We propose multilayer information spillover networks to measure the interconnectedness of
financial institutions by comprehensively considering mean spillover layer, volatility spillover …

We introduce a class of large Bayesian vector autoregressions (BVARs) that allows for non-
Gaussian, heteroscedastic, and serially dependent innovations. To make estimation …

I discuss recent research advances in Bayesian state-space modeling of multivariate time
series. A main focus is on the “decouple/recouple” concept that enables application of state …

Bayesian vector autoregressions are widely used for macroeconomic forecasting and
structural analysis. Until recently, however, most empirical work had considered only small …

This manuscript proposes a new approach for unveiling existing linkages within the
international oil market across multiple driving factors beyond production. A multilayer …

Although tourism mobility spillover continues to be a key indicator for tourism management,
more innovative research must be conducted at the micro level and high sampling …

Sample size reduction ensures a data reduction through the estimation of parametric or
nonparametric models which preserve some data properties. Cardinality reduction includes …

We propose a new measure of disagreement based on connectedness, which generalizes
the disagreement index introduced in Billio et al.(2018). Building on the lifting approach in …

We provide a graph theoretic background for the analysis of financial networks and review
some technique recently proposed for the extraction of financial networks. We develop new …

The tutorials are organized by the COST Action HiTEc that offers the possibility of attending
to the 3 tutorials independently from the conference (see HiTEc Winter Course 2023). HiTEc …