy, reducing the impact of climate change, is an essential requirement for any energy transition to a zero-carbon economy, with the ultimate goal of reaching climate neutrality. Monitoring energy prices has become increasingly important for analysts, policy makers and businesses to tackle the current situation by increasing the integration of renewable energy sources, strengthening the resilience of the energy system to future price shocks and reducing its dependence on fossil fuel imports, as well as improving the affordability of energy for consumers. Following Chan and Maheu (2002) and Chang (2012), we set up a copula-based ARJI-GARCH model to investigate the time-varying and non-linear dependence between renewable and non-renewable energies in the European energy market. By applying the model to the European Renewable Energy Index and the MSCI Europe Energy Index, we show that the ARJI-GARCH specification is able to provide reliable forecasts and an effective tail risk assessment for the energy sector returns. We then use the ARJI-GARCH forecasts to analyse their co-movement structure by applying and comparing different copula specifications. Keywords: ARJI-GARCH copula model, Non-linear dependence, Value at Risk, Energy markets, Renewable energy
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