How Vulnerable is the Turkish Stock Market to the Credit Default Swap? Evidence from the Markov Switching GARCH Model

Öz

This study aims to investigate the effect of the credit default swap (CDS) on the Turkish stock market. More specifically, it analyses whether the relationship between CDS and the Turkish stock market has changed during the period of unprecedented stock returns in 2022. The Markov Switching GARCH method is preferred because of its many advantages in the analysis of the return series of the variables. Two different models are estimated for the full sample weekly period of 2010:01-10/2022:12-11 and the subsample weekly period of 2010:01-10/2021:12-05. The subsample period is more optimal than the full sample period. Nevertheless, the findings of both sample periods are included to make a comparison. The effect of CDS on the Turkish stock market is greater in the high-volatility regime than in the lowvolatility regime. CDS has a negative impact on the Turkish stock market in both low and high volatility periods. The most striking finding is that CDS affects the Turkish stock market approximately twice as much in the subsample period as in the full sample period in both regimes. Policymakers should follow risk-oriented policies instead of policies against the wind against the risk of a possible boom in financial markets.

Anahtar Kelimeler

• Credit default swap
• Turkish stock market
• Markov Switching GARCH

Kaynakça

1. Altınok, H., & Akça, A. (2021). BRICS+ T ülkelerinde sanayi üretim endeksi ve kredi temerrüt takası arasındaki ilişki: Konya bootstrap nedensellik yaklaşımı. Maliye Dergisi, (180), 252-269. google scholar
2. Ang, A., & Timmermann, A. (2011). Regime changes and financial markets. Netspar Discussion Paper. DP 06/2011-068, 1-32. google scholar
3. Anton, S. G., & Afloarei Nucu, A. E. (2020). Sovereign credit default swap and stock markets in Central and Eastern European countries: Are feedback effects at work?. Entropy, 22(3), 338. Doi: https://doi.org/10.3390/e22030338 google scholar
4. Asandului, M., Lupu, D., Mursa, G., & Musetescu, R. (2015). Dynamic relations between CDS and stock markets in Eastern European countries. Economic Computation and Economic Cybernetics Studies and Research, Issue 4/2015. google scholar
5. Augustin, P., Subrahmanyam, M. G., Tang, D. Y., & Wang, S. Q. (2016). Credit default swaps. Annual Review of Financial Economics, 8, 175-196. google scholar
6. Ballester, L., Escriva, A. M., & Gonzalez-Urteaga, A. (2021). The Nexus between sovereign CDS and stock market volatility: new evidence. Mathematics, 9(11), 1201. Doi: https://doi.org/10.3390/math9111201 google scholar
7. Bauwens, L., Preminger, A., & Rombouts, J. V. (2010). Theory and inference for a Markov switching GARCH model. The Econometrics Journal, 13(2), 218-244. Doi: https://doi. org/10.1111/j.1368-423X.2009.00307.x google scholar
8. Bildirici, M., & Ersin, Ö. (2014). Modeling Markov switching ARMA-GARCH neural networks models and an application to forecasting stock returns. The Scientific World Journal, 2014. Doi: https:// doi.org/10.1155/2014/497941 google scholar

