Global risk transmission in GCC markets
DOI:
https://doi.org/10.55429/ijabf.v4i2.268Keywords:
Global markets, GCC markets, Tail-risk, Time-varying connectedness, DCC-GARCH, TVP-VAR, Volatility Transmission, Emerging marketsAbstract
This study analyses the transmission of global risk across global markets (MSCI US, Brent crude oil, and MSCI Gold) and the Gulf Cooperation Council (GCC) region from January 2009 to November 2024. The study uses a dual econometric framework: first, calculating extreme downside risk with a DCC-GARCH model, and then capturing the direction and magnitude of risk spillovers with a TVP-VAR model. The analysis helps determine how the relationships between these indices evolve during periods of global financial crises and uncertainty. Results show that GCC markets are highly vulnerable to external shocks and predominantly net recipients of risk. The US market emerges as the strongest net transmitter of volatility, especially during periods of crisis. Brent crude oil serves as both a transmitter and a receiver of risk, while gold serves as a shock absorber and remains a safe-haven asset. Robustness checks using alternate specifications confirm the reliability of these findings.
References
Abuzayed, B., & Al-Fayoumi, N. (2021). Risk spillover from crude oil prices to GCC stock market returns: New evidence during the COVID-19 outbreak. The North American Journal of Economics and Finance, 58, 101476. https://doi.org/10.1016/j.najef.2021.101476
Al Janabi, M. A. M., Hatemi-J, A., & Irandoust, M. (2010). An empirical investigation of the informational efficiency of the GCC equity markets: Evidence from bootstrap simulation. International Review of Financial Analysis, 19(1), 47–54. https://doi.org/10.1016/j.irfa.2009.11.002
Al-Fayoumi, N., Bouri, E., & Abuzayed, B. (2023). Decomposed oil price shocks and GCC stock market sector returns and volatility. Energy Economics, 126, 106930. https://doi.org/10.1016/j.eneco.2023.106930
Alotaibi, A. R., & Mishra, A. V. (2017). Time varying international financial integration for GCC stock markets. The Quarterly Review of Economics and Finance, 63, 66–78. https://doi.org/10.1016/j.qref.2016.03.001
Alqahtani, A., & Chevallier, J. (2020). Dynamic Spillovers between Gulf Cooperation Council’s Stocks, VIX, Oil and Gold Volatility Indices. Journal of Risk and Financial Management, 13(4), 69. https://doi.org/10.3390/jrfm13040069
Al-Yahyaee, K. H., Mensi, W., Sensoy, A., & Kang, S. H. (2019). Energy, precious metals, and GCC stock markets: Is there any risk spillover? Pacific-Basin Finance Journal, 56, 45–70. https://doi.org/10.1016/j.pacfin.2019.05.006
Anscombe, F. J., & Glynn, W. J. (1983). Distribution of the kurtosis statistic b 2 for normal samples. Biometrika, 70(1), 227–234. https://doi.org/10.1093/biomet/70.1.227
Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions. Journal of Risk and Financial Management, 13(4), 84. https://doi.org/10.3390/jrfm13040084
Arouri, M. E. H., & Fouquau, J. (2009). On the short-term influence of oil price changes on stock markets in GCC countries: linear and nonlinear analyses. ArXiv Preprint ArXiv:0905.3870.
Arouri, M. E. H., Lahiani, A., & Nguyen, D. K. (2011). Return and volatility transmission between world oil prices and stock markets of the GCC countries. Economic Modelling, 28(4), 1815–1825. https://doi.org/10.1016/j.econmod.2011.03.012
Awartani, B., & Maghyereh, A. I. (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
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. https://doi.org/10.1016/0304-4076(86)90063-1
Bollerslev, T. (1990). Modelling the Coherence in Short-Run Nominal Exchange Rates: A Multivariate Generalized Arch Model. The Review of Economics and Statistics, 72(3), 498. https://doi.org/10.2307/2109358
Bouri, E., Jain, A., Biswal, P. C., & Roubaud, D. (2017). Cointegration and nonlinear causality amongst gold, oil, and the Indian stock market: Evidence from implied volatility indices. Resources Policy, 52, 201–206. https://doi.org/10.1016/j.resourpol.2017.03.003
D’Agostino, R. B. (1970). Transformation to normality of the null distribution of g 1. Biometrika, 57(3), 679–681. https://doi.org/10.1093/biomet/57.3.679
Diebold, F. X., & Yilmaz, K. (2009). Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets. The Economic Journal, 119(534), 158–171. https://doi.org/10.1111/j.1468-0297.2008.02208.x
Diebold, F. X., & Yilmaz, K. (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
Diebold, F. X., & Yılmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119–134. https://doi.org/10.1016/j.jeconom.2014.04.012
Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient Tests for an Autoregressive Unit Root. Econometrica, 64(4), 813. https://doi.org/10.2307/2171846
Engle, R. (2002). Dynamic Conditional Correlation. Journal of Business & Economic Statistics, 20(3), 339–350. https://doi.org/10.1198/073500102288618487
Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4), 987. https://doi.org/10.2307/1912773
