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Journal of Asset Management

, Volume 20, Issue 1, pp 72–90 | Cite as

Return and volatility spillovers in the presence of structural breaks: evidence from GCC Islamic and conventional banks

  • Noureddine BenlaghaEmail author
  • Slim Mseddi
Original Article
  • 30 Downloads

Abstract

The dynamics of return and volatility spillover indices were investigated to reveal the strength and direction of transmission that occurred during a financial crisis. The focus of this study was especially placed on the 2007 US subprime mortgage crisis, the global financial crisis, the European sovereign debt crisis, and the dramatic collapse of oil prices since 2014. The paper uses the Diebold and Yilmaz (Economic Journal 119(534): 158–171, 2009, International Journal of Forecasting 28(1): 57–66, 2012) spillover index behavior. Assuming one structural break, return and volatility linkages for Islamic banks in the GCC were stronger than for conventional banks. When multiple breaks were allowed, the spillover index was found to be highly sensitive to various economic events. Overall, the findings of this study provide new insights into the behavior of the Islamic and conventional banks stock returns and volatility spillovers, which may improve investment decisions and the trading strategies portfolio of investors.

Keywords

Financial crisis Islamic banks Conventional banks Spillover effects Financial markets Structural breaks 

Notes

References

  1. Abdelsalam, O., P. Dimitropoulos, M. Elnahass, and S. Leventis. 2016. Earnings management behaviors under different monitoring mechanisms: The case of Islamic and conventional banks. Journal of Economic Behavior & Organization 132: 155–173.Google Scholar
  2. Abedifar, P., P. Molyneux, and A. Tarazi. 2013. Risk in Islamic banking. Review of Finance 17 (6): 2035–2096.  https://doi.org/10.1093/rof/rfs041.Google Scholar
  3. Alagidede, P., T. Panagiotidis, and X. Zhang. 2011. Causal relationship between stock prices and exchange rates. Journal of International Trade and Economic Development 20 (1): 67–86.  https://doi.org/10.1080/09638199.2011.538186.Google Scholar
  4. Aloui, R., S. Hammoudeh, and D.K. Nguen. 2013. A time-varying copula approach to oil and stock market dependence: the case of transition economies. Energy Economics 39: 208–221.Google Scholar
  5. Antonakakis, N., and R. Kizys. 2015. Dynamic spillovers between commodity and currency markets. International Review of Financial Analysis 41: 303–319.  https://doi.org/10.1016/j.irfa.2015.01.016.Google Scholar
  6. Awartani, B., and A.I. Maghyereh. 2013. Dynamic spillovers between oil and stock markets in the Gulf Cooperation Council Countries. Energy Economics 36: 28–42.  https://doi.org/10.1016/j.eneco.2012.11.024.Google Scholar
  7. Beck, T., A. Demirgüç-Kunt, and O. Merrouche. 2013. Islamic vs. conventional banking: Business model, efficiency and stability. Journal of Banking & Finance 37 (2): 433–447.  https://doi.org/10.1016/j.jbankfin.2012.09.016.Google Scholar
  8. Bekiros, S.D. 2014. Contagion, decoupling and the spillover effects of the US financial crisis: Evidence from the BRIC markets. International Review of Financial Analysis 33: 58–69.  https://doi.org/10.1016/j.irfa.2013.07.007.Google Scholar
  9. Beltratti, A., and R.M. Stulz. 2012. The credit crisis around the globe: Why did some banks perform better? Journal of Financial Economics 105 (1): 1–17.  https://doi.org/10.1016/j.jfineco.2011.12.005.Google Scholar
  10. Berger, A.N., and C.H.S. Bouwman. 2013. How does capital affect bank performance during financial crises? Journal of Financial Economics 109 (1): 146–176.  https://doi.org/10.1016/j.jfineco.2013.02.008.Google Scholar
