DCC-GARCH Modeli Yardımıyla İslami Bankalar Arasındaki Etkileşimin Belirlenmesi

Year 2023, Volume: 22 Issue: 3, 932 - 948, 28.07.2023

Faruk Taşkıran , Semra Taspunar Altuntaş

https://doi.org/10.21547/jss.1247563

Abstract

Son yıllarda İslam ekonomilerindeki büyüme ve finansal sistemin gelişimiyle birlikte İslami bankaların finansal piyasalar üzerindeki etkileri artmıştır. İslami bankalar arasındaki finansal etkileşimlerin etkisini araştırmak, finansal istikrar açısından önemlidir. Çalışma İslami bankalar arası finansal etkileşimi Türkiye örneklemi üzerinden açıklamayı amaçlamaktadır. Çalışmada 2021 yılı aktif büyüklüklerine göre sıralanmış küresel İslami bankalar ve bir Türk İslami banka seçilerek oluşturulan örneklem üzerinden gerçekleştirilmektedir. Küresel dört büyük İslami banka seçiminde farklı ülkelerden olması dikkate alınarak ülkeler arası finansal etkileşim dikkate alınmaktadır. Bu çalışmada, finansal bulaşma etkisini ampirik olarak araştırmak için seçilen bankaların borsa fiyatı verileri değişken olarak kullanılmıştır. Beş farklı ülkenin İslami bankalar örneklem seçiminde borsada işlem görme kriteri günlük fiyatlara ulaşma açısından tercih edilmiştir. İslami finans sisteminin gelişmesi ve İslami bankaların büyümesine paralel olarak önemli olayların meydana geldiği bir dönemi kapsayan 02.08.2016 – 08.08.2022 tarihleri etkileşimin incelenmesi ve verilerin ulaşılabilirliği açısından seçilmiştir. Çalışmada dinamik koşullu korelasyonu tahmin etmek için bir DCC-GARCH modeli kullanılmıştır. Model kapsamında seçilen tarih aralığı günlük veri seti bakımından anlamlı sonuçlara ulaşmak için yeterli sayıda bulunmaktadır. Ampirik sonuçlar, İslami bankaların getirileri arasındaki finansal etkileşimin gerçekleştiğini göstermektedir. Ek olarak finansal aktarımın seçilen örneklemde yer alan tüm bankalar arasında gerçekleşmemektedir. Bulgular, Türkiye’deki İslami piyasayı temsilen seçilen İslami bankanın, diğer küresel bankalarla finansal bulaşma etkisinin varlığına işaret etmektedir. Türkiye, Kuveyt ve Suudi Arabistan bankaları arasında bir finansal etkileşim olduğu yönünde bulgular bulunmaktadır. En güçlü finansal etkileşimin model sonuçlarına göre Katar ve Birleşik Arap Emirlikleri’ne ait İslami bankalar arasında olduğu görülmektedir. Finansal etkileşiminin İslami bankalar arasında güçlü ve güçsüz şekilde süreklilik gösterebileceğini göstermektedir.

Keywords

finansal etkileşim, islami bankalar, DCC-GARCH Model

Determining the Interaction Between DCC-GARCH Model and Islamic Banks

Abstract

In recent years, Islamic banks have gained increased influence in financial markets due to the growth of Islamic economies and the development of the financial system. This study focuses on investigating the financial interactions among Islamic banks, specifically within the Turkish Islamic banking sector. A sample is constructed, consisting of globally ranked Islamic banks based on their 2021 asset sizes, along with a selected Turkish Islamic bank. To examine the contagion effect, stock price data of the selected banks are used as variables. The sample includes Islamic banks from different countries to consider cross-country financial interactions. The analysis covers the period from August 2, 2016, to August 8, 2022, considering significant events related to the Islamic finance system's development and the growth of Islamic banks, as well as data availability. A DCC-GARCH model is employed to estimate dynamic conditional correlation. The empirical findings indicate the existence of financial interactions between the returns of Islamic banks. However, not all banks in the sample experience financial contagion. The study suggests the presence of a contagion effect between the selected Turkish Islamic bank and other global banks, indicating the influence of the Turkish market. Furthermore, financial interactions are observed between Turkish, Kuwaiti, and Saudi Arabian banks. The strongest financial interaction is found between Islamic banks from Qatar and the United Arab Emirates, demonstrating that financial interactions among Islamic banks can exhibit both strong and weak continuity.