Engle, R. F., & Kroner, K. F. (1995). Multivariate Simultaneous Generalized Arch. Econometric Theory, 11(1), 122–150. http://www.jstor.org/stable/3532933
Gabauer, D., & Gupta, R. (2018). On the transmission mechanism of country-specific and international economic uncertainty spillovers: Evidence from a TVP-VAR connectedness decomposition approach. Economics Letters, 171, 63–71. https://doi.org/10.1016/j.econlet.2018.07.007
Guesmi, K., & Fattoum, S. (2014). Return and volatility transmission between oil prices and oil-exporting and oil-importing countries. Economic Modelling, 38, 305–310. https://doi.org/10.1016/j.econmod.2014.01.022
Hamao, Y., Masulis, R. W., & Ng, V. (1990). Correlations in Price Changes and Volatility across International Stock Markets. The Review of Financial Studies, 3(2), 281–307. http://www.jstor.org/stable/2962024
Hammoudeh, S., & Choi, K. (2007). Characteristics of permanent and transitory returns in oil-sensitive emerging stock markets: The case of GCC countries. Journal of International Financial Markets, Institutions and Money, 17(3), 231–245. https://doi.org/10.1016/j.intfin.2005.11.002
Hanif, W., El Khoury, R., & Gubareva, M. (2026). How Do GCC Countries Stocks Interact With US and European Debt Markets? International Journal of Finance & Economics, 31(1), 70–98. https://doi.org/10.1002/ijfe.3129
Hansen, P. R., & Lunde, A. (2005). A forecast comparison of volatility models: does anything beat a GARCH(1,1)? Journal of Applied Econometrics, 20(7), 873–889. https://doi.org/10.1002/jae.800
Hussain, M., & Rehman, R. U. (2022). Volatility connectedness of GCC stock markets: how global oil price volatility drives volatility spillover in GCC stock markets? Environmental Science and Pollution Research, 30(6), 14212–14222. https://doi.org/10.1007/s11356-022-23114-5
Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259. https://doi.org/10.1016/0165-1765(80)90024-5
Kapar, B., Billah, S. M., Rana, F., & Balli, F. (2024). An investigation of the frequency dynamics of spillovers and connectedness among GCC sectoral indices. International Review of Economics & Finance, 89, 1442–1467. https://doi.org/10.1016/j.iref.2023.09.004
Koop, G., & Korobilis, D. (2014). A new index of financial conditions. European Economic Review, 71, 101–116. https://doi.org/10.1016/j.euroecorev.2014.07.002
Koop, G., Pesaran, M. H., & Potter, S. M. (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
Mensi, W., Hammoudeh, S., & Tiwari, A. K. (2016). New evidence on hedges and safe havens for Gulf stock markets using the wavelet-based quantile. Emerging Markets Review, 28, 155–183. https://doi.org/10.1016/j.ememar.2016.08.003
Nakajima, J. (2011). Time-Varying Parameter VAR Model with Stochastic Volatility: An Overview of Methodology and Empirical Applications. Monetary and Economic Studies, 29, 107–142. https://EconPapers.repec.org/RePEc:ime:imemes:v:29:y:2011:p:107-142
Pericoli, M., & Yilmaz, K. (2024). Shocks and global asset market connectedness. In G. M. Caporale (Ed.), Handbook of Financial Integration (pp. 108–133). Edward Elgar Publishing.
Pesaran, H. H., & Shin, Y. (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
Primiceri, G. E. (2005). Time Varying Structural Vector Autoregressions and Monetary Policy. The Review of Economic Studies, 72(3), 821–852. https://doi.org/10.1111/j.1467-937X.2005.00353.x
Shahzad, U., Mohammed, K. S., Tiwari, S., Nakonieczny, J., & Nesterowicz, R. (2023). Connectedness between geopolitical risk, financial instability indices and precious metals markets: Novel findings from Russia Ukraine conflict perspective. Resources Policy, 80, 103190. https://doi.org/10.1016/j.resourpol.2022.103190
Younis, I., Naeem, M. A., Shah, W. U., & Tang, X. (2025). Inter- and intra-connectedness between energy, gold, Bitcoin, and Gulf cooperation council stock markets: New evidence from various financial crises. Research in International Business and Finance, 73, 102548. https://doi.org/10.1016/j.ribaf.2024.102548
Yousaf, I., Beljid, M., Chaibi, A., & Ajlouni, A. AL. (2022). Do volatility spillover and hedging among GCC stock markets and global factors vary from normal to turbulent periods? Evidence from the global financial crisis and Covid-19 pandemic crisis. Pacific-Basin Finance Journal, 73, 101764. https://doi.org/10.1016/j.pacfin.2022.101764
Ziadat, S. A., & AlKhouri, R. (2022). Revisiting volatility spillovers in the Gulf Cooperation Council. Cogent Economics & Finance, 10(1). https://doi.org/10.1080/23322039.2022.2031683
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Chinmaya Narayany S., Asgar Ali, Faisal Nazir Zargar

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This is an open-access journal. Your article will be published open-access, but you will not have to pay an APC (article processing charge) - publication is free. Your article will be published with a Creative Commons CC BY-NC 4.0 user licence, which outlines how readers can reuse your work. The licence terms may be found at https://creativecommons.org/licenses/by-nc/4.0/.
Accepted 2026-04-12
Published 2026-06-06
