Cilt 8 Sayı 1 (2020): Business & Management Studies: An International Journal
Makaleler

RİSK GÖSTERGELERİNİN SENDİKASYON KREDİLERİNE ETKİLERİ: ASİMETRİ VE FREKANS BOYUTUNDA ANALİZ

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  • Melik KAMIŞLI
Melik KAMIŞLI
Dr. Öğr. Üyesi, Bilecik Şeyh Edebali Üniversitesi

Yayınlanmış 25.03.2020

Anahtar Kelimeler

  • Syndicated Loans, Risk Indicators, Asymmetric Causality, Asymmetric Frequency Domain Causality
  • Sendikasyon Kredisi, Risk Göstergeleri, Asimetrik Nedensellik, Asimetrik Frekansta Nedensellik

Nasıl Atıf Yapılır

RİSK GÖSTERGELERİNİN SENDİKASYON KREDİLERİNE ETKİLERİ: ASİMETRİ VE FREKANS BOYUTUNDA ANALİZ. (2020). Business & Management Studies: An International Journal, 8(1), 181-195. https://doi.org/10.15295/bmij.v8i1.1364

Nasıl Atıf Yapılır

RİSK GÖSTERGELERİNİN SENDİKASYON KREDİLERİNE ETKİLERİ: ASİMETRİ VE FREKANS BOYUTUNDA ANALİZ. (2020). Business & Management Studies: An International Journal, 8(1), 181-195. https://doi.org/10.15295/bmij.v8i1.1364

Öz

Çalışmada Türk bankacılık sektörü tarafından alınan sendikasyon kredileri ile küresel ve yerel risk göstergeleri arasındaki ilişkilerinin asimetri ve frekans boyutunda belirlenmesi amaçlanmıştır. Bu amaç doğrultusunda 2008 Kasım -2019 Temmuz tarihleri arasında Türk bankacılık sektörü tarafından alınan toplam sendikasyon kredileri ile global ekonomik belirsizlik endeksi, VIX endeksi, Libor, Türkiye 5 yıllık CDS primi, Türkiye jeopolitik risk endeksi ve BIST Bankacılık sektörü endeks oynaklığı arasındaki ilişkiler geleneksel, asimetrik ve asimetrik frekans nedensellik testleri ile analiz edilmiştir. Uygulanan testler sonucunda sendikasyon kredileri ile ele alınan tüm risk göstergeleri arasında nedensellik ilişkisi tespit edilmiştir. Sonuçlar, tespit edilen ilişkilerin hem farklı frekanslarda hem de farklı asimetrik boyutlarda olduğunu göstermektedir.

