2011
DOI: 10.21799/frbp.wp.2011.45
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On the Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms

Abstract: We propose several connectedness measures built from pieces of variance decompositions, and we argue that they provide natural and insightful measures of connectedness among financial asset returns and volatilities. We also show that variance decompositions define weighted, directed networks, so that our connectedness measures are intimately-related to key measures of connectedness used in the network literature. Building on these insights, we track both average and daily time-varying connectedness of major U.… Show more

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Cited by 54 publications
(153 citation statements)
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“…We further normalized ← θ i j H using Equation (4) following Pesaran and Shin (1998). The resulting forecast error variance decompositions can be used to define weighted, directed, and time-varying networks (Diebold & Yilmaz, 2014). The resulting forecast error variance decompositions can be used to define weighted, directed, and time-varying networks (Diebold & Yilmaz, 2014).…”
Section: Generalized Forecast Error Variancementioning
confidence: 99%
“…We further normalized ← θ i j H using Equation (4) following Pesaran and Shin (1998). The resulting forecast error variance decompositions can be used to define weighted, directed, and time-varying networks (Diebold & Yilmaz, 2014). The resulting forecast error variance decompositions can be used to define weighted, directed, and time-varying networks (Diebold & Yilmaz, 2014).…”
Section: Generalized Forecast Error Variancementioning
confidence: 99%
“…In order to study the dynamic effects particularly during the euro area sovereign debt crisis, when the shifts in volatility became extreme, the VARX is estimated using rolling windows as in Diebold and Yilmaz (2014). Specifically, we run a standard vector autoregression with exogenous variables (VARX), where the endogenous variables include 10 euro area sovereign yields, the US Treasury and the UK gilt yields, the conventional monetary policy rates of the Federal Reserve (FED), Bank of England (BoE) and European Central Bank (ECB) and the exogenous variables comprise oil prices and macro news of the G10 countries.…”
Section: Introductionmentioning
confidence: 99%
“…Interdependence among sovereign yields is studied using the variance decomposition of shocks as in Diebold and Yilmaz (2014). We find that total connectedness among sovereign markets declined steadily from end-2008 to end-2012.…”
Section: Introductionmentioning
confidence: 99%
“…Caceres, Guzzo, and Segoviano (2010) find that the source of contagion shifted from countries such as Austria, the Netherlands, and Ireland, which were severely affected by the financial crisis, to countries with high short-term refinancing risk and uncertain long-term fiscal sustainability. Alter and Beyer (2014) measure credit risk spillovers across sovereign and bank CDSs between October 2009 and July 2012 using a methodology based on Diebold and Yilmaz (2011). Studies more closely related to our research are those of Alter and Beyer (2014); Gray, Gross, Paredes, and Sydow (2013); and Gross and Kok (2013).…”
Section: Introductionmentioning
confidence: 99%
“…Gross and Kok (2013) confirm these findings in a mixed-cross-section GVAR and show furthermore that spillover potential was high for banks in 2008 and high for sovereigns in 2012. These studies rely on generalized impulse responses, which have the advantage that they are invariant to the ordering of the variables and can easily be implemented into a framework such as that of Diebold and Yilmaz (2011). Their results indicate a strong contraction in real activity following sovereign risk shocks.…”
Section: Introductionmentioning
confidence: 99%