Unveiling the Role of Industries for European Financial Stability. Insights From the Energy Sector

Abstract

Extensive analysis of intertwinement with other industries caused the energy sector to gain momentum in the recent economic literature. This paper aims to create an indicator that captures the impact of financial stability for energy companies on all other industrial groups. To this end, we use daily data from 2007 until the end of 2021 to compute financial stability metrics for all European companies from the STOXX 600 index. The main contribution of our study is to harness the neural network forecasting power to predict extreme levels of this impact. We motivate this choice with evidence from the literature that documents the improved performance of these methods in predicting crises. Our methodological approach also employs an outlier detection algorithm based on copula (COPOD) to identify situations when the energy sector substantially impacts other industries and develop a framework to predict out-of-sample situations. We found evidence that the Deep Renewal model has superior forecasting accuracy to the standard Croston model. The main conclusion is that the design of this methodological framework allows authorities to monitor the impact of shocks produced by the energy sector on financial stability at the European level and undertake strategic management actions.