Kredi Temerrüt Swapları (CDS) ile Borsa İstanbul 100 Endeksi Arasındaki İlişki: Kısa ve Uzun Dönemli Zaman Serisi Analizleri

Amaç – Çalışmada, 2010:01-2019:06 dönemi için Türkiye Kredi Temerrüt Swapı (CDS) ile Borsa İstanbul (BIST) 100 Endeks getirisi arasındaki kısa ve uzun vadeli ilişkiyi ortaya çıkarmak amaçlanmıştır. Yöntem – Araştırmada, Sabit, sabit ve trend, sabitte kırılma, sabitte kırılma ve trend, trendde kırılma, rejimde kırılma, rejimde ve trendde kırılma modellerine ilişkin kısa ve uzun vadeli zaman serisi analizleri yöntem olarak belirlenmiştir. Bulgular – CDS ve BIST100 serilerinin düzey değerlerinde durağan oldukları belirlenmiştir. CDS primleri ile BIST100 getirisi arasındaki uzun vadeli eşbütünleşme ilişkisinin varlığı tespit edilmiştir. CDS ile BIST100 getirisi arasında uzun dönemde FMOLS ve CCR'ye göre %25, DOLS'e göre %43 negatif yönlü bir ilişki tespit edilmiştir. Granger nedensellik test sonuçlarına göre, CDS’ten BIST100 getirisine doğru tek yönlü nedensellik ilişkisine rastlanılmıştır. Etki-tepki analizi sonucunda, CDS’teki bir şokun BIST100 getirisinde 2. ayda 0.013 düşüşe yol açtığı ve bu etkinin 5. ayda ortadan kalkarak sıfıra yakınsadığı belirlenmiştir. Varyans ayrıştırmasına göre ise ve 9. ay itibariyle BIST100 getirisindeki değişimlerin yaklaşık %0,20’lik kısmının CDS değişkeni tarafından meydana geldiği tespit edilmiştir. Tartışma – Araştırmada ulaşılan CDS ile BIST100 getirisi arasındaki negatif yönlü ilişkinin teorik olarak desteklendiğini ve ülke riskinin arttıkça pay piyasa getirisinin azaldığını söylemek mümkündür.

The Relationship between Credit Default Swaps and Borsa Istanbul 100 Index: The Short and Long Term Time Series Analysis

Purpose – This study that focuses on the analyzing the short and long terms impacts of Turkey’s CDS on return of BIST100 Index in 2010:01-2019:06 periods. Design/methodology/approach – Considering the the short and long term time series analysis used to process with constant, constant-trend, level shift, level shift-trend, trend shift, regime shift, regime-trend shift models. Findings – It was determined that both series were stationary at the level. The cointegration was determined relationship between CDS and return of BIST100. A negative relationship was found between CDS and BIST100 return in the long term by 25% according to FMOLS and CCR and 43% to DOLS. According to short-term error correction model results, it was found that the short-term deviations in return of BIST100 equilibrated after 2.43 months and 41.1% of the deviations in return of BIST100 disappeared. Granger causality test results, there is Granger causality from CDS to BIST100 return. As a result of the impulse-response functions, it was determined that a shock in CDS caused 0.013 decrease return of BIST100 in 2 months and this effect disappeared in 5 months and converged to zero. According to variance decomposition, It has been found that approximately 0.20% of the changes in BIST100 return as of the 9th month is caused by CDS variable. Discussion – It is possible to say that the negative relationship between the CDS and BIST100 return reached in the research is supported theoretically and the market return decreases as the country risk increases.

