Volatility spillover between Germany, France, and CEE stock markets
Abstract
The CEE stock markets are more and more integrated in the European financial markets. The growth of the integration of financial markets favours the volatility and return spillover between them. The current study analyses the volatility spillover among the stock markets in the countries from Central and East Europe (CEE) and Germany and France with the aim to identify the possibilities of reduction of a portfolio risk. A special attention is granted to the analysis during the pandemic caused by COVID-19. The time-varying parameter vector autoregressive (TVP-VAR) model on which is based the methodology proposed by Antonakakis and Gabauer (2017) is used to estimate the evolution in time of volatility spillover. The empirical results obtained for the period January 2001 – September 2021 highlight the increase in volatility spillover between the countries analysed when the pandemic caused by COVID-19 was confirmed. The lack of volatility integration of the markets analysed enables the making of arbitrages in order to reduce the risk of a portfolio. The results obtained are important in the management of financial asset portfolios.
Keyword : stock markets, emerging markets, risk, volatility transmission, TVP-VAR, spillover index
How to Cite
Chirilă, V., & Chirilă, C. (2022). Volatility spillover between Germany, France, and CEE stock markets. Journal of Business Economics and Management, 23(6), 1280–1298. https://doi.org/10.3846/jbem.2022.18194
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Andrieș, A. M., & Galasan, E. (2020). Measuring financial contagion and spillover effects with a state dependent sensitivity value-at-risk model. Risks, 8(1), 5. https://doi.org/10.3390/risks8010005
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Apostolakis, G. N., Floros, C., Gkillas, K., & Wohar, M. (2021). Political uncertainty, COVID-19 pandemic and stock market volatility transmission. Journal of International Financial Markets, Institutions and Money, 74, 101383. https://doi.org/10.1016/j.intfin.2021.101383
Aslam, F., Ferreira, P., Mughal, K. S., & Bashir, B. (2021). Intraday volatility spillovers among European financial markets during COVID-19. Inter-national Journal of Financial Studies, 9(1), 5. https://doi.org/10.3390/ijfs9010005
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Beirne, J., Caporale, G. M., Schulze-Ghattas, M., & Spagnolo, N. (2013). Volatility spillovers and contagion from mature to emerging stock markets. Review of International Economics, 21(5), 1060–1075. https://doi.org/10.1111/roie.12091
Ben Slimane, F., Mehanaoui, M., & Kazi, I. A. (2013). How does the financial crisis affect volatility behavior and transmission among European stock markets? International Journal of Financial Studies, 1(3), 81–101. https://doi.org/10.3390/ijfs1030081
Boțoc, C., & Anton, S. G. (2020). New empirical evidence on CEE’s stock markets integration. The World Economy, 43(10), 2785–2802. https://doi.org/10.1111/twec.12961
Căpraru, B., & Ihnatov, I. (2012). Interest rate transmission and exchange rate arrangements in the Central and Eastern European countries: Evidence from the current international financial crises, Procedia – Social and Behavioral Sciences, 58, 1273–1282. https://doi.org/10.1016/j.sbspro.2012.09.1110
Chatziantoniou, I., Gabauer, D., & Marfatia, H. A. (2022). Dynamic connectedness and spillovers across sectors: Evidence from the Indian stock mar-ket. Scottish Journal of Political Economy, 69(3), 283–300. https://doi.org/10.1111/sjpe.12291
Chaudhary, R., Bakhshi, P., & Gupta, H. (2020). Volatility in international stock markets: An empirical study during COVID-19. Journal of Risk and Financial Management, 13(9), 208. https://doi.org/10.3390/jrfm13090208
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Chirilă, V., Turturean, C. I., & Chirilă, C. (2015). Volatility spillovers between Eastern European and Euro Zone stock markets. Transformations in Business & Economics, 14(2A), 464–477.
