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Modeling Systemic Risk with Markov Switching Graphical SUR Models

49 Pages Posted: 14 Dec 2014 Last revised: 18 May 2017

Daniele Bianchi

University of Warwick, Warwick Business School

Monica Billio

Ca Foscari University of Venice - Dipartimento di Economia

Roberto Casarin

University Ca' Foscari of Venice - Department of Economics

Massimo Guidolin

Bocconi University - Department of Finance

Date Written: June 19, 2015

Abstract

We propose a Markov Switching Graphical Seemingly Unrelated Regression (MS-GSUR) model to investigate time-varying systemic risk based on a range of multi-factor asset pricing models. Methodologically, we develop a Markov Chain Monte Carlo (MCMC) scheme in which latent states are identified on the basis of a novel weighted eigenvector centrality measure. An empirical application to the S&P100 constituents shows that cross-firm connectivity significantly increased over the period 1999-2003 and the financial crisis of 2008-2009. Finally, we provide evidence that firm-level centrality does not correlate with market values and is instead positively linked to realized financial losses.

Keywords: Markov Regime-Switching, Weighted Eigenvector Centrality, Graphical Models, MCMC, Systemic Risk, Network Connectivity

JEL Classification: C11, C15, C32, C58

Suggested Citation

Bianchi, Daniele and Billio, Monica and Casarin, Roberto and Guidolin, Massimo, Modeling Systemic Risk with Markov Switching Graphical SUR Models (June 19, 2015). Available at SSRN: https://ssrn.com/abstract=2537986 or http://dx.doi.org/10.2139/ssrn.2537986

Daniele Bianchi (Contact Author)

University of Warwick, Warwick Business School ( email )

Gibbet Hill Rd
Coventry, CV4 7AL
Great Britain

HOME PAGE: http://whitesphd.com/

Monica Billio

Ca Foscari University of Venice - Dipartimento di Economia ( email )

Cannaregio 873
Venice, 30121
Italy

HOME PAGE: http://www.unive.it/persone/billio

Roberto Casarin

University Ca' Foscari of Venice - Department of Economics ( email )

San Giobbe 873/b
Venice, 30121
Italy
+39 030.298.91.49 (Phone)
+39 030.298.88.37 (Fax)

HOME PAGE: http://venus.unive.it/r.casarin/

Massimo Guidolin

Bocconi University - Department of Finance ( email )

Via Roentgen 1
Milano, MI 20136
Italy

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