  11. Bourkhis, K., and M.S. Nabi. 2013. Islamic and conventional banks’ soundness during the 2007–2008 financial crisis. Review of Financial Economics 22 (2): 68–77.  https://doi.org/10.1016/j.rfe.2013.01.001.Google Scholar
  12. Charfeddine, L., and N. Benlagha. 2016. A time-varying copula approach for modelling dependency: New evidence from commodity and stock markets. Journal of Multinational Financial Management 37–38: 168–189.Google Scholar
  13. Chiang, S.M., H.F. Chen, and C.T. Lin. 2013. The spillover effects of the sub-prime mortgage crisis and optimum asset allocation in the BRICV stock markets. Global Finance Journal 24 (1): 30–43.  https://doi.org/10.1016/j.gfj.2013.03.001.Google Scholar
  14. Diebold, F.X., and K. Yilmaz. 2009. Measuring financial asset return and volatility spillovers, with application to global equity markets. Economic Journal 119 (534): 158–171.  https://doi.org/10.1111/j.1468-0297.2008.02208.x.Google Scholar
  15. Diebold, F.X., and K. Yilmaz. 2012. Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting 28 (1): 57–66.  https://doi.org/10.1016/j.ijforecast.2011.02.006.Google Scholar
  16. Ewing, B.T., and F. Malik. 2016. Volatility spillovers between oil prices and the stock market under structural breaks. Global Finance Journal 29: 12–23.  https://doi.org/10.1016/j.gfj.2015.04.008.Google Scholar
  17. Fahlenbrach, R., R. Prilmeier, and R.M. Stulz. 2012. This time is the same: Using bank performance in 1998 to explain bank performance during the recent financial crisis. Journal of Finance 67 (6): 2139–2185.  https://doi.org/10.1111/j.1540-6261.2012.01783.x.Google Scholar
  18. Fahlenbrach, R., and R.M. Stulz. 2011. Bank CEO incentives and the credit crisis. Journal of Financial Economics 99 (1): 11–26.  https://doi.org/10.1016/j.jfineco.2010.08.010.Google Scholar
  19. Farooq, M., and S. Zaheer. 2015. Are Islamic banks more resilient during financial panics? Pacific Economic Review 20 (1): 101–124.  https://doi.org/10.1111/1468-0106.12096.Google Scholar
  20. Gil-alana, L.A. 2010. Inflation in South Africa: A time-series view across sectors using long-range dependence. South African Journal of Economics 78 (4): 325–343.Google Scholar
  21. Hamilton, J. 1983. Oil and the Macroeconomy since World War II. Journal of Political Economy. 91 (2): 228–248.Google Scholar
  22. Hansen, P.R., and A. Lunde. 2006. Consistent ranking of volatility models. Journal of Econometrics 131: 97–121.  https://doi.org/10.1016/j.jeconom.2005.01.005.Google Scholar
  23. Hasan, M., and Dridi, J. 2010. The effects of the global crisis on Islamic and conventional banks: A comparative study. IMF Working Paper 10/201: International Monetary Fund.Google Scholar
  24. Hasan, M., and J. Dridi. 2011. The effects of the global crisis on Islamic and conventional banks: A comparative study. Journal of International Commerce, Economics and Policy 2 (2): 163–200.  https://doi.org/10.1142/S1793993311000270.Google Scholar
  25. Hassan, M.K., and M.K. Lewis. 2007. Islamic banking: An introduction and overview. Cheltenham: Edward Elgar publishing limited.Google Scholar
  26. Huang, R.D., R.W. Masulis, and H.R. Stoll. 1996. Energy shocks and financial markets. Journal of Futures Markets 16 (1): 1–27.Google Scholar
  27. Irresberger, F., J. Mühlnickel, and G.N.F. Weiß. 2015. Explaining bank stock performance with crisis sentiment. Journal of Banking & Finance 59: 311–329.  https://doi.org/10.1016/j.jbankfin.2015.06.001.Google Scholar
  28. Johnes, J., M. Izzeldin, and V. Pappas. 2014. A comparison of performance of Islamic and conventional banks 2004–2009. Journal of Economic Behavior & Organization 103: S93–S107.  https://doi.org/10.1016/j.jebo.2013.07.016.Google Scholar
