The work performed during the EARLINESS.eu project focussed on new scientific contributions and the realization, jointly with the Systemic Risk Lab (SAFE), of a platform that makes available on a regular basis systemic risk measures proposed by literature and developed during the project. First, the project proposed a construction of an overall meta-index for the measurement of systemic risk based on a Sparse Principal Component Analysis of main systemic risk measures, which ultimately aims to provide an index with a more stable dynamic and with an explicit link to severe economic recessions. Second, Dynamic Quantile Factor models were effectively employed. The proposed model is based on the use of the Dynamic Factor Quantiles model (DFQ) which considers dynamics in the quantiles as a function of latent variables. DQF models are then employed to extract the latent signal of systemic risk from a panel of financial institutions belonging to a given financial system. Third, the project introduces a novel Bayesian model to estimate multi-quantiles in a dynamic framework. The main innovation lies in the assumption that the quantile level of a vector of response variables depends on macroeconomic variables as well as on latent factors. The analysis focuses on equity market returns and macroeconomic variables to analyse the dynamic evolution of spillovers in individual Value-at-Risks. Fourth, the project analyses the contagion channels of the European financial system through the stochastic block models, which group homogeneous connectivity patterns among the financial institutions, thus allowing to describe in a compact way the shock transmission mechanisms of the network. Fifth, a Bayesian approach is proposed to the problem of variable selection and shrinkage in high dimensional sparse regression models where the regularisation method is an extension of a previous LASSO model, which allows to include a large number of institutions improving the identification of the relationship. Findings show that changes in the shape of the out-degree distribution of the network over time represent a responsive indicator of the global financial system and a significant predictor of market returns. Sixth, new measures of network connectivity are proposed, that are Von Neumann entropies and disagreement persistence indexes, using the spectrum of normalized Laplacian and Diplacian. Seventh, an extension of the study of the rate of convergence to a consensus of autonomous agents on an interaction network is proposed by introducing antagonistic interactions and thus a signed network. Finally, the project contributed directly to the realization of the Systemic Risk Dashboard (SRDB) platform, providing the code for the systemic risk measures and the structure code (reading, cleaning and computation of the data) using parallelization in MATLAB to automatize routines. The SRDB is regularly updated and upgrades with new measures are already scheduled. The web-application has been realized with the support of the SAFE Data Center. Dissemination activities of the EARLINESS.eu project involved conferences and workshops related to finance, financial econometrics and statistical.
