COVID-19 DUYURULARININ VE HÜKÜMET KISITLAMALARININ BRICS-T ÜLKELERİNİN CDS PRİMLERİ ÜZERİNDEKİ ETKİSİ

Abstract

In this study, the impact of changes in the number of Covid-19 cases and deaths, as well as government restrictions taken to reduce the spread of the pandemic, on the CDS premiums of BRICS-T countries, which are risk indicators, were examined. The data for the study include the number of deaths and cases as Covid-19 announcements, the stringency index calculated by the Oxford Covid-19 Government Response Tracker (OxCGRT) for government restrictions, and the CDS premium prices for Brazil, Russia, India, China, South Africa, and Turkey. For he study, Kao and Pedroni cointegration tests, Dumitrescu Hurlin and Granger causality analyses, and static panel data analysis were conducted. According to the analysis results, the cointegration tests indicate a long-term relationships between CDS premiums and case, death, strigency index of BRICS-T countries. According to the causality test results, a causal relationship from government restrictions to country CDS premiums, while no relationship could be determined from the number of cases and deaths. The static panel analysis results indicate that only government restrictions have a positive and significant effect on CDS premiums. In conclusion, the study shows that the increase in restrictions, along with the pressure of government restrictions on the economic system, increases the risk of emerging and developing countries.

Keywords

• BRICS-T
• CDS Primleri
• Covid-19
• Hükümet Duyuruları

IMPACT OF COVID 19 ANNOUNCEMENTS AND GOVERNMENT RESTRICTIONS ON CDS PREMIUMS OF BRICS-T COUNTRIES

Abstract

In this study, the impact of changes in the number of Covid-19 cases and deaths, as well as government restrictions taken to reduce the spread of the pandemic, on the CDS premiums of BRICS-T countries, which are risk indicators, were examined. The data for the study include the number of deaths and cases as Covid-19 announcements, the stringency index calculated by the Oxford Covid-19 Government Response Tracker (OxCGRT) for government restrictions, and the CDS premium prices for Brazil, Russia, India, China, South Africa, and Turkey. For he study, Kao and Pedroni cointegration tests, Dumitrescu Hurlin and Granger causality analyses, and static panel data analysis were conducted. According to the analysis results, the cointegration tests indicate a long-term relationships between CDS premiums and case, death, strigency index of BRICS-T countries. According to the causality test results, a causal relationship from government restrictions to country CDS premiums, while no relationship could be determined from the number of cases and deaths. The static panel analysis results indicate that only government restrictions have a positive and significant effect on CDS premiums. In conclusion, the study shows that the increase in restrictions, along with the pressure of government restrictions on the economic system, increases the risk of emerging and developing countries.

Keywords

• BRICS-T
• CDS Premiums
• Covid-19
• Government Restrictions

References

1. Ammer, J., & Cai, F. (2011). Sovereign CDS and bond pricing dynamics in emerging markets: Does the cheapest-to-deliver option matter?. Journal of International Financial Markets, Institutions and Money, 21(3), 369-387.
2. Andrieș, A. M., Ongena, S., & Sprincean, N. (2021). The Covid-19 pandemic and sovereign bond risk. The North American Journal of Economics and Finance, 58, 101527.
3. Bank for International Settlements (2021).OTC derivatives statistics at end-June2021, Available Online: https://www.bis.org/publ/otc_hy2111.htm.
4. Baum, C. F., & Wan, C. (2010). Macroeconomic uncertainty and credit default swap spreads. Applied Financial Economics, 20(15), 1163-1171.
5. Bayraktar, A. (2020). Covid-19 Pandemisinin Finansal Etkileri: BİST İmalat Sektörü Uygulaması. Turkish Studies, 15(8), 3415-3427.
6. Bȩdowska-Sójka, B., & Kliber, A. (2022). Impact of Covid-19 on sovereign risk: Latin America versus Asia. Finance Research Letters, 47, 102582.
7. Cevik, S., & Öztürkkal, B. (2021). Contagion of fear: Is the impact of Covid-19 on sovereign risk really indiscriminate?. International Finance, 24(2), 134-154.
8. Choi, I. (2001). Unit root tests for panel data. Journal of İnternational Money and Finance, 20(2), 249-272.

