Macroeconomic Determinants of the Term Structure of Sovereign Credit Default Swap (CDS) Spread: Insights from MIDAS Regression

##plugins.themes.academic_pro.article.sidebar##

Published Sep 30, 2023
https://doi.org/10.61506/02.00111
Download
PDF
Statistic
Vol. 9 No. 3 (2023)

##plugins.themes.academic_pro.article.main##

Arshad Khan
Department of Management Sciences COMSATS University, Islamabad, Pakistan
Naveed Raza
Department of Management Sciences COMSATS University, Islamabad, Pakistan

Abstract

When investors seek to diversify their investment portfolios across countries to maximize returns, they also expose themselves to additional risks, including the risk of sovereign defaults, which is a growing concern for investors in many countries worldwide. To better understand the factors critical to sovereign defaults, this study aims to investigate the impact of both country-specific and global factors on the term structure of Sovereign Credit Default Swap (CDS) Spreads, which acts as gauges for the extent of risk and vulnerability to credit defaults. Moreover, quarterly and monthly data from ten Eurozone countries, spanning from 2007 to 2022, is used and the MIDAS regression approach is applied. The empirical findings indicate that country-specific and global variables significantly impact sovereign risk, as measured by the term structure of sovereign CDS Spreads. However, the effect varies among the countries, possibly due to differing economic fundamentals and trade relationships with other countries. Among the country-specific variables, Local stock market returns, Forex Rate, and Debt-to-GDP ratio emerge as the most influential indicators. At the same time, impact of Changes in Reserve and Terms of Trade is less. U.S. Stock Return holds more influence among the global factors than U.S. Variance Risk Premium and U.S. Long-Term Yield. The study's outcomes have implications for investors, policymakers, and regulators.

##plugins.themes.academic_pro.article.details##

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
[1]
Khan, A. and Raza, N. 2023. Macroeconomic Determinants of the Term Structure of Sovereign Credit Default Swap (CDS) Spread: Insights from MIDAS Regression. Journal of Policy Research. 9, 3 (Sep. 2023), 240–252. DOI:https://doi.org/10.61506/02.00111.
Crossref
Scopus
Google Scholar
Europe PMC

