Exploring dependence structures among European electricity markets: Static and dynamic copula-GARCH and dynamic state-space approaches

In this paper, we examine various characteristics of both base and peak electricity spot prices their returns, investigate dependence structures, extreme co-movements, risk spillovers, integration relationships among the five major European markets, including France, Germany, Netherlands, Spain, UK. To do so, propose a new perspective by applying hybrid ARMA-GARCH, static dynamic copulas, state-space models with Kalman filter to address issue. Based on results ARMA-GJR-GARCH model, first find that there are spillover effects in returns heteroskedastic, asymmetric, leverage negative positive shocks, spikes drops during load periods. Hence, decrease will boom variance can lead much greater increase volatility. Second, exist some extents dependencies, tail co-movements markets based copula models. addition, degree (tail) potential state market stronger higher period than period, implying could or crash together, especially period. Further, copulas show most pairs co-move symmetrically have time-varying dependence, but not appear grow over time. Finally, provide an application copula-GARCH model estimating predicting spillovers across markets. We document high-risk because values Conditional Value-at-Risk ( CoVaR ) large. Also, more integrated market, systematic contribution as indicated ? . Our findings useful information regarding integration, management, asset pricing for • A space deployed. Investigating behaviours returns. Modelling (extreme) Measuring degrees Conducting robustness check different GARCH Applying