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Volatility Interaction between Dow Jones Sukuk Index and Selected Stock Indices

Year 2022, Volume: 7 Issue: 3, 697 - 712, 30.09.2022
https://doi.org/10.30784/epfad.1116773

Abstract

Sukuk, which is described as the equivalent of traditional bonds in Islamic financial products, is a financial product that draws quite attention in global markets and used by both Muslim and non-Muslim investors. Developments in financialization and financial product diversity have attracted attention to the investigations of volatility spillover and interaction between financial markets. This increase in both Islamic markets and volatility analysis has formed the basis for the study of certain Islamic Indices selected with the Dow Jones Sukuk Index, which is the aim of the study. In this context, the interaction between the return volatility of the Dow Jones Sukuk Index and the Dow Jones India Index, MSCI USA Islamic Index, Jakarta Islamic Index and Doha Al-Rayan Islamic Indices was examined based on the 2013-2021 period data. In this study, in which the Dynamic Conditional Correlation-GARCH model was used, it was concluded that there was volatility clustering and continuity in volatility in all series examined. In addition, in the results of the dynamic conditional correlation model, it was found that there is a positive volatility interaction that changes over time between Dow Jones Sukuk Index and Dow Jones India Index, MSCI USA Islamic Index and Doha Al-Rayan. Accordingly, when there is an increase in volatility in the Dow Jones Sukuk Index, it is expected that there will be an increase in volatility in these examined indices.

