Estimation and Model-Based Combination of Causality Networks
Authors: Giovanni Bonaccolto (University of Enna), Massimiliano Caporin (University of Padova), Roberto Panzica (Goethe University)
Title: Estimation and Model-Based Combination of Causality Networks
Abstract: Causality is a widely-used concept in theoretical and empirical economics. The recent financial economics literature has used Granger causality to detect the presence of contemporaneous links between financial institutions and, in turn, to obtain a network structure. Subsequent studies combined the estimated networks with traditional pricing or risk measurement models to improve their fit to empirical data. In this paper, we provide two contributions: we show how to use a linear factor model as a device for estimating a combination of several networks that monitor the links across variables from different viewpoints; and we demonstrate that Granger causality should be combined with quantile-based causality when the focus is on risk propagation. The empirical evidence supports the latter claim.