ESTIMATION OF STOCK RETURNS VOLATILITY AND SPILLOVERS AMONG DAX, S&P 500, AND XU100 USING GARCH AND CAUSALITY TESTS

Year 2025, Volume: 26 Issue: 3, 161 - 181, 28.09.2025

Havva Nesrin Tiryaki

https://doi.org/10.53443/anadoluibfd.1635574

Abstract

The escalation of financial and economic interdependence among countries leads to the transmission of shocks in financial markets to other countries. Events such as the 2008 global financial crisis and the COVID-19 pandemic have induced considerable volatility in the stock markets of both developed and developing nations. This study estimated the conditional variance series of the DAX, S&P500, and XU100 indexes using the GARCH model based on their respective returns. The GARCH estimation results indicate that volatility clusters were present in all three index returns, particularly during the COVID-19 era; however, the intensity and frequency of these clusters were markedly heightened for the XU100 index during and after COVID-19. The causation link between the computed conditional variance series was assessed using the Granger and Toda-Yamamoto techniques. The findings indicate a bidirectional causal relationship between spillovers in the DAX and S&P500 indices. A relationship between DAXG and XU100G is evident at a 5% significance level; however, while XU100 strongly influences S&P500, no significant relationship is observed from SP500G to XU100G. The results indicate that volatilities in Turkish stock markets influence German and US stock markets, although all foreign shocks do not uniformly impact Turkish stock markets.

