Networks in Risk Spillovers: A Multivariate GARCH Perspective

Abstract

We propose a spatiotemporal approach for modeling risk spillovers using time-varying proximity matrices based on observable financial networks and introduce a new bilateral specification. We study covariance stationarity and identification of the model, and analyze consistency and asymptotic normality of the quasi-maximum-likelihood estimator. We show how to isolate risk channels and we discuss how to compute target exposure able to reduce system variance. An empirical analysis on Euro-area cross-country holdings shows that Italy and Ireland are key players in spreading risk, France and Portugal are the major risk receivers, and we uncover Spain's non-trivial role as risk middleman.

Information Flow in Times of Crisis: The Case of the European Banking and Sovereign Sectors

“…The empirical work in this paper uses data for 5-year credit default swap (CDS) spreads as liquid proxies for credit risk; see also Pan and Singleton (2008), Duca and Peltonen (2013), Kalbaskaa and Gatkowskib (2012), Billio et al (2017). The CDS is a financial swap agreement that the buyer in the CDS contract (usually the creditor of the reference loan) pays a periodic fee to the seller until the contract matures or a credit event occurs.…”