References

  • Abdul Rahim, F., Ahmad, N. and Ahmad, I. (2009). Information transmission between Islamic stock indices in South East Asia. International Journal of Islamic and Middle Eastern Finance and Management, 2(1), 7-19. doi:10.1108/17538390910946230
  • Ahmad, W., Sehgal, S. and Bhanumurthy, N.R. (2013). Eurozone crisis and BRICKS stock markets: Contagion or market interdependence? Economic Modelling, 33, 209-225. doi:10.1016/j.econmod.2013.04.009
  • Archer, S. and Karim, R.A.A. (2018). Islamic capital markets and products. Managing capital and liquidity requirements under Basel III. United Kingdom: John Wiley and Sons.
  • Baba, Y., Engle, R.F., Kraft, D. and Kroner, K. (1990). Multivariate simultaneous generalized ARCH. San Diego: Mimeo.
  • Başarır, Ç. (2018). Volatility structure of stock price index and exchange rates: Casuality analysis for Turkey. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 9(24), 330-349. Retrieved from https://dergipark.org.tr/tr/pub/gumus/
  • Bollerslev, T. (1990). Modelling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. The Review of Economics and Statistics, 498-505. https://doi.org/10.2307/2109358
  • Cappiello, L., Engle, R.F. and Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4(4), 537-572. https://doi.org/10.1093/jjfinec/nbl005
  • Çelik, İ., Özdemir, A. ve Gülbahar, S.D. (2018). İslami hisse senedi endeksleri arasında getiri ve volatilite yayılımı: Gelişmiş ve gelişmekte olan piyasalarda çok değişkenli VAR-EGARCH uygulaması. Muhasebe ve Finans İncelemeleri Dergisi, 1(2), 89-100. https://doi.org/10.32951/mufider.418295
  • Ding, L. and Vo, M. (2012). Exchange rates and oil prices: A multivariate stochastic volatility analysis. The Quarterly Review of Economics and Finance 52(1), 15-37. https://doi.org/10.1016/j.qref.2012.01.003
  • Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339-350. https://doi.org/10.1198/073500102288618487
  • Engle, R.F. and Kroner, K.F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11, 122-150. https://doi.org/10.1017/S0266466600009063
  • Güçlü, F. (2019). Katılım 30 endeksinin zamanla değişen betası. Uluslararası İktisadi ve İdari İncelemeler Dergisi (BOR Özel Sayısı), 115-126. https://doi.org/10.18092/ulikidince.515150
  • Hesse, H., Frank, N. and González-Hermosillo, B. (2008). Transmission of liquidity shocks: Evidence from the 2007 subprime crisis (IMF Working Paper No. 08/200). Retrieved from https://ssrn.com/abstract=1266533
  • ICD. (2019). Islamic finance development report 2019. Retrieved from https://icd-ps.org/uploads/files/IFDI%202019%20DEF%20digital1574605094_7214.pdf
  • Kamışlı, S. ve Esen, E. (2020). İslami hisse senedi endeksleri arasındaki oynaklık ilişki yapısı. Journal of Management and Economics Research, 18(1), 108-121. http://doi:10.11611/Yead.607940
  • Kebalo, L. (2016). What DCC-GARCH model tell us about the effect of the gold price’s volatility on South African exchange rate? Journal of Economics Library, 3(4), 570-582. Retrieved from https://mpra.ub.uni-muenchen.de/
  • Majdoub, J. and Ben Sassi, S. (2017). Volatility spillover and hedging effectiveness among China and emerging Asian Islamic equity indexes. Emerging Markets Review, 31, 16-31. https://doi.org/10.1016/j.ememar.2016.12.003
  • Majdoub, J. and Mansour, W. (2014). Islamic equity market integration and volatility spillover between emerging and US stock markets. The North American Journal of Economics and Finance, 29, 452-470. https://doi.org/10.1016/j.najef.2014.06.011
  • Najeeb, S.F., Bacha, O. and Masih, M. (2015). Does heterogeneity in investment horizons affect portfolio diversification? Some insights using M-GARCH-DCC and wavelet correlation analysis. Emerging Markets Finance and Trade, 51(1), 188-208. https://doi.org/10.1080/1540496X.2015.1011531
  • Nasr, A.B., Lux, T., Ajmi, A.N. and Gupta, R. (2016). Forecasting the volatility of the Dow Jones Islamic stock market index: Long memory vs. regime switching. International Review of Economics & Finance, 45, 559-571. doi:10.1016/j.iref.2016.07.014
  • Orskaug, E. (2009). Multivariate DCC-GARCH model: With various error distributions (Unpublished doctoral dissertation). Norwegian University of Science and Technology, Institute of Mathematics Master of Science in Physics and Mathematics.
  • Rejeb, A.B. and Arfoui, M. (2019). Do Islamic stock indexes outperform conventional stock indexes? A state space modeling approach. European Journal of Management and Business Economics, 28(3), 301-322. doi:10.1108/EJMBE-08-2018-0088
  • Roy, R.P. and Roy, S.S. (2017). Financial contagion and volatility spillover: An exploration into Indian commodity derivative market. Economic Modelling, 67, 368-380. doi:10.1016/j.econmod.2017.02.019
  • Saadaoui, A. and Boujelbene, Y. (2015). Volatility transmission between Dow Jones Stock Index and emerging Islamic stock index: Case of subprime financial crises. EMAJ: Emerging Markets Journal, 5(1), 41-49.http://doi.org/10.5195/emaj.2015.68
  • Shahzad, S.J.H., Ferrer, R., Ballester, L. and Umar, Z. (2017). Risk transmission between Islamic and conventional stock markets: A return and volatility spillover analysis. International Review of Financial Analysis, 52, 9-26. https://doi.org/10.1016/j.irfa.2017.04.005
  • Singhal, S. and Ghosh, S. (2016). Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models. Resources Policy, 50, 276-288. doi:10.1016/j.resourpol.2016.10.001
  • Tanjung, H. (2014). Volatility of Jakarta Islamic index. Al-Iqtishad: Jurnal Ilmu Ekonomi Syariah, 6(2), 207-222. http://doi:10.15408/aiq.v6i2.1231
  • TKBB. (2015). Faizsiz finans standartları. Erişim adresi: https://tkbb.org.tr/Documents/Yonetmelikler/FAIZSIZ-FINANS-STANDARTLARI.pdf
  • Vishwanath, S.R. and Azmi, S. (2009). An overview of Islamic sukuk bonds. The Journal of Structured Finance, 14(4), 58-67. https://doi.org/10.3905/JSF.2009.14.4.058
  • Wang, K.M. and Thi, T.B.N. (2006). Does contagion effect exist between stock markets of Thailand and Chinese economic area (CEA) during the Asian flu? Asian Journal of Management and Humanity Sciences, 1(1), 16-36. Retrieved from https://citeseerx.ist.psu.edu/
  • Wang, P. and Moore, T. (2012). The integration of the credit default swap markets during the US subprime crisis: Dynamic correlation analysis. Journal of International Financial Markets, Institutions and Money, 22(1), 1-15. doi:10.1016/j.intfin.2011.07.001
  • Yakar, S., Kandır, S.Y. ve Önal, Y.B. (2013). Yeni bir finansman aracı olarak “Sukuk-Kira Sertifikası” ve vergisel boyutunun incelenmesi. Bankacılar Dergisi, 84, 72-94. Erişim adresi: https://www.tbb.org.tr/tr

