Analyzing credit risk transmission to the nonfinancial sector in Europe: A network approach

Gross, C. J.; Siklos, Pierre L.

doi:10.1002/jae.2726

Cited by 24 publications

(12 citation statements)

References 83 publications

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“…Further applications of the model could focus on the study of the potential transmission of credit risk across sovereign, bank, and non-bank institutions (see e.g. Gross and Siklos 2020 ), or in the modeling of quanto CDS spreads (i.e. differences in CDS premia in different currency denominations, see e.g.…”

Section: Discussionmentioning

confidence: 99%

A revised version of the Cathcart & El-Jahel model and its application to CDS market

Radi

Hoang

Torri

et al. 2021

Decisions Econ Finan

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The paper considers the pricing of credit default swaps (CDSs) using a revised version of the credit risk model proposed in Cathcart and El-Jahel (2003). Default occurs either the first time a signaling process breaches a threshold barrier or unexpectedly at the first jump of a Cox process. The intensity of default depends on the risk-free interest rate, which follows a Vasicek process, instead of a Cox-Ingersoll-Ross process as in the original model. This offers two advantages. On the one hand, it allows us to account for negative interest rates which are recently observed, on the other hand, it simplifies the formula for pricing CDSs. The goodness of fit of the model is tested using a dataset of CDS credit spreads related to European companies. The results obtained show a rather satisfactory agreement between theoretical predictions and market data, which is identical to the one obtained with the original model. In addition, the values of the calibrated parameters result to be stable over time and the semi-closed form solution ensures a very fast implementation.

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Section: Discussionmentioning

confidence: 99%

A revised version of the Cathcart & El-Jahel model and its application to CDS market

Radi

Hoang

Torri

et al. 2021

Decisions Econ Finan

View full text Add to dashboard Cite

show abstract

“…We use the approaches of Demirer et al ( 2017 ) and Gross and Siklos ( 2020 ) to compute directional connectedness from an estimation of variance decomposition to construct a network. We consider a covariance stationary VAR ( p ) with an N -dimensional vector of sovereign CDS returns as follows: …”

Section: Methodsmentioning

confidence: 99%

Sovereign default network and currency risk premia

Yang

Yang²,

Cui

2023

Financ Innov

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We construct a sovereign default network by employing high-dimensional vector autoregressions obtained by analyzing connectedness in sovereign credit default swap markets. We develop four measures of centrality, namely, degree, betweenness, closeness, and eigenvector centralities, to detect whether network properties drive the currency risk premia. We observe that closeness and betweenness centralities can negatively drive currency excess returns but do not exhibit a relationship with forward spread. Thus, our developed network centralities are independent of an unconditional carry trade risk factor. Based on our findings, we develop a trading strategy by taking a long position on peripheral countries’ currencies and a short position on core countries’ currencies. The aforementioned strategy generates a higher Sharpe ratio than the currency momentum strategy. Our proposed strategy is robust to foreign exchange regimes and the coronavirus disease 2019 pandemic.

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“…With the continuous development of modern econometric methods, the application of LASSO and elastic network shrinkage technology provided the possibility for the construction of high-dimensional financial networks [35]. In particular, the elastic network shrinkage technology combines LASSO and ridge regression, which had better efficacy in the estimation of high-dimensional dynamic network models based on the rolling time window [5].…”

Section: Related Literaturementioning

confidence: 99%

“…Therefore, we focus on the dynamic modeling of the financial network. The rolling time window technology is often used to capture the time-varying characteristic of financial networks [4,5], which is advantageous in describing the differences of financial network risk contagion relationships in different periods. In particular, since the financial system is characterized by high dimensionality and high complexity, how to integrate the "high-dimensional" and "time-varying" characteristics of financial network into the same framework and construct the high-dimensional dynamic network model is worth further exploration.…”

Section: Introductionmentioning

confidence: 99%

How Connected Is China’s Systemic Financial Risk Contagion Network?—A Dynamic Network Perspective Analysis

Zhang

Xie

2023

Mathematics

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Modeling the effects and paths of systemic financial risk contagion is significant for financial stability. This paper focuses on China’s systemic financial risk from the perspective of dynamic networks. First, we construct a high-dimensional dynamic financial network model to capture risk contagion effects. Second, considering the ripple effect of financial risk contagion, we introduce and improve the basic model of the ripple-spreading network. Finally, small- and medium-sized banks and economic policy uncertainty are selected as the internal and external contagion source, respectively, to simulate the risk of ripple-spreading paths. The results show that financial contagion is more likely to occur within the same industry. The contagion triggered by internal shock first spreads within the same industry, and then to other industries. The contagion triggered by external shock first spreads to banks, then to diversified financial institutions, securities and insurance institutions, successively. Moreover, some small- and medium-sized commercial banks show strong abilities to spread risk ripples. The securities industry is the intermediary layer of the ripple network and plays a leading role in the ripple-spreading process. Therefore, systemic financial risk regulation should focus not only on large financial institutions but also on financial institutions with strong ripple effects. During major risk events, isolating risk intermediary nodes can cut off the paths of risk contagion and mitigate the impact on the whole financial system effectively.

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Analyzing credit risk transmission to the nonfinancial sector in Europe: A network approach

Cited by 24 publications

References 83 publications

A revised version of the Cathcart & El-Jahel model and its application to CDS market

A revised version of the Cathcart & El-Jahel model and its application to CDS market

Sovereign default network and currency risk premia

How Connected Is China’s Systemic Financial Risk Contagion Network?—A Dynamic Network Perspective Analysis

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