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Referanslar

  1. Acharya, V. V., Eisert, T., Eufinger, C., & Hirsch, C. (2018). Real effects of the sovereign debt crisis in Europe: Evidence from syndicated loans. The Review of Financial Studies, 31(8), 2855-2896. https://doi.org/10.1093/rfs/hhy045
  2. Amiram, D., Beaver, W. H., Landsman, W. R., & Zhao, J. (2017). The effects of credit default swap trading on information asymmetry in syndicated loans. Journal of Financial Economics, 126(2), 364-382. https://doi.org/10.1016/j.jfineco.2016.10.001
  3. Breitung, J., & Candelon, B. (2006). Testing for short and long-run causality: A frequency-domain approach. Journal of Econometrics, 132(2), 363-378. https://doi.org/10.1016/j.jeconom.2005.02.004
  4. Champagne, C., & Kryzanowski, L. (2007). Are current syndicated loan alliances related to past alliances?. Journal of Banking & Finance, 31(10), 3145-3161. https://doi.org/10.1016/j.jbankfin.2006.11.018
  5. Ciner, C. (2011). Information transmission across currency futures markets: Evidence from frequency domain tests. International Review of Financial Analysis, 20, 134-139. https://doi.org/10.1016/j.irfa.2011.02.010
  6. Doornik J. A., & Hansen, H. (2008). An Omnibus Test for Univariate and Multivariate Normality. Oxford Bulletin of Economics and Statistics, 70(1), 927-939 https://doi.org/10.1111/j.1468-0084.2008.00537.x
  7. Drago, D., & Gallo, R. (2017). The impact of sovereign rating changes on European syndicated loan spreads: The role of the rating-based regulation. Journal of International Money and Finance, 73, 213-231. https://doi.org/10.1016/j.jimonfin.2017.02.029
  8. Fang, X., Li, Y., Xin, B. & Zhang, W. (2016). Financial statement comparability and debt contracting: Evidence from the syndicated loan market. Accounting Horizons, 30(2), 277-303. https://doi.org/10.2308/acch-51437
  9. Gadanecz, B. (2004). The syndicated loan market: structure, development and implications. BIS Quarterly Review, December, 75-89. https://ssrn.com/abstract=1967463
  10. Geweke, J. (1982). Measurement of linear dependence and feedback between multiple time series. Journal of the American Statistical Association, 77, 304-324. https://doi.org/10.1080/01621459.1982.10477803
  11. Giannetti, M., & Laeven, L. (2012). The flight home effect: Evidence from the syndicated loan market during financial crises. Journal of Financial Economics, 104(1), 23-43. https://doi.org/10.1016/j.jfineco.2011.12.006
  12. Godlewski, C. J., & Weill, L. (2008). Syndicated loans in emerging markets. Emerging Markets Review, 9(3), 206-219. https://doi.org/10.1016/j.ememar.2008.04.001
  13. Gong, D., Jiang, T., & Wu, W. (2018). A foreign currency effect in the syndicated loan market of emerging economies. Journal of International Financial Markets, Institutions and Money, 52, 211-226. https://doi.org/10.1016/j.intfin.2017.09.022
  14. Granger, C. W. J., & Yoon, G. (2002). Hidden cointegration. University of California, Economics Working Paper No. 2002-02. http://dx.doi.org/10.2139/ssrn.313831
  15. Hacker, R. S., & Hatemi-J, A. (2005). A test for multivariate ARCH effects. Applied Economics Letters, 12(7), 411-417. https://doi.org/10.1080/13504850500092129
  16. Harm, C. (2001). European financial market integration: the case of private sector bonds and syndicate loans. Journal of International Financial Markets, Institutions and Money, 11(3-4), 245-263. https://doi.org/10.1016/S1042-4431(01)00039-7
  17. Hatemi-J, A. (2012). Asymmetric Causality Tests with an Application. Empirical Economics, 43(1), 447-456. https://doi.org/10.1007/s00181-011-0484-x
  18. Hosoya, Y. (1991). The decomposition and measurement of the interdependence between secondorder stationary processes. Probability Theory and Related Fields, 88(4), 429-444. https://doi.org/10.1007/BF01192551.
  19. Ng, S., & Perron, P. (2001). LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power. Econometrica, 69(6), 1519-1554. https://doi.org/10.1111/1468-0262.00256
  20. Pişkin, F. (2016). Türk Bankacılık Sektörü Tarafından Alınan Sendikasyon Kredilerinde Spreadi Belirleyen Faktörler. İstanbul Üniversitesi İktisat Fakültesi Mecmuası, 66(2), 113-158. https://dergipark.org.tr/tr/download/article-file/329997
  21. Ranjbar, O., Chang, T., Nel, E., & Gupta, R. (2017). Energy consumption and economic growth nexus in South Africa: Asymmetric frequency domain approach. Energy Sources, Part B: Economics, Planning, and Policy, 12(1), 24-31. https://doi.org/10.1080/15567249.2015.1020120
  22. Thomas, H., & Wang, Z. (2004). The integration of bank syndicated loan and junk bond markets. Journal of Banking & Finance, 28(2), 299-329. https://doi.org/10.1016/j.jbankfin.2003.01.001

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