  29. Khediri, K.B., L. Charfeddine, and S. Ben Youssef. 2015. Islamic versus conventional banks in the GCC countries: A comparative study using classification techniques. Research in International Business and Finance 33: 75–98.  https://doi.org/10.1016/j.ribaf.2014.07.002.Google Scholar
  30. Koop, G., M.H. Pesaran, and S.M. Potter. 1996. Impulse response analysis in nonlinear multivariate models. Journal of Econometrics 74 (1): 119–147.  https://doi.org/10.1016/0304-4076(95)01753-4.Google Scholar
  31. Longin, F., and B. Solnik. 1995. Is the correlation in international equity returns constant: 1960–1990? Journal of International Money and Finance 14 (1): 3–26.  https://doi.org/10.1016/0261-5606(94)00001-H.Google Scholar
  32. Narayan, P.K., and D. Bannigidadmath. 2015. Are Indian stock returns predictable? Journal of Banking & Finance 58: 506–531.Google Scholar
  33. Narayan, P.K., D.H.B. Phan, S.S. Sharma, and J. Westerlund. 2016. Are Islamic stock returns predictable? A global perspective. Pacific Basin Finance Journal 40: 210–223.  https://doi.org/10.1016/j.pacfin.2016.08.008.Google Scholar
  34. Onour, I.A. 2010. Analysis of portfolio diversifications efficiency in emerging African stock markets. International Research Journal of Finance and Economics 40: 30–37.Google Scholar
  35. Pappas, V., S. Ongena, M. Izzeldin, and A.M. Fuertes. 2016. A survival analysis of Islamic and conventional banks. Journal of Financial Services Research 51 (2): 221–256.  https://doi.org/10.1007/s10693-016-0239-0.Google Scholar
  36. Patton, A.J. 2011. Volatility forecast comparison using imperfect volatility proxies. Journal of Econometrics 160: 246–256.  https://doi.org/10.1016/j.jeconom.2010.03.034.Google Scholar
  37. Pesaran, H.H., and Y. Shin. 1998. Generalized impulse response analysis in linear multivariate models. Economics Letters 58 (1): 17–29.  https://doi.org/10.1016/S0165-1765(97)00214-0.Google Scholar
  38. Phillips, P.C.B., and P. Perron. 1988. Testing for a unit root in time series regression. Biometrika 75 (2): 335–346.  https://doi.org/10.1093/biomet/75.2.335.Google Scholar
  39. Sensoy, A., G. Aras, and E. Hacihasanoglu. 2015. Predictability dynamics of Islamic and conventional equity markets. North American Journal of Economics and Finance 31: 222–248.  https://doi.org/10.1016/j.najef.2014.12.001.Google Scholar
  40. Silvennoinen, A., and S. Thorp. 2013. Financialization, crisis and commodity correlation dynamics. Journal of International Financial Markets, Institutions and Money 24 (1): 42–65.  https://doi.org/10.1016/j.intfin.2012.11.007.Google Scholar
  41. Sorwar, G., V. Pappas, J. Pereira, and M. Nurullah. 2016. To debt or not to debt: Are Islamic banks less risky than conventional banks? Journal of Economic Behavior & Organization 132: 113–126.  https://doi.org/10.1016/j.jebo.2016.10.012.Google Scholar
  42. Zhang, B., and P. Wang. 2014. Return and volatility spillovers between china and world oil markets. Economic Modelling 42: 413–420.  https://doi.org/10.1016/j.econmod.2014.07.013.Google Scholar
  43. Zhou, X., W. Zhang, and J. Zhang. 2012. Volatility spillovers between the Chinese and world equity markets. Pacific Basin Finance Journal 20 (2): 247–270.  https://doi.org/10.1016/j.pacfin.2011.08.002.Google Scholar

Copyright information

© Springer Nature Limited 2019

Authors and Affiliations

  1. 1.Department of Finance and Economics, College of Business and EconomicsQatar UniversityDohaQatar
  2. 2.Department of Finance and Investment, College of Economics and Administrative SciencesAl Imam Mohammad Ibn Saud Islamic University (IMSIU)RiyadhSaudi Arabia

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