Dow Jones Sukuk Endeksiyle Seçilmiş İslami Hisse Senedi Endeksleri Arasındaki Volatilite Etkileşimi

Year 2022, Volume: 7 Issue: 3, 697 - 712, 30.09.2022
https://doi.org/10.30784/epfad.1116773

Abstract

Geleneksel tahvillerin İslami finansal ürünlerdeki karşılığı olarak ifade edilen sukuk, küresel piyasalarda oldukça dikkat çeken hem Müslümanlar hem de Müslüman olmayan yatırımcılar tarafından kullanılan bir finansal üründür. Finansallaşmada ve finansal ürün çeşitliliğinde yaşanan gelişmeler finansal piyasalar arasındaki volatilite yayılımı ve etkileşimi incelemelerinin dikkat çekmesine neden olmuştur. Hem İslami piyasalar hem de volatilite incelemelerindeki bu artış, çalışmanın amacı olan Dow Jones Sukuk Endeksi ile seçilmiş bazı İslami Endekslerin incelenmesinde temel oluşturmuştur. Bu bağlamda Dow Jones Sukuk Endeski ile Dow Jones Hindistan Endeksi, MSCI USA İslami Endeksi, Jakarta İslami Endeksi ve Doha Al-Rayan İslami Endekslerinin getiri volatiliteleri arasındaki etkileşim 2013-2021 dönemi verileri baz alınarak incelenmiştir. Dinamik Koşullu Korelasyon-GARCH modelinin kullanıldığı bu çalışmada, incelenen tüm serilerde volatilite kümelenmesi ve volatilitede süreklilik olduğu sonucuna ulaşılmıştır. Dinamik koşullu korelasyon modeli sonuçlarında da Dow Jones Sukuk Endeksi ile Dow Jones Hindistan Endeksi, MSCI USA İslami Endeksi ve Doha Al-Rayan arasında zamanla değişen pozitif yönlü volatilite etkileşimi olduğu bulgusu elde edilmiştir. Buna göre Dow Jones Sukuk Endeksi’nde volatilite artışı olduğunda incelenen bu endekslerde volatilite artışı olması beklenmektedir.

