CDS Spreads and Systemic Risk - A Spatial Econometric Approach

Keiler, Sebastian; Eder, Armin

doi:10.2139/ssrn.2207625

Cited by 16 publications

(27 citation statements)

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“…Most closely related to our article are the recent works by Meine et al (2015b); Christoffersen et al (2014); Koziol et al (2015) and Keiler and Eder (2013). The paper by Meine et al (2015b) provides evidence that the propensity of a bank to experience extreme co-movements in its own credit default swap together with the market is priced in the CDS during the financial crisis.…”

Section: Determinants Of Cdssupporting

confidence: 57%

“…However, their study is limited to a sample of banks and their model is restricted to the skewed t-copula, while our paper studies the effect of different copulas and we do not restrict our study to a sample of banks. Going in the same direction is the study of Keiler and Eder (2013). They address the question of how the CDS spread of one financial company is influenced by the CDS spreads of other financial companies within the system.…”

Section: Determinants Of Cdsmentioning

confidence: 99%

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The Determinants of CDS Spreads: Evidence from the Model Space

Pelster

Vilsmeier

2016

SSRN Journal

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The CDS market plays an important role in understanding the dynamics of financial markets and financial stability and consequently has received growing attention in the recent literature. Despite the rich literature there is still no consensus about which factors mainly drive CDS spreads. Instead we observe an increasingly large number of potential determinants being suggested. We aim to provide a transparent and robust analysis for the determinants of CDS spreads by focusing on the information provided by a large number of models (the "model space") instead of focusing on one or few "hand-picked" specifications. Our model space covers most of the specifications used elsewhere in the literature and includes several variables measuring the sensitivity of firms to extreme market movements (tail dependence). ContributionWe show that the model space includes models which allow backing many different theories by significant coefficients and good fit to the data. Thus, the information content from single model specifications is rather restricted. In contrast to previous studies, we use information from the entire model space instead of restricting ourselves to some "hand-picked" models. Doing so, we provide a transparent and robust analysis for the determinants of CDS spreads. Besides covering the informational content of most previous studies in our analysis we also give clear evidence on the impact of using different estimation procedures to measure tail dependence in CDS markets. ResultsUsing a large data-set, we find that CDS price dynamics can be mainly explained by factors describing firms' sensitivity to extreme market movements. More precisely, our results suggest that variables measuring tail dependence -based on so-called dynamic copula models -incorporate almost all essential pricing information making other potential determinants such as default risk (Merton-type) factors or variables capturing the systematic market evolutions negligible. The determinants of CDS spreads: evidence from the model space * Matthias Pelster Leuphana University of Lueneburg Johannes Vilsmeier Deutsche Bundesbank AbstractWe apply Bayesian Model Averaging and a frequentistic model space analysis to assess the pricing-determinants of credit default swaps (CDS). Our study focuses on the complete model space of plausible models covering most of the variables and specifications used elsewhere in the literature, including different copula models. The approach followed supports ultimate transparency and robustness for the empirical study at hand. Using a large data-set of CDS contracts we find that CDS price dynamics can be mainly explained by factors describing firms' sensitivity to extreme market movements. More precisely, our results suggest that dynamic copula based measures of tail dependence incorporate almost all essential pricing information making other potential determinants such as Merton-type factors or variables measuring the systematic market evolution -based on simple means or principal component analysis -negligible.

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Section: Determinants Of Cdssupporting

confidence: 57%

Section: Determinants Of Cdsmentioning

confidence: 99%

The Determinants of CDS Spreads: Evidence from the Model Space

Pelster

Vilsmeier

2016

SSRN Journal

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“…However, the existing academic literature has already demonstrated that other factors, having a more systematic nature, such as general economic conditions but also liquidity, plays a role. Recently, Giglio (2011) or Keiler and Eder (2013) further suggest the importance of a systemic factor.…”

Section: Price Discovery Processmentioning

confidence: 98%

“…Similarly, Berndt et al (2005) suggest that CDS spreads are likely not attributed to credit risk alone and Annaert et al (2013) notably conclude that liquidity and global economic variables are important to explain CDS variations. More recently, Keiler and Eder (2013) investigate the degree of systemic risk and the importance of potential spill-over effects in the banking system by analyzing the determinants of CDS spreads using spatial econometric approach. Such technique enables them to look at the existing cross-sectional interactions and to distinguish between three main components: a systemic one, a systematic one and an idiosyncratic one.…”

Section: The Determinants Of Credit and Cds Spreadsmentioning

confidence: 99%

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Unveiling Sovereign Effects in European Banks CDS Spreads Variations

Peters

Pirotte

2014

SSRN Journal

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Starting from the structural model developed by Merton (1974) and the derived notion of distance-to-default, we study the determinants of credit default swap (CDS) spreads for a sample of European banks over a period from January 2006 to December 2011. In particular, we test variables that are specific to the banking industry and look at the possible interaction with CDS spreads for the related sovereigns. We confirm findings from the literature review regarding the low significance of the structural model and its breakdown in times of stress. We confirm the importance of macro-economic components such as the general level of interest rates and the general state of the economy, particularly in times of stress. We find that before the crisis period the micro-and macro-components are generally predominant in the determination of CDS spread variations while the influence of sovereigns' CDS become more important when entering further into the crisis period. Interestingly, southern European countries are the first to become significant at the start of the crisis. Progressively, all CDS countries become increasingly significant, overweigh all other explanatory variables and remain so even after the crisis period, thereby suggesting the focused attention of market participants for the sovereign dimension.Keywords: Credit default swaps, CDS spreads, structural model, distance to default, banking debt, sovereign debt. AbstractStarting from the structural model developed by Merton (1974) and the derived notion of distance-to-default, we study the determinants of credit default swap (CDS) spreads for a sample of European banks over a period from January 2006 to December 2011. In particular, we test variables that are specific to the banking industry and look at the possible interaction with CDS spreads for the related sovereigns. We confirm findings from the literature review regarding the low significance of the structural model and its breakdown in times of stress. We confirm the importance of macro-economic components such as the general level of interest rates and the general state of the economy, particularly in times of stress. We find that before the crisis period the micro-and macro-components are generally predominant in the determination of CDS spread variations while the influence of sovereigns' CDS become more important when entering further into the crisis period. Interestingly, southern European countries are the first to become significant at the start of the crisis. Progressively, all CDS countries become increasingly significant, overweigh all other explanatory variables and remain so even after the crisis period, thereby suggesting the focused attention of market participants for the sovereign dimension.

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Networks in risk spillovers: A multivariate GARCH perspective

Billio

Caporin

Frattarolo

et al. 2023

Econometrics and Statistics

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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.

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CDS Spreads and Systemic Risk - A Spatial Econometric Approach

Cited by 16 publications

References 50 publications

The Determinants of CDS Spreads: Evidence from the Model Space

The Determinants of CDS Spreads: Evidence from the Model Space

Unveiling Sovereign Effects in European Banks CDS Spreads Variations

Networks in risk spillovers: A multivariate GARCH perspective

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