References

  1. Annaert, J., De Ceuster Marc, M., Van Roy, P., & Vespro, C. (2013). What determines euro area bank CDS spreads? Journal of International Money and Finance, 32(1), 444–461. https://doi.org/10.1016/j.jimonfin.2012.05.029 DOI: https://doi.org/10.1016/j.jimonfin.2012.05.029
  2. Armesto, M. T., Engemann, K. M., & Owyang, M. T. (2010). Forecasting with mixed frequencies. Federal Reserve Bank of St. Louis Review, 92(6), 521–536. https://doi.org/10.20955/r.92.521-36 DOI: https://doi.org/10.20955/r.92.521-36
  3. Augustin, P. (2018). The term structure of CDS spreads and sovereign credit risk. Journal of Monetary Economics, 96, 53–76. https://doi.org/10.1016/j.jmoneco.2018.04.001 DOI: https://doi.org/10.1016/j.jmoneco.2018.04.001
  4. Baldacci, E., Gupta, S., & Mati, A. (2011). Political and fiscal risk determinants of sovereign spreads in emerging markets. Review of Development Economics, 15(2), 251–263. DOI: https://doi.org/10.1111/j.1467-9361.2011.00606.x
  5. Blau, B. M., & Roseman, B. S. (2014). The reaction of European credit default swap spreads to the U.S. credit rating downgrade. International Review of Economics and Finance, 34, 131–141. https://doi.org/10.1016/j.iref.2014.07.009 DOI: https://doi.org/10.1016/j.iref.2014.07.009
  6. Calice, G., & Zeng, M. (2021). The term structure of sovereign credit default swap and the cross-section of exchange rate predictability. International Journal of Finance and Economics, 26(1), 445–458. https://doi.org/10.1002/ijfe.1798 DOI: https://doi.org/10.1002/ijfe.1798
  7. Chen, H. Y., & Chen, S. S. (2018). Quality of government institutions and spreads on sovereign credit default swaps. Journal of International Money and Finance, 87(64), 82–95. https://doi.org/10.1016/j.jimonfin.2018.05.008 DOI: https://doi.org/10.1016/j.jimonfin.2018.05.008
  8. Chiarella, C., ter Ellen, S., He, X. Z., & Wu, E. (2015). Fear or fundamentals? Heterogeneous beliefs in the European sovereign CDS market. Journal of Empirical Finance, 32, 19–34. https://doi.org/10.1016/j.jempfin.2014.11.003 DOI: https://doi.org/10.1016/j.jempfin.2014.11.003
  9. Cho, D., & Rhee, D. E. (2023). Determinants of market-assessed sovereign default risk: Macroeconomic fundamentals or global shocks? International Finance, November 2022. https://doi.org/10.1111/infi.12440 DOI: https://doi.org/10.1111/infi.12440
  10. Duffie, D., Pedersen, L. H., & Singleton, K. J. (2003). Modeling Sovereign Yield Spreads: A Case Study of Russian Debt. Journal of Finance, 58(1), 119–159. https://doi.org/10.1111/1540-6261.00520 DOI: https://doi.org/10.1111/1540-6261.00520
  11. Erba, S. D., Hausmann, R., & Panizza, U. (2010). Working Papers. Journal of Food System Research, 17(3), 159–275. https://doi.org/10.5874/jfsr.17.159 DOI: https://doi.org/10.5874/jfsr.17.159
  12. Fontana, A., & Scheicher, M. (2016). An analysis of euro area sovereign CDS and their relation with government bonds. Journal of Banking and Finance, 62, 126–140. https://doi.org/10.1016/j.jbankfin.2015.10.010 DOI: https://doi.org/10.1016/j.jbankfin.2015.10.010
  13. Ghysels, E. (2004). The MIDAS Touch : Mixed Data Sampling Regression Models ∗ Pedro Santa-Clara Rossen Valkanov. Ucla, 919.
  14. Ghysels, E., & Qian, H. (2019). Estimating MIDAS regressions via OLS with polynomial parameter profiling. Econometrics and Statistics, 9, 1–16. https://doi.org/10.1016/j.ecosta.2018.02.001 DOI: https://doi.org/10.1016/j.ecosta.2018.02.001
  15. Ghysels, E., Santa-Clara, P., & Valkanov, R. (2006). Predicting volatility: Getting the most out of return data sampled at different frequencies. Journal of Econometrics, 131(1–2), 59–95. https://doi.org/10.1016/j.jeconom.2005.01.004 DOI: https://doi.org/10.1016/j.jeconom.2005.01.004
  16. Ghysels, E., Sinko, A., & Valkanov, R. (2007). MIDAS regressions: Further results and new directions. In Econometric Reviews (Vol. 26, Issue 1). https://doi.org/10.1080/07474930600972467 DOI: https://doi.org/10.1080/07474930600972467
  17. Gibson, H. D., Hall, S. G., & Tavlas, G. S. (2012). Journal of International Money The Greek fi nancial crisis : Growing imbalances and sovereign spreads. Journal of International Money and Finance, 31(3), 498–516. https://doi.org/10.1016/j.jimonfin.2011.10.009 DOI: https://doi.org/10.1016/j.jimonfin.2011.10.009
  18. Grammatikos, T., & Vermeulen, R. (2012). Transmission of the financial and sovereign debt crises to the EMU: Stock prices, CDS spreads and exchange rates. Journal of International Money and Finance, 31(3), 517–533. https://doi.org/10.1016/j.jimonfin.2011.10.004 DOI: https://doi.org/10.1016/j.jimonfin.2011.10.004
