Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads

Lange, Rutger‐Jan; Lucas, André; Siegmann, Arjen

doi:10.2139/ssrn.2831450

Cited by 3 publications

(1 citation statement)

References 23 publications

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“…D'Agostino and Ehrmann ( 2014 ) pointed to an overreaction of the market given the change in fundamentals and thus to a structural change in longer-term risk perception. Gross and Kok ( 2013 ); Alter and Beyer ( 2014 ); Broner et al ( 2014 ); Glover and Richards-Shubik ( 2014 ); Shoesmith ( 2014 ); Erce ( 2015 ); Li and Waterworth ( 2016 ); Lange et al ( 2017 ) discussed the relationships between private and public sector bonds, between sovereign bonds and credit derivatives, and the transmission channels between bank risk and sovereign risk. Gerlach-Kristen ( 2015 ); Blasques et al ( 2016 ); Ehrmann and Fratzscher ( 2017 ); Moessner ( 2018 ); Arakelian et al ( 2019 ) confirmed the stabilizing impact of ECB measures on bond spreads after 2012.…”

Section: Introductionmentioning

confidence: 99%

Sentiment Analysis of European Bonds 2016–2018

Schwendner

Schüle

Hillebrand³

2019

Front. Artif. Intell.

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We revisit the discussion of market sentiment in European sovereign bonds using a correlation analysis toolkit based on influence networks and hierarchical clustering. We focus on three case studies of political interest. In the case of the 2016 Brexit referendum, the market showed negative correlations between core and periphery only in the week before the referendum. Before the French presidential elections in 2017, the French bond spread widened together with the estimated Le Pen election probability, but the position of French bonds in the correlation blocks did not weaken. In summer 2018, during the budget negotiations within the new Italian coalition, the Italian bonds reacted very sensitively to changing political messages but did not show contagion risk to Spain or Portugal for several months. The situation changed during the week from October 22 to 26, as a spillover pattern of negative sentiment also to the other peripheral countries emerged.

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Section: Introductionmentioning

confidence: 99%

Sentiment Analysis of European Bonds 2016–2018

Schwendner

Schüle

Hillebrand³

2019

Front. Artif. Intell.

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Measuring connectedness of euro area sovereign risk

Buse

Schienle

2019

International Journal of Forecasting

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We introduce a methodology for measuring default risk connectedness that is based on an out-of-sample variance decomposition of model forecast errors. The out-of-sample nature of the procedure leads to "realized" measures which, in practice, respond more quickly to crisis occurrences than those based on in-sample methods. The resulting relative and absolute connectedness measures find distinct and complementary information from CDS and bond yield data on European area sovereign risk. The detection and use of these second moment differences of CDS and bond data is new to the literature and allows to identify countries that impose risk on the system from those which sustain risk.

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Comparison of Score-Driven Equity-Gold Portfolios During the COVID-19 Pandemic Using Model Confidence Sets

Ayala,

Blazsek,

Licht

2023

Studies in Nonlinear Dynamics &Amp; Econometrics

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Gold may have a hedge, safe haven, or diversifier property when added to stock portfolios. Motivated by the favorable statistical properties and out-of-sample performance of score-driven models, we investigate for equity-gold portfolios whether score-driven mean, volatility, and copula models can improve the performances of DCC (dynamic conditional correlation) portfolios, the naïve portfolio strategy, and the Standard & Poor’s 500 (S&P 500) index. We consider 2880 score-driven portfolio strategies. We use score-driven Clayton, rotated Clayton, Frank, Gaussian, Gumbel, rotated Gumbel, Plackett, and Student’s t copulas. We use several classical and score-driven models of marginal distribution. We use weekly, monthly, quarterly, semi-annual, and annual updates of portfolio weights. We use minimum-variance, maximum Sharpe ratio, and maximum utility function strategies. We use rolling data-windows for portfolio optimization for the COVID-19 investment period of February 2020 to September 2021. We classify competing portfolios by using a new robust multi-step model confidence set (MCS) test approach and provide evidence of the superiority of score-driven portfolios.

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Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads

Cited by 3 publications

References 23 publications

Sentiment Analysis of European Bonds 2016–2018

Sentiment Analysis of European Bonds 2016–2018

Measuring connectedness of euro area sovereign risk

Comparison of Score-Driven Equity-Gold Portfolios During the COVID-19 Pandemic Using Model Confidence Sets

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