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Arai, Y., and Kurozumi, E. (2007). Testing for the null hypothesis of cointegration with a structural break, Econometric Review, 2, 705-739.
Balı, S. ve Yılmaz, Z. (2012). Kredi temerrüt takası marjları ile İMKB 100 endeksi arasındaki ilişki, 16. Finans Sempozyumu, Erzurum, 83-104.
Basazinew, S. T. and Vashkevich, A. (2013). Relationshıp between sovereign credit default swap and stock marketsthe case of east asia, master thesis, Umeå School of Business and Economics.
Bektur, Ç. ve Malcıoğlu, G. (2017). Kredi temerrüt takasları ile BIST 100 endeksi arasındaki ilişki: Asimetrik nedensellik analizi, AİBÜ Sosyal Bilimler Enstitüsü Dergisi, 17 (3), 73-83.
Breusch, T. S. (1978). Testing for autocorrelation in dynamic linear models, Australian Economic Papers, 17, 334– 355.
Brooks, C. (2008). Introductory Econometrics for Finance, Cambridge University Press, New York.
Carrion-i-Silvestre, J. and Sansó, L. A. (2006). Testing the null of cointegration with structural breaks, Oxford Bulletin of Economics and Statistics, 68 (5), 623-646.
Ceylan, I. E., Ceylan, F., Tuzun, O. ve Ekinci, R. (2018). The effect of credit default swaps (CDS) on BIST100 in Turkey: MSVAR approach, ECOFORUM, 7 (14).
Chau, F., Han, C. and Shi, S. (2018). Dynamics and determinants of credit risk discovery: evidence from CDS and stock markets, International Review of Financial Analysis, 55, 156-169.
Choudhry, M. (2006). The credit default swap basis, New York, Bloomberg Press.
Coronado, M., Corzo, T. and Lazcano, L. (2011). A case for Europe: The relationship between sovereign CDS and stock ındexes, Frontiers in Finance and Economics, 9 (2), 32-63.
Değirmenci, N. ve Pabuçcu, H. (2016). Borsa İstanbul ve risk primi arasındaki etkileşim: VAR ve NARX model, Akademik Sosyal Araştırmalar Dergisi, 4, 248-261.
Dhamala, M., Rangarajan, G. and Ding, M. (2008). Estimating granger causality from fourier and wavelet transforms of time series data, Phys. Rev. Let, 100, 018701.
Duffie, D. (1999). Credit swap valuation, Financial Analysts Journal, 55 (1), 73-87.
Enders, W. and Lee, J. (2004). Testing for a unit root with a nonlinear fourier function, Mimeo, University of Alabama.
Engle, R. F. and Granger, C. W. J. (1987). Cointegration and error correction: representation, estimation and testing, Econometrica, 55, 251-276.
Eren, M. ve Başar S. (2016). Makroekonomik faktörler ve kredi temerrüt takaslarının BIST-100 endeksi üzerindeki etkisi: ARDL yaklaşımı, Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 30 (3), 576-589.
Fung, H. G., Sierra, G. E., Yau, J. and Zhang, G. (2008). Are the US stock market and credit default swap market related? Evidence from the cdx ındices, The Journal of Alternative Investments, 11 (1), 43-61.
Godfrey, L. G. (1978). Testing for higher order serial correlation in regression equations when the regressors include lagged dependent variables, Econometrica, 46, 1303-1310.
Granger, C. W. J. (1969), Investigating causal relations by econometric models and cross-spectral models, Econometrica, 37, 424-438.
Gregory, A. W. and Hansen, B. E. (1996a). Residual-based tests for cointegration in models with regime shifts, Journal of Econometrics, 70, 99-126.
Gregory, A. W. and Hansen, B. E. (1996b). Tests for cointegration in models with regime and trend shifts, Oxford Bulletin of Economics and Statistics, 58, 555-560.
Hancı, G. (2014). Kredi temerrüt takaslar ve BİST 100 arasındaki ilişkinin incelenmesi, Maliye Finans Yazıları, 28, 9-24.
Im, K. S., Lee, J. and Tieslau, M. A. (2014). More powerful unit root tests with non-normal errors. In Sickles, R. & Horrace, W. (Eds.), Festschrift in Honor of Peter Schmidt (315–342). New York: Springer.
Koop, G., Pesaran, M. H. and Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models, Journal of Econometrics, 74, 119–147.
Lee, J. and Strazicich, M. C. (2004). Minimum LM unit root test with one structural break, Working Paper, Department of Economics, Appalachain State University.
Nazlıoğlu, S., Görmüş, A. and Soytaş, U. (2018). Oil prices and monetary policy in emerging markets: Structural shifts in causal linkages, Emerging Markets Finance and Trade, DOI: 10.1080/1540496X.2018.1434072
Nazlıoğlu, S., Gupta, R., Görmüş, A. and Soytaş, U. (2019). Price and volatility linkages between ınternational reıts and oil markets, University of Pretoria Department of Economics Working Paper Series, 2019-54.
Nazlıoğlu, Ş., Görmüş, N. A. and Soytaş, U. (2016). Oil prices and real estate ınvestment trusts (reits): Gradualshift causality and volatility transmission analysis, Energy Economics, 60, 168-175.
Park, J. Y. (1992). Canonical cointegrating regressions, Econometrica, 60, 119–143.
Pesaran, M. H. and Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models, Economics Letters, 58, 17-29.
Phillips, P. C . B . and Hansen, B. E. (1990). Statistical inference in instrumental variable regression with I(1) processes, Review of Economic Studies, 57, 99–125.
Phillips, P. C. B. and Ouliaris, S. (1990). Asymptotic properties of residual based tests for cointegration, Econometrica, 58, 165–193.
Saikkonen, P. (1992). Estimation and testing of cointegrated systems by an autoregressive approximation, Econometric Theory, 8, 1-27.
Shahzad, S. J. H., Mensi, W., Hammoudeh, S., Balcilar, M. and Shahbaz, M. (2018). Distribution specific dependence and causality between industry-level U.S. credit and stock markets, Journal of International Financial Markets, Institutions & Money, 52, 114-133.
Shin Y. (1994). A residual-based test of the null of cointegration against the alternative of no cointegration, Econometric Theory, 10, 91–115.
Sims, C. A. (1980). Macroeconomics and reality, Econometrica, 48, 1-48.
Sovbetov, Y. and Saka, H. (2018). The interaction between credit default swaps and national stock indices: Empirical evidence from Turkey, Journal of Economics and Financial Analysis, 2 (1), 129-149.
Stock, J. and Watson, M. (1993). A simple estimator of cointegrating vectors in higher order integrated systems, Econometrica, 61 (4), 783-820.
Şahin, E. E. and Özkan, O. (2018). Credit default swap, exchange rates and BİST 100 index relationship: Cointegration and causality analysis, Hitit University Journal of Social Sciences Institute, 11 (3), 1939- 1945.
Toda, H. Y. and Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes, Journal of Econometrics, 66, 225–250.
Tseng, M. L. and Tan, K. H. (2016). Sustainable consumption and production in emerging markets, International Journal of Production Economics, 181, 257-261.