Keywords

Financial interaction, Islamic Banks, DCC-GARCH Model

References

• Akkizidis, I. J. ve Khandelwal, K. (2019). Interbank lending and macroeconomic factors: Evidence from selected Eurozone countries. Journal of Financial Economic Policy, 11(4), 498-515.
• Albaraka Türk Katılım Bankası A.Ş. (2022). Albaraka 2021 faaliyet raporu. Albaraka Türk Katılım Bankası A.Ş. Erişim adresi: https://www.albaraka.com.tr/documents/yatirimci-iliskileri/faaliyet-raporlari/2021-faaliyet-raporu.pdf
• Al-Tamimi, H. A. H. ve Molyneux, P. (2015). The impact of the global financial crisis on Islamic bank lending and risk: The UAE experience. International Review of Financial Analysis, 38, 29-41.
• Altunbas, Y., Gambacorta, L., ve Marqués-Ibáñez, D. (2010). Bank risk and monetary policy. Journal of Financial Stability, 6(3), 121-129.
• Ariff, M. ve Rosly, S. A. (2014). The efficiency of Islamic banks: Empirical evidence from the MENA and Asian countries Islamic banking sectors. Global Finance Journal, 25(2), 153-166.
• Ariff, M. ve Rosly, S. A. (2014). Interbank lending and efficiency of Islamic banks. Journal of Economic Cooperation and Development, 35(3), 69-90.
• Bashir, A. H. M. (2003). Determinants of profitability in Islamic banks: Some evidence from the Middle East. Islamic Economic Studies, 11(1), 31-57.
• Bauwens, L., Laurent, S., ve Rombouts, J.V.K. (2006). Multivariate GARCH models: A survey. Journal of Applied Econometrics, 21(1), 79-109.
• Beirne, J., Fratzscher, M. ve Mehl, A. (2014). The interbank market puzzle. Journal of International Economics, 92(2), 244-260.
• Bekaert, G. ve Harvey, C. (1997). Emerging equity market volatility. Journal Of Financial Economics, 43(1), 29-77.
• Bollerslev, T., Engle, R. F. ve Wooldridge, J. M. (1988). A capital asset pricing model with time-varying covariances. The Journal of Political Economy, 96(1), 116-131.
• Bollerslev, T. (1990). Modelling the coherence in the short-run nominal exchange rates: A multivariate generalized ARCH model. The Review of Economics and Statistics, 72(3), 498-505.
• Bourkhis, K. ve Nabi, M. S. (2013). Islamic and conventional banks' soundness during the 2007–2008 financial crisis. Review of Financial Economics, 22(2), 68-77.
• Caby, J. ve Boumedienne, A. (2013). The financial volatility of islamic banks during the subprime crisis. Markets and Investors, 126, 30-39.
• Carbo-Valverde, S., Fernandez, F. R. ve Rodriguez-Fernandez, F. (2016). Interbank market integration, loan rates, and firms' leverage. Journal of Banking and Finance, 72, 119-132.
• Cihak, M. ve Hesse, H. (2008). Islamic banks and financial stability: An empirical analysis. Washington: IMF Working Paper.
• Dermine, J. (2018). Financial intermediation and monetary policy: A general equilibrium exposition. Princeton University Press.
• Eichengreen, B., Rose, A. ve Wyplosz, C. (1996). Contagious currency crises: First tests. The Scandinavian Journal of Economics. 94(4), 463-484.
• Elgammal, M. A. ve Al-Rashidy, R. A. (2020). The impact of global financial contagion on the Islamic financial markets: Evidence from the GCC countries. Journal of Economic Studies, 47(2), 363-379.
• Elgammal, M. A. ve Al-Rashidy, R. A. (2020). Interbank contagion and its impact on GDP: Evidence from the Gulf Cooperation Council countries. Journal of Economic Cooperation and Development, 41(2), 1-28.
• Engle, R. ve Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11(1), 122-150.
• Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350.
• Fakhfekh, M. ve Hachicha, N. (2014). Return volatilities and contagion transmission between ıslamic and conventional banks throughout the subprime crisis: Evidence from the DCC-MGARCH model. International Journal of Managerial and Financial Accounting, 6(2), 133-145.