9. Daehler, T., Aizenman, J., & Jinjarak, Y. (2020). Emerging Markets Sovereign Spreads And Country-Specific Fundamentals During Covid-19. https://coilink.org/20.500.12592/fnj5fb
10. Das, S. R., Hanouna, P., & Sarin, A. (2009). Accounting-based versus market-based cross-sectional models of CDS spreads. Journal of Banking & Finance, 33(4), 719-730.
11. Demirhan, E. (2020). “Covid-19 Küresel Salgınının Türkiye CDS Primlerine ve BİST 100 Endeksine Etkisi”, Türkiye Ekonomi Politikaları Araştırma Vakfı, WP202001.
12. Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic modelling, 29(4), 1450-1460.
13. Duran, M.S. ve Acar, M. (2020). “Bir Virüsün Dünyaya Ettikleri: Covid-19 Pandemisinin Makroekonomik Etkileri”, International Journal of Social and Economic Sciences, 10(1), 54-67.
14. Dünya Sağlık Örgütü. (2023). “WHO Coronavirus (Covid-19) Dashboard”, http://Covid-19.who.int . Erişim: 06.12.2023
15. Erer, D. (2022). The Asymmetrıcal Impact Of Policy Responses On Volatility Of Sovereign Default Swaps. Financial Studies, 26(3).
16. Ericsson, J., Jacobs, K., & Oviedo, R. (2009). The determinants of credit default swap premia. Journal of financial and quantitative analysis, 44(1), 109-132.
17. Forte, S., & Pena, J. I. (2009). Credit spreads: An empirical analysis on the informational content of stocks, bonds, and CDS. Journal of Banking & Finance, 33(11), 2013-2025.
18. Galil, K., Shapir, O. M., Amiram, D., & Ben-Zion, U. (2014). The determinants of CDS spreads. Journal of Banking & Finance, 41, 271-282.
19. Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: journal of the Econometric Society, 424-438.
20. Ho, S. H. (2016). Long and short-runs determinants of the sovereign CDS spread in emerging countries. Research in International Business and Finance, 36, 579-590.
21. Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of econometrics, 115(1), 53-74.
22. İlhan, B. ve Bayır, M. (2021). “BİST Sınai ve BİST Mali Endeksi ile CDS, Faiz, Döviz Kuru, Toplam Krediler ve Covid-19 Arasındaki Dinamik İlişki”, Üçüncü Sektör Sosyal Ekonomi Dergisi, 56(4), 3090-311
23. Kajurova, V. (2015). The determinants of CDS spreads: The case of UK companies. Procedia economics and finance, 23, 1302-1307.
24. Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of econometrics, 90(1), 1-44.
25. Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: asymptotic and finite-sample properties. Journal of econometrics, 108(1), 1-24.
26. Maddala, G.S. and Wu, Shaowen, (1999), A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test, Oxford Bulletin of Economics and Statistics, 61, 631-652.
27. Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. The Journal of finance, 29(2), 449-470.
28. Miyakawa, D., & Watanabe, S. (2014). What determines CDS prices? Evidence from the estimation of protection demand and supply. International review of finance, 14(1), 1-28.
29. Özdemir, L. (2020). “Covid-19 Pandemisinin Bist Sektör Endeksleri Üzerine Asimetrik Etkisi”, Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 5(3).
30. Pan, W. F., Wang, X., Wu, G., & Xu, W. (2021). The Covid-19 pandemic and sovereign credit risk. China Finance Review International, 11(3), 287-301.
31. Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and statistics, 61(S1), 653-670.
32. Pelster, M., & Vilsmeier, J. (2018). The determinants of CDS spreads: evidence from the model space. Review of Derivatives Research, 21, 63-118.
33. Procasky, W. J., & Yin, A. (2023). The impact of Covid-19 on the relative market efficiency and forecasting ability of credit derivative and equity markets. International Review of Financial Analysis, 90, 102926.
34. Risks, C. S., & Soundness, R. F. (2008). Global financial stability report. International Monetary Fund, Washington.
35. Shahzad, S. J. H., Nor, S. M., Ferrer, R., & Hammoudeh, S. (2017). Asymmetric determinants of CDS spreads: US industry-level evidence through the NARDL approach. Economic Modelling, 60, 211-230.
36. Vurur, N.S. (2021). Bist 100 endeksi ile CDS Primleri arasındaki ilişkide Covıd-19 etkisi. Uluslararası İktisadi ve İdari İncelemeler Dergisi, (31), 97-112.