9. Bildirici, M., Sonüstün, B., & Gökmenoğlu, S. M. (2019, November). CDS-Stock market chaotic relationship-Turkish stock market case. In AIP Conference Proceedings (Vol. 2178, No. 1, p. 030068). Doi: https://doi.org/10.1063/1.5135466 google scholar
10. Bolaman Avcı, Ö. (2020). Interaction between CDS premiums and stock markets: Case of Turkey. Ömer Halisdemir Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 13(1), 1-8. Doi: https://doi. org/10.25287/ohuiibf.526638 google scholar
11. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307-327. Doi: https://doi.org/10.1016/0304-4076(86)90063-1 google scholar
12. Celik, S., & Koc, Y. D. (2016). Relationship between sovereign credit default swap and stock markets: the case of Turkey. The Macrotheme Review, 5(4), 36-40. google scholar
13. Central Bank of the Republic of Turkey, the Electronic Data Delivery System, (Date accessed: 12/20/2022). google scholar
14. Ceylan, F., Tuzun, O., & Ekinci, R. (2018). The effect of credit default swaps (CDS) on BIST100 in Turkey: MS-VAR approach. Ecoforum journal, 7(1). google scholar
15. Chau, F., Han, C., & Shi, S. (2018). Dynamics and determinants of credit risk discovery: Evidence from CDS and stock markets. International Review of Financial Analysis, 55, 156-169. Doi: https:// doi.org/10.1016/j.irfa.2017.11.004 google scholar
16. Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica: Journal of the Econometric Society, 1057-1072. Doi: https://doi. org/10.2307/1912517 google scholar
17. Dieobold, F. X. (1986). Modeling the persistence of conditional variances: A comment. Econometric Reviews, 5(1), 51-56. Doi: https://doi.org/10.1080/07474938608800096 google scholar
18. Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society, 987-1007. Doi: https://doi.org/10.2307/1912773 google scholar
19. Esen, S., Zeren, F., & Şimdi, H. (2015). CDS and stock market: panel evidence under cross-section dependency. South-Eastern Europe Journal of Economics, 13(1). google scholar
20. Fei, F., Fuertes, A. M., & Kalotychou, E. (2017). Dependence in credit default swap and equity markets: Dynamic copula with Markov-switching. International Journal of Forecasting, 33(3), 662678. Doi: https://doi.org/10.1016/j.ijforecast.2017.01.006 google scholar
21. 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. Doi: https://doi. org/10.1016/j.jbankfin.2009.04.015 google scholar
22. Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica: Journal of the Econometric Society, 357-384. Doi: https://doi. org/10.2307/1912559 google scholar
23. Hammoudeh, S., & Sari, R. (2011). Financial CDS, stock market and interest rates: Which drives which?. The North American Journal of Economics and Finance, 22(3), 257-276. Doi: https://doi. org/10.1016/j.najef.2011.04.001 google scholar
24. Inclan, C., & Tiao, G. C. (1994). Use of cumulative sums of squares for retrospective detection of changes of variance. Journal of the American Statistical Association, 89(427), 913-923. Doi: https://doi.org/10.1080/01621459.1994.10476824 google scholar
25. Kandemir, T., Vurur, N. S., & Gökgöz, H. Türkiye’nin CDS primleri ile Bist100, döviz kurları ve tahvil faizleri arasındaki etkileşimin cDCC-EGARCH ve varyansta nedensellik analizleriyle incelemesi. Karamanoğlu Mehmetbey Üniversitesi Sosyal Ve Ekonomik Araştırmalar Dergisi, 24(42), 510-526. google scholar
26. Lamoureux, C. G., & Lastrapes, W. D. (1990). Persistence in variance, structural change, and the GARCH model. Journal of Business & Economic Statistics, 8(2), 225-234. google scholar
27. Longstaff, F. A., Mithal, S., & Neis, E. (2005). Corporate yield spreads: default risk or liquidity? New evidence from the credit default swap market. The Journal of Finance, 60(5), 221-353. google scholar
28. Mateev, M. (2019). Volatility relation between credit default swap and stock market: new empirical tests. Journal of Economics and Finance, 43(4), 681-712. Doi: https://doi.org/10.1007/s12197-018-9467-5 google scholar
29. Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. The Journal of finance, 29(2), 449-470. Doi: https://doi.org/10.2307/2978814 google scholar
30. Modigliani, F., & Miller, M. H. (1958). The cost of capital, corporation finance and the theory of investment. The American economic review, 48(3), 261-297. google scholar
31. Ozsoy, T. (2022). Turkish Stock Market’s 80% rally fuels world’s top gains in 2022, Bloomberg, https://www.bloomberg.com/news/articles/2022-11-22/inflation-hit-turks-lift-stocks-to-world-s-top-2022-performer?leadSource=uverify%20wall, (Date accessed: 12/22/2022). google scholar
32. Phillips, P. C., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346. Doi: https://doi.org/10.1093/biomet/75.2.335 google scholar
33. Sanso, A., Carrion, J. L., & Arago, V. (2004). Testing for changes in the unconditional variance of financial time series. Revista de Economfa Financiera, 2004, 4, p. 32-52. google scholar
34. Saritaş, H., Kiliç, E., & Nazlioğlu, E. H. (2021). CDS primleri ve derecelendirme (raiting) notları ile BIST 100 endeksi arasındaki ilişkinin incelenmesi: Türkiye örneği. Maliye ve Finans Yazıları, (116), 73-92. Doi: https://doi.org/10.33203/mfy.854876 google scholar
35. Schwert, G. W. (1989). Why does stock market volatility change over time?. The Journal of Finance, 44(5), 1115-1153. Doi: https://doi.org/10.1111/j.1540-6261.1989.tb02647.x google scholar
36. Sovbetov, Y., & Saka, H. (2018). Does it take two to tango: Interaction between credit default swaps and national stock indices. Journal of Economics and Financial Analysis, 2(1), 129-149. google scholar
37. Sun, X., Wang, J., Yao, Y., Li, J., & Li, J. (2020). Spillovers among sovereign CDS, stock and commodity markets: A correlation network perspective. International Review of Financial Analysis, 68, 101271. Doi: https://doi.org/10.1016/j.irfa.2018.10.008 google scholar
38. Topaloğlu, E. E., & Ege, İ. (2020). Kredi temerrüt swapları (CDS) ile Borsa İstanbul 100 endeksi arasındaki ilişki: kısa ve uzun dönemli zaman serisi analizleri. İşletme Araştırmaları Dergisi, 12(2), 1373-1393. Doi: https://doi.org/10.20491/isarder.2020.918 google scholar
39. Ustaoğlu, E. (2022). Analysis of Relations between CDS, Stock Market, and Exchange Rate: Evidence from Covid-19. Ekonomi Politika ve Finans Araştırmaları Dergisi, 7(2), 301-315. Doi: https://doi. org/10.30784/epfad.1085420 google scholar
40. Wee, D. C., Chen, F., & Dunsmuir, W. T. (2020). Likelihood inference for Markov switching GARCH (1,1) models using sequential Monte Carlo. Econometrics and Statistics. Doi: https://doi. org/10.1016/j.ecosta.2020.03.004 google scholar
41. www.investing.com, (Date accessed: 12/20/2022). google scholar