• Global Islamic Finance Report. (2021). Islamic finance in a post-covid world. Cambridge Institute of Islamic Finance.
• Gulzar, M. A. ve Asif, M. (2019). Performance evaluation of Islamic banks: A comparative study of selected Islamic and conventional banks in Pakistan. International Journal of Finance and Economics, 4(3), 127-136.
• Hamao, Y., Masulis, R. W. ve Ng, V. (1990). Correlations in price changes and volatility across international stock markets. The Review of Financial Studies, 3(2), 281-307.
• Haron, S. ve Azmi, W. N. W. (2008). Islamic banking institutions and the capital structure puzzle. Journal of Economic Cooperation and Development, 29(1), 41-58.
• Hasan, M. ve Dridi, J. (2010). The effects of the global crisis on islamic and conventional banks: A comparative study. Imf Working Paper, WP/10/201.
• Hashem, S.Q. ve Giudici, P. (2016). Systemic risk of conventional and islamic banks: Comparison with Graphical Network Models. Applied Mathematics, 7, 2079-2096.
• Hepsağ A. ve Akçalı, B.Y. (2016). Analysis of volatility spillovers between the bank stocks traded in Istanbul stock exchange and New York stock exchange. Statistics & Emprical Economics Journal, 1, 54-72.
• Ibrahim, M. H., Rizvi, S. A. R. ve Abbas, Q. (2016). Determinants of Islamic banking growth in Pakistan: An empirical investigation. International Journal of Islamic and Middle Eastern Finance and Management, 9(3), 347-366.
• Islamic Development Bank. (2021). 2020 Annual Report. Islamic Research and Training Institute.
• Kassab, S. (2013). Modeling volatility stock market using the ARCH and GARCH models: Comparative study index. European Journal of Banking and Finance, 10, 72-77.
• Kenourgios, D., Samitas, A. ve Paltalidis, N. (2007). Financial crises and contagion: Evidence for BRICS stock markets. The European Financial Management Association Annual Conference. Vienna: SSRN.
• King, M. A. ve Wadhwani, S. (1990). Transmission of volatility between stock markets. The Review of Financial Studies, 3(1), 5-33.
• Koetter, M., Noth, F. ve Rehbein, O. (2016). Banks' concentration versus diversification in the loan portfolio: New evidence from Germany. Journal of Financial Stability, 23, 47-58.
• Latifa, M. B. ve Khoufi, W. (2018). Contagion between islamic and conventional banks in Malaysia: Empirical investigation using a DCC-GARCH model. Journal of King Abdulaziz University: Islamic Economics, 31(1), 1-12.
• Lee, S. B. ve Kim, K. J. (1993). Does the October 1987 crash strengthen the co-movements among natıonal stock markets? Review of Financial Economics, 3(1), 89-102.
• Nazlioglu, S., Erdem, C. ve Soytas, U. (2013). Volatility spillover between oil and agricultural commodity markets. Energy Economics, 36, 658-665.
• Ng, A. (2000). Volatility spillover effects from japan and the us to the pacific–basin. Journal of International Money and Finance, 19(2), 207-233.
• Saiti, B., Bacha, O. I. ve Masih, M. (2014). Testing the integrated Islamic stock market hypothesis with nonlinear causality tests. Borsa Istanbul Review, 14(4), 196-213.
• Tai, C. (2004). Can bank be a source of contagion during the 1997 Asian crisis? Journal of Banking and Finance, 28(2), 399-421.
• Tse, Y. K. ve Tsui, A. K. C. (2002). A multivariate generalized autoregressive conditional heteroscedasticity model with time-varying correlations. Journal of Business and Economic Statistics, 20(3), 351-362.
• Waqas, M., Nawaz, T. ve Asif, M. (2019). Performance comparison of Islamic and conventional banks in Pakistan. Journal of Finance and Accounting Research, 1(2), 23-37.
• Zhang, J., Zhang, Y. ve Zhang, Y. (2019). The impact of interbank network structure on systemic risk. International Review of Economics and Finance, 59, 465-479.