Research article
Special Issues
The behavior of Sovereign Credit Default Swaps (CDS) spread: evidence from Turkey with the effect of Covid-19 pandemic
-
Received:
09 May 2020
Accepted:
30 June 2020
Published:
03 July 2020
-
-
JEL Codes:
C22, E44, F30, G12, G15
-
-
This study examines how sovereign CDS spreads of Turkey behave in Covid-19 pandemic times by considering that CDS spreads reflect the riskiness, vulnerability, financial stability, and macroeconomic stability of countries and CDS spreads of most of the emerging countries have increased with the emergence of Covid-19 pandemic. Therefore, the study focuses on the year 2020 which includes before Covid-19 and Covid-19 pandemic times periods. In this context, daily data between 12.06.2019 and 06.16.2020, 6 independent variables, and 6 Covid-19 situations are analyzed by employing Multivariate Adaptive Regression Splines (MARS) method. The findings reveal that (i) influential factors on Turkey's CDS spreads are BIST100 index, VIX index, MSCI Turkey index, and USD/TL foreign exchange rates for the period which is before Covid-19 pandemic times; (ii) MSCI emerging market index, number of new deaths from Covid-19, USD/TL foreign exchange rates, weighted average cost of funds, number of new cases from Covid-19, and VIX index have effect on Turkey's CDS spreads in Covid-19 pandemic times, respectively; (iii) on the other hand, number of cumulative cases, number of cumulative deaths, and measures do not have effect on Turkey's CDS spreads in any period. Taking precautions to decrease negative effects on Turkey's CDS spreads by considering the importance of deaths number from Covid-19 pandemic is very important. Hence, Turkey could stimulate foreign portfolio investment inflows with decreasing CDS spreads.
Citation: Mustafa Tevfik Kartal. The behavior of Sovereign Credit Default Swaps (CDS) spread: evidence from Turkey with the effect of Covid-19 pandemic[J]. Quantitative Finance and Economics, 2020, 4(3): 489-502. doi: 10.3934/QFE.2020022
-
Abstract
This study examines how sovereign CDS spreads of Turkey behave in Covid-19 pandemic times by considering that CDS spreads reflect the riskiness, vulnerability, financial stability, and macroeconomic stability of countries and CDS spreads of most of the emerging countries have increased with the emergence of Covid-19 pandemic. Therefore, the study focuses on the year 2020 which includes before Covid-19 and Covid-19 pandemic times periods. In this context, daily data between 12.06.2019 and 06.16.2020, 6 independent variables, and 6 Covid-19 situations are analyzed by employing Multivariate Adaptive Regression Splines (MARS) method. The findings reveal that (i) influential factors on Turkey's CDS spreads are BIST100 index, VIX index, MSCI Turkey index, and USD/TL foreign exchange rates for the period which is before Covid-19 pandemic times; (ii) MSCI emerging market index, number of new deaths from Covid-19, USD/TL foreign exchange rates, weighted average cost of funds, number of new cases from Covid-19, and VIX index have effect on Turkey's CDS spreads in Covid-19 pandemic times, respectively; (iii) on the other hand, number of cumulative cases, number of cumulative deaths, and measures do not have effect on Turkey's CDS spreads in any period. Taking precautions to decrease negative effects on Turkey's CDS spreads by considering the importance of deaths number from Covid-19 pandemic is very important. Hence, Turkey could stimulate foreign portfolio investment inflows with decreasing CDS spreads.
References
[1]
|
Akçelik F, Fendoğlu S (2019) Country Risk Premium and Domestic Macroeconomic Fundamentals When Global Risk Appetite Slides. CBRT Research and Monetary Policy Department, No. 2019-04.
|
[2]
|
Alexander C, Kaeck A (2008) Regime Dependent Determinants of Credit Default Swap Spreads. J Bank Financ 32: 1008-1021. doi: 10.1016/j.jbankfin.2007.08.002
|
[3]
|
Benbouzid N, Mallick SK, Sousa RM (2017) An International Forensic Perspective of the Determinants of Bank CDS Spreads. J Financ Stability 33: 60-70. doi: 10.1016/j.jfs.2017.10.004
|
[4]
|
CBRT (2020a) Inflation Report 2020-I. Available from: https://www.tcmb.gov.tr/wps/wcm/connect/EN/TCMB+EN/Main+Menu/Publications/Reports/Inflation+Report.
|
[5]
|
CBRT (2020b) Electronic Data Distribution System (EVDS). Available from: https://evds2.tcmb.gov.tr/index.php?/evds/serieMarket.
