Estimation and Model-Based Combination of Causality Networks

95 Pages Posted: 2 Feb 2017

See all articles by Giovanni Bonaccolto

Giovanni Bonaccolto

University "Kore" of Enna

Massimiliano Caporin

University of Padua - Department of Statistical Sciences

Roberto Panzica

Goethe University Frankfurt - Research Center SAFE

Date Written: January 31, 2017

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.

Keywords: Granger Causality, Quantile Causality, Multi-Layer Network, Network Combination

JEL Classification: C58, C31, C32, G01

Suggested Citation

Bonaccolto, Giovanni and Caporin, Massimiliano and Panzica, Roberto, Estimation and Model-Based Combination of Causality Networks (January 31, 2017). SAFE Working Paper No. 165. Available at SSRN: https://ssrn.com/abstract=2909585 or http://dx.doi.org/10.2139/ssrn.2909585

Giovanni Bonaccolto (Contact Author)

University "Kore" of Enna ( email )

Viale delle Olimpiadi
Enna, 94100
Italy

Massimiliano Caporin

University of Padua - Department of Statistical Sciences ( email )

Via Battisti, 241
Padova, 35121
Italy

Roberto Panzica

Goethe University Frankfurt - Research Center SAFE ( email )

(http://www.safe-frankfurt.de)
Theodor-W.-Adorno-Platz 3
Frankfurt am Main, 60323
Germany

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