Keywords

Volatility , Stock Returns , XU100 , Spillovers , GARCH

References

• Adekoya, O. B., & Oliyide, J. A. (2021). How COVID-19 drives connectedness among commodity and financial markets: Evidence from TVP-VAR and causality-in-quantiles techniques. Resources Policy, 70. https://doi.org/10.1016/j.resourpol.2020.101898
• Akhtaruzzaman, M., Boubaker, S., & Sensoy, A. (2021). Financial contagion during COVID–19 crisis. Finance Research Letters, 38. https://doi.org/10.1016/j.frl.2020.101604
• Allou, E. J., Adeleye, B. N., Cheng, J., & Abdul, R. (2020). Is there a nexus between China outward foreign direct investment and welfare in Côte dʼIvoire? Empirical evidence from the Toda–Yamamoto procedure. African Development Review, 32(3), 499-510. https://doi.org/10.1111/1467-8268.12456
• Andersen, T. G., Bollerslev, T., Christoffersen, P. F., & Diebold, F. X. (2006). Volatility and correlation forecasting. Handbook of Economic Forecasting, 1, 777-878. https://doi.org/10.1016/S1574-0706(05)01015-3
• Baele, L. (2005). Volatility spillover effects in European equity markets. Journal of Financial and Quantitative Analysis, 40(2), 373–401. https://doi.org/10.1017/S0022109000002350
• Bajaj, S., & Vibha, D. U. A. (2014). Investigation of causal relationship between stock prices and trading volume using Toda and Yamamoto procedure. Eurasian Journal of Business and Economics, 7(14), 155-181. https://doi.org/10.17015/ejbe.2014.014.09
• Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal Of Econometrics, 31(3), 307-327. https://doi.org/10.1016/0304-4076(86)90063-1
• Cheung, W., Fung, S., & Tsai, S. C. (2010). Global capital market interdependence and spillover effect of credit risk: evidence from the 2007–2009 global financial crisis. Applied Financial Economics, 20(1-2), 85-103. https://doi.org/10.1080/09603100903262962
• Dhamija, A. K., & Bhalla, V. K. (2010). Financial time series forecasting: comparison of neural networks and ARCH models. International Research Journal Of Finance And Economics, 49, 185-202.
• 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
• Dinga, B., Claver, J. H., Cletus, K. K., & Che, S. F. (2023). Modeling and Predicting Exchange Rate Volatility: Application of Symmetric GARCH and Asymmetric EGARCH and GJR-GARCH Models. Journal Of The Cameroon Academy Of Sciences, 19(2), 155-178. https://doi.org/10.4314/jcas.v19i2.6
• Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal Of The Econometric Society, 987–1007. https://doi.org/10.2307/1912773
• Gamba-Santamaria, S., Gomez-Gonzalez, J. E., Hurtado-Guarin, J. L., & Melo-Velandia, L. F. (2017). Stock market volatility spillovers: Evidence for Latin America. Finance Research Letters, 20, 207-216. https://doi.org/10.1016/j.frl.2016.10.001
• Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal Of The Econometric Society, 424–438. https://doi.org/10.2307/1912791
• Habiba, U.E., Peilong, S., Zhang, W., & Hamid, K. (2020). International stock markets Integration and dynamics of volatility spillover between the USA and South Asian markets: evidence from Global financial crisis. Journal Of Asia Business Studies, 14(5), 779–794. https://doi.org/10.1108/JABS-03-2019-0071
• Jung, R. C., & Maderitsch, R. (2014). Structural breaks in volatility spillovers between international financial markets: contagion or mere interdependence? Journal Of Banking & Finance, 47, 331-342. https://doi.org/10.1016/j.jbankfin.2013.12.023
• Kanas, A. (1998). Volatility spillovers across equity markets: European evidence. Applied Financial Economics, 8(3), 245–256. https://doi.org/10.1080/096031098333005
• Kim, B. H., Kim, H., & Lee, B. S. (2015). Spillover effects of the US financial crisis on financial markets in emerging Asian countries. International Review of Economics & Finance, 39, 192-210. https://doi.org/10.1016/j.iref.2015.04.005
• Koutmos, G., & Booth, G. G. (1995). Asymmetric volatility transmission in international stock markets. Journal Of International Money and Finance, 14(6), 747–762. https://doi.org/10.1016/0261-5606(95)00031-3
• Li, Y., & Giles, D. E. (2015). Modelling volatility spillover effects between developed stock markets and Asian emerging stock markets. International Journal of Finance & Economics, 20(2), 155-177. https://doi.org/10.1002/ijfe.1506
• Liu, C. (2016). Spillover effects in major equity markets: A GARCH BEKK approach. Open Access Library Journal, 3, 1–21. doi: https://doi.org/10.4236/oalib.1102160
• Majdoub, J., & 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
• Mensi, W., Hammoudeh, S., & Kang, S. H. (2017). Risk spillovers and portfolio management between developed and BRICS stock markets. The North American Journal Of Economics And Finance, 41, 133-155. https://doi.org/10.1016/j.najef.2017.03.006
• Miyakoshi, T. (2003). Spillovers of stock return volatility to Asian equity markets from Japan and the US. Journal Of International Financial Markets, Institutions And Money, 13(4), 383-399. https://doi.org/10.1016/S1042-4431(03)00015-5
• Panda, A. K., & Nanda, S. (2018). A GARCH modelling of volatility and M-GARCH approach of stock market linkages of North America. Global Business Review, 19(6), 1538-1553. https://doi.org/10.1177/09721509187935
• Salmanov, O. N., Babina, N. V., Samoshkina, M. V., Drachena, I. P., & Salmanova, I. P. (2020). The effects of volatility and changes in conditional correlations in the stock markets of Russia and developed countries. Economic Annals, 65(227), 67-94. https://doi.org/10.2298/EKA2027067S
• Schmidt, L. (2021). Volatility forecasting performance of GARCH models: a study on Nordic indices during COVID-19 (Unpublished dissertation). Retrieved from https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184529
• Sijabat, R. (2022). The association of economic growth, foreign aid, foreign direct investment and gross capital formation in Indonesia: Evidence from the Toda–Yamamoto approach. Economies, 10(4).
• Sugimoto, K., Matsuki, T., & Yoshida, Y. (2014). The global financial crisis: An analysis of the spillover effects on African stock markets. Emerging Markets Review, 21, 201–233. https://doi.org/10.1016/j.ememar.2014.09.004
• Thanasas, G. L., & Havrylov, I. (2024). Empirical analysis of the causal relationships of spillovers in the volatility of the S&P-500 index. Journal Of European Economy, 23(2), 192–203. https://doi.org/10.35774/jee2024.02.192
• Toda, H. Y., & Phillips, P. C. (1993). The spurious effect of unit roots on vector autoregressions: an analytical study. Journal Of Econometrics, 59(3), 229–255. https://doi.org/10.1016/0304-4076(93)90024-Y
• Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal Of Econometrics, 66(1-2), 225-250. https://doi.org/10.1016/0304-4076(94)01616-8
• Toong, D., Goh, K. W., & Sim, Y. W. (2023). Estimation of stock market index volatility using the GARCH model: Causality between stock indices. Asian Economic And Financial Review, 13(3), 162-179. https://doi.org/10.55493/5002.v13i3.4738
• Vo, D. H., Ho, C. M., & Dang, T. H. N. (2022). Stock market volatility from the COVID-19 pandemic: new evidence from the Asia-Pacific region. Heliyon, 8(9). https://doi.org/10.1016/j.heliyon.2022.e10763
• Vo, X. V., & Tran, T. T. A. (2020). Modelling volatility spillovers from the US equity market to ASEAN stock markets. Pacific-Basin Finance Journal, 59. https://doi.org/10.1016/j.pacfin.2019.101246
• Wan, J., Yin, L., & Wu, Y. (2024). Return and volatility connectedness across global ESG stock indexes: evidence from the time-frequency domain analysis. International Review Of Economics & Finance, 89, 397-428. https://doi.org/10.1016/j.iref.2023.10.038
• Wang, Y., & Liu, L. (2016). Spillover effect in Asian financial markets: A VAR-structural GARCH analysis. China Finance Review International, 6(2), 150-176. https://doi.org/10.1108/CFRI-11-2014-0095
• Wang, Y., Pan, Z., & Wu, C. (2018). Volatility spillover from the US to international stock markets: A heterogeneous volatility spillover GARCH model. Journal Of Forecasting, 37(3), 385-400. https://doi.org/10.1002/for.2509
• Worthington, A., & Higgs, H. (2004). Transmission of equity returns and volatility in Asian developed and emerging markets: a multivariate GARCH analysis. International Journal Of Finance & Economics, 9(1), 71–80. https://doi.org/10.1002/ijfe.222
• Yıldız, B. (2016). Oynaklık tahmininde simetrik ve asimetrik GARCH modellerinin kullanılması: seçilmiş BİST alt sektör endeksleri üzerine bir uygulama. Muhasebe ve Finansman Dergisi, (72), 83-106. https://doi.org/10.25095/mufad.396721
• Youssef, M., Mokni, K., & Ajmi, A. N. (2021). Dynamic connectedness between stock markets in the presence of the COVID-19 pandemic: Does economic policy uncertainty matter? Financial Innovation, 7(1). https://doi.org/10.1186/s40854-021-00227-3
• Zarezade, R., Ghousi, G., & Mohammadi, E. (2024). Spillover effects of volatility between the Chinese stock market and selected emerging economies in the Middle East: A conditional correlation analysis with portfolio optimization perspective. Accounting, 10(2), 97–106. https://doi.org/10.5267/j.ac.2023.11.001
• Zhang, Y., & Mao, J. (2022). COVID-19's impact on the spillover effect across the Chinese and US stock markets. Finance Research Letters, 47. https://doi.org/10.1016/j.frl.2022.102684