|
[6]
|
Cremers KM, Driessen J, Maenhout P (2008) Explaining the Level of Credit Spreads: Option-Implied Jump Risk Premia in a Firm Value Model. Rev Financ Stud 21: 2209-2242. doi: 10.1093/rfs/hhn071
|
[7]
|
Dooley M, Hutchison M (2009) Transmission of the US Subprime Crisis to Emerging Markets: Evidence on the Decoupling-Recoupling Hypothesis. J Int Money Financ 28: 1331-1349. doi: 10.1016/j.jimonfin.2009.08.004
|
[8]
|
Ertuğrul HM, Öztürk H (2013) The Drivers of Credit Swap Prices: Evidence from Selected Emerging Market Countries. Emerging Markets Financ Trade 49: 228-249. doi: 10.2753/REE1540-496X4905S514
|
[9]
|
Fontana A, Scheicher M (2016) An Analysis of Euro Area Sovereign CDS and Their Relation with Government Bonds. J Bank Financ 62: 126-140. doi: 10.1016/j.jbankfin.2015.10.010
|
[10]
|
Friedman J (1991) Multivariate Adaptive Regression Splines. Annals Stat 19: 1-141. doi: 10.1214/aos/1176347963
|
[11]
|
Galil K, Shapir OM, Amiram D, et al. (2014) The Determinants of CDS Spreads. J Bank Financ 41: 271-282. doi: 10.1016/j.jbankfin.2013.12.005
|
[12]
|
Galil K, Soffer G (2011) Good News, Bad News and Rating Announcements: An Empirical Investigation. J Bank Financ 35: 3101-3119. doi: 10.1016/j.jbankfin.2011.04.010
|
[13]
|
Goh ATC, Zhang Y, Zhang R, et al. (2017) Evaluating Stability of Underground Entry-Type Excavations Using Multivariate Adaptive Regression Splines and Logistic Regression. Tunnelling Underground Space Tcehnology 70: 148-154. doi: 10.1016/j.tust.2017.07.013
|
[14]
|
Hasan I, Liu L, Zhang G (2016) The Determinants of Global Bank Credit-Default-Swap Spreads. J Financ Serv Res 50: 275-309. doi: 10.1007/s10693-015-0232-z
|
[15]
|
Hassan MK, Kayhan S, Bayat T (2017). Does Credit Default Swap Spread Affect the Value of the Turkish Lira Against the US Dollar? Borsa İstanbul Rev 17: 1-9.
|
[16]
|
Hastie T, Tibshirani R, Friedman J (2009) The Elements of Statistical Learning: Data Mining, Inference and Prediction. 2nd Edition. New York: Springer.
|
[17]
|
Hibbert AM, Pavlova I (2017) The Drivers of Sovereign CDS Spread Changes: Local versus Global Factors. Financ Rev 52: 435-457. doi: 10.1111/fire.12140
|
[18]
|
Johnson TC (2002) Rational Momentum Effects. J Financ 57: 585-608. doi: 10.1111/1540-6261.00435
|
[19]
|
Kocsis Z, Monostori Z (2016) The Role of Country-Specific Fundamentals in Sovereign CDS Spreads: Eastern European Experiences. Emerging Markets Rev 27: 140-168. doi: 10.1016/j.ememar.2016.05.003
|
[20]
|
Lahiani A, Hammoudeh S, Gupta R (2016) Linkages between Financial Sector CDS Spreads and Macroeconomic Influence in a Nonlinear Setting. Int Rev Econ Financ 43: 443-456. doi: 10.1016/j.iref.2016.01.007
|
[21]
|
Liu LX, Zhang L (2008) Momentum Profits, Factor Pricing, and Macroeconomic Risk. Rev Financ Stud 21: 2417-2448. doi: 10.1093/rfs/hhn090
|
[22]
|
Morgan Stanley (2020) EEMEA Covid-19 Impact & Response, Research Report.
|
[23]
|
Orhan A, Kırıkkaleli D, Ayhan F (2019) Analysis of Wavelet Coherence: Service Sector Index and Economic Growth in an Emerging Market. Sustainability 11: 6684. doi: 10.3390/su11236684
|
[24]
|
Sagi JS, Seasholes MS (2007) Firm-Specific Attributes and the Cross-Section of Momentum. J Financ Econ 84: 389-434. doi: 10.1016/j.jfineco.2006.02.002
|
[25]
|
Shahzad SJH, Nor SM, Ferrer R, et al. (2017) Asymmetric Determinants of CDS Spreads: US Industry-Level Evidence through the NARDL Approach. Econ Model 60: 211-230. doi: 10.1016/j.econmod.2016.09.003
|
[26]
|
Turkey Ministry of Health (2020) Covid-19 Numbers. Available from: https://covid19.saglik.gov.tr.
|
[27]
|
World Health Organization (2020) Covid-19 Numbers. Available from: https://covid19.who.int.
|
[28]
|
Yang L, Yang L, Hamori S (2018) Determinants of Dependence Structures of Sovereign Credit Default Swap Spreads between G7 and BRICS Countries. Int Rev Financ Anal 59: 19-34. doi: 10.1016/j.irfa.2018.06.001
|
[29]
|
Zhang BY, Zhou H, Zhu H (2009) Explaining Credit Default Swap Spreads with the Equity Volatility and Jump Risks of Individual Firms. Rev Financ Stud 22: 5099-5131. doi: 10.1093/rfs/hhp004
|
-
-
-
-