Regularization approach for network modeling of German power derivative market

In this paper we propose a regularization approach for network modeling of German power derivative market. To deal with the large portfolio, we combine high-dimensional variable selection techniques with dynamic network analysis. The estimated sparse interconnectedness of the full German power derivative market, clearly identify the significant channels of relevant potential risk spillovers. Our empirical findings show the importance of interdependence between different contract types, and identify the main risk contributors. We further observe strong pairwise interconnections between the neighboring contracts especially for the spot contracts trading in the peak hours, its implications for regulators and investors are also discussed. The network analysis of the full German power derivative market helps us to complement a full picture of system risk, and have a better understanding of the German power market functioning and environment. •This paper proposes a regularization approach for dynamic network modeling of German power derivative market.•We clearly identify the significant channels of relevant potential risk spillovers in German power derivative market.•Our empirical results show the importance of interdependence between contract types, and identify the main risk contributors.•We observe strong pairwise interactions between neighboring contracts especially for the spot contracts traded in peak hours.•We aim to complement a full picture of system risk, its implications for regulators and investors are discussed.