Predictive power of oil prices on CDS spread dynamics of oil-producing countries

This paper employs predictive regressions to explore the predictability of sovereign Credit Default Swap (CDS) spread dynamics of relevant oil-producing countries. By incorporating oil prices and additional control variables, we predict the rate of CDS spread changes for Brazil, the UK, Malaysia, Norway, Qatar, Russia, Saudi Arabia, the US, and Venezuela. Our findings reveal that (i) the empirical coefficients of determination (R²) indicate low in-sample predictability for our entire period of analysis (2010–2024), the R² increases markedly when dividing the analysis period into more relevant sub-samples (2010–2016 and 2016–2024); (ii) oil prices are not significant predictors for the full period but become significant in many regressions within sub-samples; (iii) for countries where oil prices are significant in both sub-samples, the coefficient sign changes from negative to positive, suggesting that in more recent years, rising (falling) oil prices signal increasing (decreasing) geopolitical risk, positively (negatively) influencing CDS spreads.

Publication Details

Journal
PubData
Published
2025-03-22
DOI
https://doi.org/10.48548/pubdata-3120
Primary Topic
Credit Risk and Financial Regulations
Type
article
Field-Weighted Citation Impact
0.00
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article

Predictive power of oil prices on CDS spread dynamics of oil-producing countries

PubData
Credit Risk and Financial Regulations
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Predictive power of oil prices on CDS spread dynamics of oil-producing countries

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Abstract

This paper employs predictive regressions to explore the predictability of sovereign Credit Default Swap (CDS) spread dynamics of relevant oil-producing countries. By incorporating oil prices and additional control variables, we predict the rate of CDS spread changes for Brazil, the UK, Malaysia, Norway, Qatar, Russia, Saudi Arabia, the US, and Venezuela. Our findings reveal that (i) the empirical coefficients of determination (R²) indicate low in-sample predictability for our entire period of analysis (2010–2024), the R² increases markedly when dividing the analysis period into more relevant sub-samples (2010–2016 and 2016–2024); (ii) oil prices are not significant predictors for the full period but become significant in many regressions within sub-samples; (iii) for countries where oil prices are significant in both sub-samples, the coefficient sign changes from negative to positive, suggesting that in more recent years, rising (falling) oil prices signal increasing (decreasing) geopolitical risk, positively (negatively) influencing CDS spreads.

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