References

  • Abdul Rahim, F., Ahmad, N. and Ahmad, I. (2009). Information transmission between Islamic stock indices in South East Asia. International Journal of Islamic and Middle Eastern Finance and Management, 2(1), 7-19. doi:10.1108/17538390910946230
  • Ahmad, W., Sehgal, S. and Bhanumurthy, N.R. (2013). Eurozone crisis and BRICKS stock markets: Contagion or market interdependence? Economic Modelling, 33, 209-225. doi:10.1016/j.econmod.2013.04.009
  • Archer, S. and Karim, R.A.A. (2018). Islamic capital markets and products. Managing capital and liquidity requirements under Basel III. United Kingdom: John Wiley and Sons.
  • Baba, Y., Engle, R.F., Kraft, D. and Kroner, K. (1990). Multivariate simultaneous generalized ARCH. San Diego: Mimeo.
  • Başarır, Ç. (2018). Volatility structure of stock price index and exchange rates: Casuality analysis for Turkey. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 9(24), 330-349. Retrieved from https://dergipark.org.tr/tr/pub/gumus/
  • Bollerslev, T. (1990). Modelling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. The Review of Economics and Statistics, 498-505. https://doi.org/10.2307/2109358
  • Cappiello, L., Engle, R.F. and Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4(4), 537-572. https://doi.org/10.1093/jjfinec/nbl005
  • Çelik, İ., Özdemir, A. ve Gülbahar, S.D. (2018). İslami hisse senedi endeksleri arasında getiri ve volatilite yayılımı: Gelişmiş ve gelişmekte olan piyasalarda çok değişkenli VAR-EGARCH uygulaması. Muhasebe ve Finans İncelemeleri Dergisi, 1(2), 89-100. https://doi.org/10.32951/mufider.418295
  • Ding, L. and Vo, M. (2012). Exchange rates and oil prices: A multivariate stochastic volatility analysis. The Quarterly Review of Economics and Finance 52(1), 15-37. https://doi.org/10.1016/j.qref.2012.01.003
  • Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics, 20(3), 339-350. https://doi.org/10.1198/073500102288618487
  • Engle, R.F. and Kroner, K.F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11, 122-150. https://doi.org/10.1017/S0266466600009063
  • Güçlü, F. (2019). Katılım 30 endeksinin zamanla değişen betası. Uluslararası İktisadi ve İdari İncelemeler Dergisi (BOR Özel Sayısı), 115-126. https://doi.org/10.18092/ulikidince.515150
  • Hesse, H., Frank, N. and González-Hermosillo, B. (2008). Transmission of liquidity shocks: Evidence from the 2007 subprime crisis (IMF Working Paper No. 08/200). Retrieved from https://ssrn.com/abstract=1266533
  • ICD. (2019). Islamic finance development report 2019. Retrieved from https://icd-ps.org/uploads/files/IFDI%202019%20DEF%20digital1574605094_7214.pdf
  • Kamışlı, S. ve Esen, E. (2020). İslami hisse senedi endeksleri arasındaki oynaklık ilişki yapısı. Journal of Management and Economics Research, 18(1), 108-121. http://doi:10.11611/Yead.607940
  • Kebalo, L. (2016). What DCC-GARCH model tell us about the effect of the gold price’s volatility on South African exchange rate? Journal of Economics Library, 3(4), 570-582. Retrieved from https://mpra.ub.uni-muenchen.de/
  • Majdoub, J. and Ben Sassi, S. (2017). Volatility spillover and hedging effectiveness among China and emerging Asian Islamic equity indexes. Emerging Markets Review, 31, 16-31. https://doi.org/10.1016/j.ememar.2016.12.003
  • Majdoub, J. and Mansour, W. (2014). Islamic equity market integration and volatility spillover between emerging and US stock markets. The North American Journal of Economics and Finance, 29, 452-470. https://doi.org/10.1016/j.najef.2014.06.011
