ÜLKELERĠN KREDĠ TEMERRÜT TAKASI (CDS) PRĠMLERĠNĠN DĠNAMĠK NEDENSELLĠK ĠLĠġKĠSĠ ĠLE ĠNCELENMESĠ

Bu çalıĢmada, Türkiye‟nin kredi temerrüt takası (CDS) primleri ile BRICS ülkelerinin (Brezilya, Rusya, Hindistan, Çin, Güney Afrika) ve Avrupa Birliği‟nin lider ekonomilerinin (Almanya, Fransa, Ġngiltere, Ġtalya, Ġspanya) kredi temerrüt takası primleri arasındaki dinamik nedensellik iliĢkisi, iki aĢamalı çapraz korelasyon fonksiyonu (CCF) yöntemi ile incelenmiĢtir. Ġlk aĢamada, ülke CDS‟leri EGARCH modelleri ile tahmin edilmiĢtir. Ġkinci aĢamada, ülke CDS‟lerinin EGARCH modellemesinden elde edilen standart hatalar ve kareler kullanılarak, varyanstaki ve ortalamadaki nedensellikleri, çapraz korelasyon fonksiyonu yöntemi test edilmiĢtir. Elde edilen test sonuçlarına göre; BRICS ülkeleri tarafında; Türkiye ile Çin, Güney Afrika ve Hindistan arasında karĢılıklı nedensellik iliĢkisi varken, Rusya‟nın tek yönlü olarak Türkiye‟yi etkilediği tespit edilmiĢtir. Avrupa Birliği tarafında ise Almanya, Fransa ve Türkiye arasında karĢılıklı nedensellik iliĢkisi görülürken, Ġngiltere ve Ġtalya‟nın tek yönlü olarak Türkiye‟yi etkilediği görülmüĢtür. Ayrıca bu çalıĢma ile CFF YaklaĢımının ülkelerin CDS‟leri arasındaki nedensellik iliĢkisini ölçmede etkili bir method olduğu görülmüĢtür

ANALYSIS OF THE CREDIT DEFAULT SWAP (CDS) OF COUNTRIESWITH THE DYNAMIC CAUSALITY RELATION

In this study, the dynamic causality relation of the Credit Default Swaps (CDS) of Turkey, BRICS countries (Brazil, Russia, India, China, South Africa) and the most important EU economies (Germany, France, The United Kingdom, Italy, Spain) are analysed with the two-stage Cross Correlation Function (CCF) Approach. At the first stage, the CDS of the countries are estimated with EGARCH models. During the second stage, the standardized residuals and squares obtained from the EGARCH models are used for the causality test in the mean and variance for CDS values. According to the achieved test results it exposed that, across the BRICS countries there is a mutual causality relation between Turkey and China, South Africa and India, whereat it occurred that Russia has a unilateral effect on Turkey. Across the EU countries it exposed that there is a mutual causality relation between Germany, France and Turkey, where as it occurred that England and Italy have a unilateral effect on Turkey. In addition, it transpired that CFF approach is an effective method for measuring the causality relation of CDS of countries.

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AKARÇAY, M. (2016), Kredi Temerrüt Swapları, TeminatlandırılmıĢ Borç Yükümlülükleri ve 2008 Küresel Krizi. Ekonomi, Politika & Finans AraĢtırmaları Dergisi, 1(1-2), 23-39.
ALTURKI, Sultan Abdulaziz M; HIBBERT, Ann Marie. 2021. The Impact of Oil Shocks on Sovereign Default Risk. Policy Research Working Paper;No. 9546. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/ 10986/ 35142 License: CC BY 3.0 IGO.”
BARTRAM, Söhnke M. and CONRAD, Jennifer S. and LEE, Jongsub and Subrahmanyam, MARTI G., Credit Default Swaps Around the World (January 2021). CEPR Discussion Paper No. DP15668, Available at SSRN: https://ssrn.com/abstract=3783886
BOYRIEA , M. E., & PAVLOVA, I. (2016), Dynamic Interdependence of Sovereign Credit Default Swaps in BRICS And MIST Countries. Applied Economics, 48(7), 563– 575. doi:http://dx.doi.org/10.1080/00036846.2015.1083089
CALICE, G, Zeng, M. The term structure of sovereign credit default swap and the cross section of exchange rate predictability. Int J Fin Econ. 2021; 26: 445– 458. https://doi.org/ 10.1002/ijfe.1798
CHEUNG, Y.-W., & NG, L. (1996), A Causality-in-Variance Test and Its Application to Financial Market Prices. Journal of Econometrics, 72(1-2), 33-48. doi:https://doi.org/10.1016/0304-4076(94)01714-X
DEĞĠRMENCĠ, N., & PABUÇCU, H. (2016), Borsa Ġstanbul ve Risk Primi Arasındaki EtkileĢim: VAR ve NARX Model. Akademik Sosyal AraĢtırmalar Dergisi, 4, 248-261. doi:10.16992/ASOS.7594
HANCI, G. (2014), Kredi Temerrüt Takasları ve Bist-100 Arasındaki ĠliĢkinin Ġncelenmesi. Maliye Finans Yazilari, 28(102), 9-22.
HONG, Y. (2001), A Test for Volatility Spillover with Application to Exchange Rates. Journal of Econometrics, 103(1), 183-224. doi:10.1016/S0304-4076(01)00043-4
KANNO, Masayasu, Sovereign Default Risk Valuation Using CDS Spreads: Evidence from the COVID-19 Crisis (January 22, 2021). Available at SSRN: https://ssrn.com/abstract=3772135 or http://dx.doi.org/10.2139/ssrn.3772135
KORKMAZ, T., & ÇEVĠK, E. Ġ. (2009), Reel Kesim Güven Endeksi ile ĠMKB 100 Endeksi Arasındaki Dinamik Nedensellik ĠliĢkisi. Ġstanbul Üniversitesi ĠĢletme Fakültesi Dergisi, 38(1), 24-37.
KORKMAZ, T., ÇEVĠK, E. Ġ., & ATUKEREN, E. (2012), Return and Volatility Spillovers Among CIVETS Stock Markets. Emerging Markets Rewiev, 230-252.
NELSON, D. B. (1991), Conditional Heteroskedasticity In Asset Returns: A New Approach. Econometrica, 59(2), 347-370 .
STOLBOV, M. (2014), The causal linkages between sovereign CDS prices for the BRICS and major European economies. Economics Discussion Papers(9), 1-22.
STOLBOV, M. (2016), Causality between sovereign, quasi-sovereign credit risks and global volatility: The case of Russia. Journal of Eurasian Studies(7), 71-84.
ġAHĠN, C. (2018), Cari Açık Değerleri CDS Puanları Üzerinde Etkili midir? Türkiye Ġçin Bir Perspektif. Muhasebe ve Finansman Dergisi, 189-204. doi:10.25095/mufad.465937
TOYOSHIMA, Y., & SHIGEYUKI , H. (2012), Volatility Transmission of Swap Spreads Among The US, Japan and The UK: A Cross-Correlation Function Approach. Applied Financial Economics, 11, 849-862.
YA Liu, BUHUI Qiu, TENG Wang, Debt Rollover Risk, Credit Default Swap Spread And Stock Returns: Evidence from the COVID-19 crisis, Journal of Financial Stability, Volume 53, 2021, 100855, ISSN 1572-3089, https://doi.org/10.1016/j.jfs.2021.100855