Corbet, S., Hou, Y. G., Hu, Y., Oxley, L., & Xu, D. (2021). Pandemic-related financial market volatility spillovers: Evidence from the Chinese COVID-19 epicentre. International Review of Economics & Finance, 71, 55–81. https://doi.org/10.1016/j.iref.2020.06.022
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 427–431. https://doi.org/10.2307/2286348
Diebold, F., & 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., & Yilmaz, 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), 813–836. https://doi.org/10.2307/2171846
Fasanya, I., Oyewole, O., Adekoya, O., & Odei-Mensah, J. (2021). Dynamic spillovers and connectedness between COVID-19 pandemic and global foreign exchange markets, Economic Research-Ekonomska Istraživanja, 34(1), 2059–2084. https://doi.org/10.1080/1331677X.2020.1860796
Gabauer, D. (2021). Dynamic measures of asymmetric & pairwise connectedness within an optimal currency area: Evidence from the ERM I system. Journal of Multinational Financial Management, 60, 100680. https://doi.org/10.1016/j.mulfin.2021.100680
Gherghina, Ș. C., Armeanu, D. Ș., & Joldeș, C. C. (2021). COVID-19 Pandemic and Romanian stock market volatility: A GARCH approach. Journal of Risk and Financial Management, 14(8), 341. https://doi.org/10.3390/jrfm14080341
Jebabli, I., Kouaissah, N., & Arouri, M. (2021). Volatility spillovers between stock and energy markets during crises: A comparative assessment be-tween the 2008 global financial crisis and the COVID-19 pandemic crisis. Finance Research Letters, 46(A), 102363. https://doi.org/10.1016/j.frl.2021.102363
Kanas, A. (1998). Volatility spillovers across equity markets: European evidence. Applied Financial Economics, 8(3), 245–256. https://doi.org/10.1080/096031098333005
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
Kregzde, A. (2018). Wavelets analysis of the Baltic equity market: Risk and comovement with the European market. Engineering Economics, 29(5), 507–515. https://doi.org/10.5755/j01.ee.29.5.19330
Li, W. (2021). COVID-19 and asymmetric volatility spillovers across global stock markets. North American Journal of Economics & Finance, 58, 101474. https://doi.org/10.1016/j.najef.2021.101474
Liu, T., & Gong, X. (2020). Analyzing time-varying volatility spillovers between the crude oil markets using a new method, Energy Economics, 87, 104711. https://doi.org/10.1016/j.eneco.2020.104711
Lupu, R., Călin, A. C., Zeldea, C. G., & Lupu, I. (2021). Systemic risk spillovers in the European energy sector. Energies, 14(19), 6410. https://doi.org/10.3390/en14196410
Lütkepohl, H. (2005). New introduction to multiple time series analysis. Springer. https://doi.org/10.1007/978-3-540-27752-1_4
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. https://doi.org/10.1016/S0261-5606(00)00006-1
Okorie, D. I., & Lin, B. (2021). Stock markets and the COVID-19 fractal contagion effects. Finance Research Letters, 38, 101640. https://doi.org/10.1016/j.frl.2020.101640
Perron, P. (1989). The great crash, the oil price shock and the unit root hypothesis. Econometrica, 57(6), 1361–1401. https://doi.org/10.2307/1913712
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
Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. https://doi.org/10.2307/2336182
Shahzad, S. J. H., Naeem, M. A., Peng, Z., & Bouri, E. (2021). Asymmetric volatility spillover among Chinese sectors during COVID-19. Internation-al Review of Financial Analysis, 75, 101754. https://doi.org/10.1016/j.irfa.2021.101754
Škrinjarić, T. (2019). Stock market stability on selected CEE and SEE markets: A quantile regression approach. Post-Communist Economies, 32(3), 352–375. https://doi.org/10.1080/14631377.2019.1640994
Škrinjarić, T., & Šego, B. (2020). Risk connectedness of selected CESEE stock markets: A spillover index approach. China Finance Review Interna-tional, 10(4), 447–472. https://doi.org/10.1108/CFRI-07-2019-0124
Spulbar, C., Trivedi, J., & Birau, R. (2020). Investigating abnormal volatility transmission patterns between emerging and developed stock markets: A case study. Journal of Business Economics and Management, 21(6), 1561–1592. https://doi.org/10.3846/jbem.2020.13507
Theodossiou, P., & Lee, U. (1993). Mean and volatility spillovers across major national stock markets: Further empirical evidence. Journal of Financial Research, 16(4), 337–350. https://doi.org/10.1111/j.1475-6803.1993.tb00152.x
Wei, Z., Luo, Y., Huang, Z., & Guo, K. (2020). Spillover effects of RMB exchange rate among B&R countries: Before and during COVID-19 event. Finance Research Letters, 37, 101782. https://doi.org/10.1016/j.frl.2020.101782
Yilmaz, K. (2010). Return and volatility spillovers among the East Asian equity markets. Journal of Asian Economics, 21(3), 304–313. https://doi.org/10.1016/j.asieco.2009.09.001
Yousaf, I., & Ali, S. (2020). Discovering interlinkages between major cryptocurrencies using high-frequency data: New evidence from COVID-19 pandemic. Financial Innovation, 6, 45. https://doi.org/10.1186/s40854-020-00213-1
Zhang, W., Zhuang, X., & Wu, D. (2020). Spatial connectedness of volatility spillovers in G20 stock markets: Based on block models analysis. Finance Research Letters, 34, 101274. https://doi.org/10.1016/j.frl.2019.08.022
Ajayi, R. A., Mehdian, S., & Stoica, O. (2018). An empirical examination of the dissemination of equity price innovations between the emerging mar-kets of Nordic-Baltic States and major advanced markets. Emerging Markets Finance and Trade, 54(3), 642–660. https://doi.org/10.1080/1540496X.2017.1419426
Aktan, B., Korsakienė, R., & Smaliukiene, R. (2010). Time‐varying volatility modelling of Baltic stock markets. Journal of Business Economics and Management, 11(3), 511–532. https://doi.org/10.3846/jbem.2010.25
Andrieș, A. M., & Galasan, E. (2020). Measuring financial contagion and spillover effects with a state dependent sensitivity value-at-risk model. Risks, 8(1), 5. https://doi.org/10.3390/risks8010005
Antonakakis, N., & Gabauer, D. (2017). Refined measures of dynamic connectedness based on TVP-VAR (MPRA Paper No. 78282).