  • Najeeb, S.F., Bacha, O. and Masih, M. (2015). Does heterogeneity in investment horizons affect portfolio diversification? Some insights using M-GARCH-DCC and wavelet correlation analysis. Emerging Markets Finance and Trade, 51(1), 188-208. https://doi.org/10.1080/1540496X.2015.1011531
  • Nasr, A.B., Lux, T., Ajmi, A.N. and Gupta, R. (2016). Forecasting the volatility of the Dow Jones Islamic stock market index: Long memory vs. regime switching. International Review of Economics & Finance, 45, 559-571. doi:10.1016/j.iref.2016.07.014
  • Orskaug, E. (2009). Multivariate DCC-GARCH model: With various error distributions (Unpublished doctoral dissertation). Norwegian University of Science and Technology, Institute of Mathematics Master of Science in Physics and Mathematics.
  • Rejeb, A.B. and Arfoui, M. (2019). Do Islamic stock indexes outperform conventional stock indexes? A state space modeling approach. European Journal of Management and Business Economics, 28(3), 301-322. doi:10.1108/EJMBE-08-2018-0088
  • Roy, R.P. and Roy, S.S. (2017). Financial contagion and volatility spillover: An exploration into Indian commodity derivative market. Economic Modelling, 67, 368-380. doi:10.1016/j.econmod.2017.02.019
  • Saadaoui, A. and Boujelbene, Y. (2015). Volatility transmission between Dow Jones Stock Index and emerging Islamic stock index: Case of subprime financial crises. EMAJ: Emerging Markets Journal, 5(1), 41-49.http://doi.org/10.5195/emaj.2015.68
  • Shahzad, S.J.H., Ferrer, R., Ballester, L. and Umar, Z. (2017). Risk transmission between Islamic and conventional stock markets: A return and volatility spillover analysis. International Review of Financial Analysis, 52, 9-26. https://doi.org/10.1016/j.irfa.2017.04.005
  • Singhal, S. and Ghosh, S. (2016). Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models. Resources Policy, 50, 276-288. doi:10.1016/j.resourpol.2016.10.001
  • Tanjung, H. (2014). Volatility of Jakarta Islamic index. Al-Iqtishad: Jurnal Ilmu Ekonomi Syariah, 6(2), 207-222. http://doi:10.15408/aiq.v6i2.1231
  • TKBB. (2015). Faizsiz finans standartları. Erişim adresi: https://tkbb.org.tr/Documents/Yonetmelikler/FAIZSIZ-FINANS-STANDARTLARI.pdf
  • Vishwanath, S.R. and Azmi, S. (2009). An overview of Islamic sukuk bonds. The Journal of Structured Finance, 14(4), 58-67. https://doi.org/10.3905/JSF.2009.14.4.058
  • Wang, K.M. and Thi, T.B.N. (2006). Does contagion effect exist between stock markets of Thailand and Chinese economic area (CEA) during the Asian flu? Asian Journal of Management and Humanity Sciences, 1(1), 16-36. Retrieved from https://citeseerx.ist.psu.edu/
  • Wang, P. and Moore, T. (2012). The integration of the credit default swap markets during the US subprime crisis: Dynamic correlation analysis. Journal of International Financial Markets, Institutions and Money, 22(1), 1-15. doi:10.1016/j.intfin.2011.07.001
  • Yakar, S., Kandır, S.Y. ve Önal, Y.B. (2013). Yeni bir finansman aracı olarak “Sukuk-Kira Sertifikası” ve vergisel boyutunun incelenmesi. Bankacılar Dergisi, 84, 72-94. Erişim adresi: https://www.tbb.org.tr/tr
There are 32 citations in total.

Details

Primary Language Turkish
Subjects Finance
Journal Section Makaleler
Authors

Müge Sağlam Bezgin 0000-0001-8674-2707

Emine Karaçayır 0000-0003-0512-9084

Publication Date September 30, 2022
Acceptance Date September 29, 2022
Published in Issue Year 2022 Volume: 7 Issue: 3

Cite

APA Sağlam Bezgin, M., & Karaçayır, E. (2022). Dow Jones Sukuk Endeksiyle Seçilmiş İslami Hisse Senedi Endeksleri Arasındaki Volatilite Etkileşimi. Ekonomi Politika Ve Finans Araştırmaları Dergisi, 7(3), 697-712. https://doi.org/10.30784/epfad.1116773

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