Eurozone sovereign contagion: Evidence from the CDS market (2005–2010)

Kalbaska, Alesia; Gątkowski, Mateusz

doi:10.1016/j.jebo.2012.05.010

Cited by 159 publications

(85 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…For instance, by employing an asset pricing model, Ang and Longstaff (2013) investigate the differences between U.S. and European credit default swap (CDS) spreads as a reflection of systemic risk. Lucas et al (2014) and Kalbaska and Gatkowski (2012) use multivariate time series models to model comovements in European sovereign CDS spreads. De Santis (2012) and Arezki et al (2011) study credit risk spillover effects that are induced by rating events, such as downgrades of Greek government bonds.…”

Section: Introductionmentioning

confidence: 99%

Spillover dynamics for systemic risk measurement using spatial financial time series models

Blasques

Koopman

Schaumburg

2016

Journal of Econometrics

108

106

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractWe introduce a new model for time-varying spatial dependence. The model extends the wellknown static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the static parameters is consistent and asymptotically normal. We also study the information theoretic optimality of the updating steps for the time-varying spatial dependence parameter. We adopt the model to empirically investigate the spatial dependence between eight European sovereign CDS spreads over the period [2009][2010][2011][2012][2013][2014], which includes the European sovereign debt crisis. We construct our spatial weight matrix using cross-border lending data and include country-specific and Europe-wide risk factors as controls. We find a high, time-varying degree of spatial spillovers in the sovereign CDS spread data. There is a downturn in spatial dependence after the first half of 2012, which is consistent with policy measures taken by the European Central Bank. The findings are robust to a wide range of alternative model specifications.

show abstract

Section: Introductionmentioning

confidence: 99%

Spillover dynamics for systemic risk measurement using spatial financial time series models

Blasques

Koopman

Schaumburg

2016

Journal of Econometrics

108

106

View full text Add to dashboard Cite

show abstract

“…Researchers have already used a variety of methodologies to study the transmission effects in euro area sovereign debt markets (correlation-based measures, conditional value-at-risk (CoVaR), or Granger-causality approach, among others) 2 : Kalbaska and Gatkowski (2012), Metiu (2012), Caporin et al (2013), Beirne and Fratzscher (2013), Gorea and Radev (2014), Gómez-Puig and Sosvilla-Rivero (2014) and Ludwig (2014) to name a few. Our paper adds to this literature by applying the methodology recently proposed by Diebold and Yilmaz (2012) to measure spillover effects using a generalized vector autoregressive framework in which forecast-error variance decompositions are invariant to the variable ordering.…”

Section: Introductionmentioning

confidence: 99%

Volatility spillovers in EMU sovereign bond markets

Rodríguez

Gómez‐Puig

Sosvilla‐Rivero

2015

International Review of Economics & Finance

View full text Add to dashboard Cite

AbstractsWe analyse volatility spillovers in EMU sovereign bond markets. First, we examine the unconditional patterns during the full sample (April 1999-January 2014) using a measure recently proposed by Diebold and Yılmaz (2012). Second, we make use of a dynamic analysis to evaluate net directional volatility spillovers for each of the eleven countries under study, and to determine whether core and peripheral markets present differences. Finally, we apply a panel analysis to empirically investigate the determinants of net directional spillovers of this kind.

show abstract

“…In a detailed analysis, Kalbaska and Gatkowski (2012) showed that correlations between countries before the so-called financial crisis are generally less pronounced than after the crisis. Correlation figures of CDS premiums of Germany compared to European countries with ratings lower than BBB are less pronounced after 2009 than correlation figures of CDS among the countries with a rating of less than BBB (Kalbaska & Gatkowski, 2012, p. 664).…”

mentioning

confidence: 99%

European CDS Premiums and Industrial Production

Gerhard¹,

Dieter²

2016

UCPA

View full text Add to dashboard Cite

This paper aims to find the dependence of the important European corporate CDS (Credit Default Swaps) indices and some selected country CDS of industrial production. While the existing literature acknowledges the importance of macroeconomic factors in determining CDS spreads from a general perspective, the importance of economic growth for individual firms, banks, and countries has not been examined in detail. The main hypothesis of the paper claims that weaker ratings are more growth-sensitive than better ratings. This means that the CDS will react more strongly to the industrial production when the rating is weaker. The authors analyzed the European CDS indices of investment grade, high yield enterprises, senior bank debt, and subordinated bank debt with a linear OLS (Ordinary Least Squares) regression. While the authors had to reject their main hypothesis for the European indices, they could prove their hypothesis concerning the country perspective: The German CDS has the weakest relation to industrial output, and the authors' hypothesis can be confirmed tendentially concerning the correlations of the more weakly rated countries (European periphery), which are much better. Surprisingly the correlation between peripheral country CDS and industrial production is much stronger than the correlation of corporate and bank CDS and industrial production. (ISDA Swapsinfo, 2016). This huge reduction of approximately 75% of traded volume may be correlated with the rising regulatory frameworks within the banking industry. CDS are widely used to reduce credit risks of countries, banks, or enterprises in general and are moreover considered for hedging speculative activities. In contrast to corporate bonds, the market of CDS shows much more liquidity and CDS are declared in basis points and not in total return ratios as seen in bond markets.Recent scientific studies have been carried out to identify influential factors for CDS markets. Guo and Newton (2013) found a multi-correlation among volatility, leverage, liquidity, risk free interest rate, and CDS premiums. These correlations have been identified empirically, based on the so-called "pioneering model of

show abstract

Eurozone sovereign contagion: Evidence from the CDS market (2005–2010)

Cited by 159 publications

References 22 publications

Spillover dynamics for systemic risk measurement using spatial financial time series models

Spillover dynamics for systemic risk measurement using spatial financial time series models

Volatility spillovers in EMU sovereign bond markets

European CDS Premiums and Industrial Production

Contact Info

Product

Resources

About