Antonakakis, N., Chatziantoniou, I., & Gabaur, D. (2020). Redefined measures of dynamic connectedness based on time-varying parameter vector au-toregressions. Journal of Risk and Financial Management, 13(4), 84. https://doi.org/10.3390/jrfm13040084
Apostolakis, G. N., Floros, C., Gkillas, K., & Wohar, M. (2021). Political uncertainty, COVID-19 pandemic and stock market volatility transmission. Journal of International Financial Markets, Institutions and Money, 74, 101383. https://doi.org/10.1016/j.intfin.2021.101383
Aslam, F., Ferreira, P., Mughal, K. S., & Bashir, B. (2021). Intraday volatility spillovers among European financial markets during COVID-19. Inter-national Journal of Financial Studies, 9(1), 5. https://doi.org/10.3390/ijfs9010005
Balcilar, M., Gabauer, D., & Umar, Z. (2021). Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach. Resources Policy, 73, 102219. https://doi.org/10.1016/j.resourpol.2021.102219
Beirne, J., Caporale, G. M., Schulze-Ghattas, M., & Spagnolo, N. (2013). Volatility spillovers and contagion from mature to emerging stock markets. Review of International Economics, 21(5), 1060–1075. https://doi.org/10.1111/roie.12091
Ben Slimane, F., Mehanaoui, M., & Kazi, I. A. (2013). How does the financial crisis affect volatility behavior and transmission among European stock markets? International Journal of Financial Studies, 1(3), 81–101. https://doi.org/10.3390/ijfs1030081
Boțoc, C., & Anton, S. G. (2020). New empirical evidence on CEE’s stock markets integration. The World Economy, 43(10), 2785–2802. https://doi.org/10.1111/twec.12961
Căpraru, B., & Ihnatov, I. (2012). Interest rate transmission and exchange rate arrangements in the Central and Eastern European countries: Evidence from the current international financial crises, Procedia – Social and Behavioral Sciences, 58, 1273–1282. https://doi.org/10.1016/j.sbspro.2012.09.1110
Chatziantoniou, I., Gabauer, D., & Marfatia, H. A. (2022). Dynamic connectedness and spillovers across sectors: Evidence from the Indian stock mar-ket. Scottish Journal of Political Economy, 69(3), 283–300. https://doi.org/10.1111/sjpe.12291
Chaudhary, R., Bakhshi, P., & Gupta, H. (2020). Volatility in international stock markets: An empirical study during COVID-19. Journal of Risk and Financial Management, 13(9), 208. https://doi.org/10.3390/jrfm13090208
Chirilă, V., & Chirilă, C. (2020). Asymmetric return and volatility transmission in Euro zone and Baltic countries stock markets. Ovidius University Annals, Economic Sciences Series, 2, 2–11. https://ideas.repec.org/a/ovi/oviste/vxxy2020i2p2-11.html
Chirilă, V., Turturean, C. I., & Chirilă, C. (2015). Volatility spillovers between Eastern European and Euro Zone stock markets. Transformations in Business & Economics, 14(2A), 464–477.
