Firm credit risk in normal times and during the crisis: are banks less risky?

Raunig, Burkhard

doi:10.1080/00036846.2015.1008758

Cited by 9 publications

(11 citation statements)

References 24 publications

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“…This implies that the price of the derivatives incorporated macroeconomic shocks from the conventional stock markets, especially when investors believed that a stock or the overall market would go higher. These results are in line with the findings of Galil et al (2014), Raunig (2015), Shahzad et al (2017) and Malhotra and Corelli (2018), establishing that CDS premia are significantly influenced by macroeconomic variables. The findings of the study have important implications for various economic agents related to policy development and portfolio risk management through market busts and booms.…”

Section: Discussionsupporting

confidence: 89%

“…Particularly the Oil and Gas sector and the Utilities sector exhibit significant sensitivity in both extremely bullish and bearish market situations (0.05, 0.75 and 0.95). The inverse relationship between yield rates and CDS spreads has also been evidenced by Alexander and Kaeck (2007), Chen et al (2013) and Raunig (2015). Generalizing the findings, there is evidence that the long-term factor (level) of the yield rate is the most significant determinant in the pricing of the CDS spreads, regardless of the industrial sector.…”

Section: Resultssupporting

confidence: 57%

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Are CDS Spreads Sensitive to the Term Structure of the Yield Curve? A Sector-Wise Analysis under Various Market Conditions

Aman

2019

JRFM

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This study examines the impact of changes in the yield curve factors on the Credit Default Swap (CDS) spreads of the U.S. industrial sectors. Stock returns and the crude oil-based volatility index are used in a quantile regression framework to test the validity of Merton’s model. The results suggest that the long-term factor of the yield curve is a negatively significant determinant of the CDS premia regardless of the sector and market state. The CDS spread of the financial sector exhibits sensitivity to the short-term factor of the yield rate in extreme market states. Basic materials, oil and gas and the utilities sector are responsive to variations in the medium-term factor of the yield rate in upmarket conditions. The empirical findings also suggest a significant inverse relationship between CDS spreads and stock returns.

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Section: Discussionsupporting

confidence: 89%

Section: Resultssupporting

confidence: 57%

Are CDS Spreads Sensitive to the Term Structure of the Yield Curve? A Sector-Wise Analysis under Various Market Conditions

Aman

2019

JRFM

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“…Interestingly, the SMB portfolio returns (size premium) also decrease this probability. The importance of the bank size as a strong determinant of the Banking CDS premium is also highlighted by Raunig (2015) and Bijlsma et al (2014), among others. Bijlsma et al (2014) find that large banks have a 67 basis points funding advantage over small banks.…”

Section: Tablementioning

confidence: 97%

“…The correlation results are not presented for the brevity of space; however, are available from the authors on request. Notably, we treat banks and other financial firms separately because earlier empirical works suggest that the CDS premiums of these industries react differently to market conditions (Raunig, 2015) 8 . The CDS indices (denominated in basis points so that 100 basis points equate to one percentage point) are based on 5-year contracts because the five year credit instruments are considered adequate based on liquidity and are widely used in empirical analyses (Narayan et al, 2014;Hammoudeh et al, 2013).…”

Section: Fig 1 Weekly Averages and Standard Deviations Of Us Industmentioning

confidence: 99%

Directional and bidirectional causality between U.S. industry credit and stock markets and their determinants

Shahzad

Nor

Hammoudeh

et al. 2017

International Review of Economics & Finance

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We examine the causal links between U.S. industry-wise credits and stock markets. The full sample bootstrap Granger causality results show that all stock markets Granger cause their CDS counterparts and there is also bidirectional causality for the banking, healthcare and material industries. The short-run parametric stability tests highlight that the full sample parameters are not stable and hence less reliable. The bootstrap rolling window estimations confirm the inconsistency in the CDS-stock causality relationships where bidirectional causalities are also found between the credit and stock markets that vary over different sub-samples. Finally, we analyze the impact of different financial and macroeconomic determinants on the CDS-stock causality through a probit model. Overall, the business conditions, stock market volatility, default premiums, Treasury bond rate and the slope of the yield curve are major drivers of the CDS-stock nexus. Our findings provide possible explanation for varying and mixed previous empirical findings in the existing literature, and hence have useful investment implications.JEL Classification: C32, G20, G32

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“…They used the data of 718 US firms (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) and suggested that stock returns, change in volatility and median CDS spread in of a rating class outperform the other variables. Finally, Raunig (2015) used 212 European and US firms (2007 and the random effect panel approach to analyse the determinants of CDS premia. He found that both structural-and market model-based variables explained more than 70 per cent of the variations.…”

Section: Introductionmentioning

confidence: 99%

The Determinants of Credit Risk: Analysis of US Industry-level Indices

Shahzad

Nor

Sanusi

et al. 2017

Global Business Review

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The study examines the cointegration and causal relationship between credit default swap spreads, stock prices, VIX, interest rate and slope of the yield curve for the 10 industries in the USA over the period 14 December 2007 to 30 September 2015. Due to the presence of cross-sectional dependence in the panel, we employ the Pesaran (2007, Journal of Applied Econometrics, 22(2), 265–312) CIPS test to ascertain unit root properties. The cointegration test underscores the presence of a long-run association between the variables. The long-run heterogeneous panel elasticities are estimated via Dynamic OLS (DOLS) and the causality is examined by using the Dumitrescu and Hurlin (2012, Economic Modelling, 29(4), 1450–1460) Granger causality tests. The empirical results reveal that stock prices (volatility), interest rate and slope of the yield curve decrease (increase) the CDS premia; and stock prices, VIX and interest rate Granger-cause the CDS spreads for most of the industries.

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Firm credit risk in normal times and during the crisis: are banks less risky?

Cited by 9 publications

References 24 publications

Are CDS Spreads Sensitive to the Term Structure of the Yield Curve? A Sector-Wise Analysis under Various Market Conditions

Are CDS Spreads Sensitive to the Term Structure of the Yield Curve? A Sector-Wise Analysis under Various Market Conditions

Directional and bidirectional causality between U.S. industry credit and stock markets and their determinants

The Determinants of Credit Risk: Analysis of US Industry-level Indices

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