Causality is a widely-used concept in theoretical and empirical economics. The recent financialeconomics literature has used the standard Granger causality to detect for the presenceof contemporaneous links among financial institutions, that, in turn, determine a networkstructure. Subsequent studies have combined the estimated networks with traditional pricingor risk measurement models to improve their fit to empirical data. In this paper, we providetwo contributions. First, we show how to use a linear factor model as a device for estimatinga combination of several networks that monitor the links across variables from differentviewpoints. Second, we highlight the advantages of combining quantile-based methods withthe Granger causality when the focus is on risk propagation. The empirical evidence supportsour contributions.
BONACCOLTO Giovanni;
CAPORIN Massimiliano;
PANZICA Roberto;
2019-11-18
ELSEVIER SCIENCE BV
JRC117994
0927-5398 (online),
https://www.sciencedirect.com/science/article/pii/S0927539819300738,
https://publications.jrc.ec.europa.eu/repository/handle/JRC117994,
10.1016/j.jempfin.2019.08.008 (online),
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