Corbet, S., Hou, Y. G., Hu, Y., Oxley, L., & Xu, D. (2021). Pandemic-related financial market volatility spillovers: Evidence from the Chinese COVID-19 epicentre. International Review of Economics & Finance, 71, 55–81. https://doi.org/10.1016/j.iref.2020.06.022
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74, 427–431. https://doi.org/10.2307/2286348
Diebold, F., & 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., & Yilmaz, 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), 813–836. https://doi.org/10.2307/2171846
Fasanya, I., Oyewole, O., Adekoya, O., & Odei-Mensah, J. (2021). Dynamic spillovers and connectedness between COVID-19 pandemic and global foreign exchange markets, Economic Research-Ekonomska Istraživanja, 34(1), 2059–2084. https://doi.org/10.1080/1331677X.2020.1860796
Gabauer, D. (2021). Dynamic measures of asymmetric & pairwise connectedness within an optimal currency area: Evidence from the ERM I system. Journal of Multinational Financial Management, 60, 100680. https://doi.org/10.1016/j.mulfin.2021.100680
Gherghina, Ș. C., Armeanu, D. Ș., & Joldeș, C. C. (2021). COVID-19 Pandemic and Romanian stock market volatility: A GARCH approach. Journal of Risk and Financial Management, 14(8), 341. https://doi.org/10.3390/jrfm14080341
Jebabli, I., Kouaissah, N., & Arouri, M. (2021). Volatility spillovers between stock and energy markets during crises: A comparative assessment be-tween the 2008 global financial crisis and the COVID-19 pandemic crisis. Finance Research Letters, 46(A), 102363. https://doi.org/10.1016/j.frl.2021.102363
Kanas, A. (1998). Volatility spillovers across equity markets: European evidence. Applied Financial Economics, 8(3), 245–256. https://doi.org/10.1080/096031098333005
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
Kregzde, A. (2018). Wavelets analysis of the Baltic equity market: Risk and comovement with the European market. Engineering Economics, 29(5), 507–515. https://doi.org/10.5755/j01.ee.29.5.19330
Li, W. (2021). COVID-19 and asymmetric volatility spillovers across global stock markets. North American Journal of Economics & Finance, 58, 101474. https://doi.org/10.1016/j.najef.2021.101474
Liu, T., & Gong, X. (2020). Analyzing time-varying volatility spillovers between the crude oil markets using a new method, Energy Economics, 87, 104711. https://doi.org/10.1016/j.eneco.2020.104711
Lupu, R., Călin, A. C., Zeldea, C. G., & Lupu, I. (2021). Systemic risk spillovers in the European energy sector. Energies, 14(19), 6410. https://doi.org/10.3390/en14196410
Lütkepohl, H. (2005). New introduction to multiple time series analysis. Springer. https://doi.org/10.1007/978-3-540-27752-1_4
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. https://doi.org/10.1016/S0261-5606(00)00006-1
Okorie, D. I., & Lin, B. (2021). Stock markets and the COVID-19 fractal contagion effects. Finance Research Letters, 38, 101640. https://doi.org/10.1016/j.frl.2020.101640
Perron, P. (1989). The great crash, the oil price shock and the unit root hypothesis. Econometrica, 57(6), 1361–1401. https://doi.org/10.2307/1913712
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
Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. https://doi.org/10.2307/2336182
Shahzad, S. J. H., Naeem, M. A., Peng, Z., & Bouri, E. (2021). Asymmetric volatility spillover among Chinese sectors during COVID-19. Internation-al Review of Financial Analysis, 75, 101754. https://doi.org/10.1016/j.irfa.2021.101754
Škrinjarić, T. (2019). Stock market stability on selected CEE and SEE markets: A quantile regression approach. Post-Communist Economies, 32(3), 352–375. https://doi.org/10.1080/14631377.2019.1640994
Škrinjarić, T., & Šego, B. (2020). Risk connectedness of selected CESEE stock markets: A spillover index approach. China Finance Review Interna-tional, 10(4), 447–472. https://doi.org/10.1108/CFRI-07-2019-0124
Spulbar, C., Trivedi, J., & Birau, R. (2020). Investigating abnormal volatility transmission patterns between emerging and developed stock markets: A case study. Journal of Business Economics and Management, 21(6), 1561–1592. https://doi.org/10.3846/jbem.2020.13507
Theodossiou, P., & Lee, U. (1993). Mean and volatility spillovers across major national stock markets: Further empirical evidence. Journal of Financial Research, 16(4), 337–350. https://doi.org/10.1111/j.1475-6803.1993.tb00152.x
Wei, Z., Luo, Y., Huang, Z., & Guo, K. (2020). Spillover effects of RMB exchange rate among B&R countries: Before and during COVID-19 event. Finance Research Letters, 37, 101782. https://doi.org/10.1016/j.frl.2020.101782
Yilmaz, K. (2010). Return and volatility spillovers among the East Asian equity markets. Journal of Asian Economics, 21(3), 304–313. https://doi.org/10.1016/j.asieco.2009.09.001
Yousaf, I., & Ali, S. (2020). Discovering interlinkages between major cryptocurrencies using high-frequency data: New evidence from COVID-19 pandemic. Financial Innovation, 6, 45. https://doi.org/10.1186/s40854-020-00213-1
Zhang, W., Zhuang, X., & Wu, D. (2020). Spatial connectedness of volatility spillovers in G20 stock markets: Based on block models analysis. Finance Research Letters, 34, 101274. https://doi.org/10.1016/j.frl.2019.08.022