  19. Guay, A., & Maurin, A. (2015). Disaggregation methods based on MIDAS regression. Economic Modelling, 50, 123–129. https://doi.org/10.1016/j.econmod.2015.05.013 DOI: https://doi.org/10.1016/j.econmod.2015.05.013
  20. Gujarati, D. N. (2022). Basic econometrics. Prentice Hall.
  21. Gündüz, Y., & Kaya, O. (2014). Impacts of the financial crisis on eurozone sovereign CDS spreads. Journal of International Money and Finance, 49(PB), 425–442. https://doi.org/10.1016/j.jimonfin.2014.03.013 DOI: https://doi.org/10.1016/j.jimonfin.2014.03.013
  22. Guo, B., Shi, Y., & Xu, Y. (2020). Volatility information difference between CDS, options, and the cross section of options returns. Quantitative Finance, 20(12), 2025–2036. https://doi.org/10.1080/14697688.2020.1814018 DOI: https://doi.org/10.1080/14697688.2020.1814018
  23. Hibbert, A. M., & Pavlova, I. (2017). The Drivers of Sovereign CDS Spread Changes: Local Versus Global Factors. Financial Review, 52(3), 435–457. https://doi.org/10.1111/fire.12140 DOI: https://doi.org/10.1111/fire.12140
  24. J. Bulow, K. R. (1989). Sovereign Debt: Is to forgive to Forget ? NBER Working Paper Series., 2623(1989), 43–50. DOI: https://doi.org/10.3386/w2623
  25. Jeanneret, A. (2018). Sovereign credit spreads under good/bad governance. Journal of Banking and Finance, 93, 230–246. https://doi.org/10.1016/j.jbankfin.2018.04.005 DOI: https://doi.org/10.1016/j.jbankfin.2018.04.005
  26. Kartal, M. T. (2022). Soverign credit default (CDS) spread changes in various economic conjunctures : evidence from Turky by machine learning algorithms. Journal of Management and Economics Research, 20(January), 354–374. DOI: https://doi.org/10.11611/yead.1076897
  27. Kumar, M. M. S., & Baldacci, M. E. (2010). Fiscal deficits, public debt, and sovereign bond yields. International Monetary Fund. DOI: https://doi.org/10.5089/9781455202188.001
  28. Longstaff, F. A., Pan, J., Pedersen, L. H., & Singleton, K. J. (2011). How sovereign is sovereign credit risk? American Economic Journal: Macroeconomics, 3(2), 75–103. https://doi.org/10.1257/mac.3.2.75 DOI: https://doi.org/10.1257/mac.3.2.75
  29. Marcellino, M. (1999). Some consequences of temporal aggregation in empirical analysis. Journal of Business and Economic Statistics, 17(1), 129–136. https://doi.org/10.1080/07350015.1999.10524802 DOI: https://doi.org/10.1080/07350015.1999.10524802
  30. Merton, R. C. (1974). American Finance Association On the Pricing of Corporate Debt : The Risk Structure of Interest Rates Author ( s ): Robert C . Merton Source : The Journal of Finance , Vol . 29 , No . 2 , Papers and Proceedings of the Thirty- Second Annual Meeting of the A. The Journal of Finance, 29(2), 449–470. DOI: https://doi.org/10.1111/j.1540-6261.1974.tb03058.x
  31. Pan, J., & Singleton, K. J. (2008). Default and recovery implicit in the term structure of sovereign CDS spreads. Journal of Finance, 63(5), 2345–2384. https://doi.org/10.1111/j.1540-6261.2008.01399.x DOI: https://doi.org/10.1111/j.1540-6261.2008.01399.x
  32. Remolona, E., Scatigna, M., & Wu, E. (2008). The dynamic pricing of sovereign risk in emerging markets: Fundamentals and risk aversion. Journal of Fixed Income, 17(4), 57–71. https://doi.org/10.3905/jfi.2008.705542 DOI: https://doi.org/10.3905/jfi.2008.705542
  33. Syed Jawad Hussain Shahzad, Nor, S. M., Ferrer, R., & Hammoudeh, S. (2017). Asymmetric determinants of CDS spreads: U.S. industry-level evidence through the NARDL approach. Economic Modelling, 60(September 2016), 211–230. https://doi.org/10.1016/j.econmod.2016.09.003 DOI: https://doi.org/10.1016/j.econmod.2016.09.003
  34. Tevfik Kartal, M. (2020). The behavior of Sovereign Credit Default Swaps (CDS) spread: evidence from Turkey with the effect of Covid-19 pandemic. Quantitative Finance and Economics, 4(3), 489–502. https://doi.org/10.3934/qfe.2020022 DOI: https://doi.org/10.3934/QFE.2020022
  35. Yin, C., Chiu, J., Hsiao, Y.-J., 湯建文, & Tsai, W.-C. (2021). The Effects of US Macroeconomic Surprises on the Term Structure of Emerging-market Sovereign Credit Default Swaps. SSRN Electronic Journal, 886, 1–54. https://doi.org/10.2139/ssrn.3759530 DOI: https://doi.org/10.2139/ssrn.3759530
  36. Yu, F. (2002). Modeling Expected Return on Defaultable Bonds. The Journal of Fixed Income, 12(2), 69–81. https://doi.org/10.3905/jfi.2002.319326 DOI: https://doi.org/10.3905/jfi.2002.319326
  37. Zhang, Y. J., & Wang, J. L. (2019). Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models. Energy Economics, 78, 192–201. https://doi.org/10.1016/j.eneco.2018.11.015 DOI: https://doi.org/10.1016/j.eneco.2018.11.015