Spillover Effects of Stock Markets in the COVID-19 Pandemic Period: Evidence From Central and East European Countries

Year 2022, Volume: 72 Issue: 1, 211 - 238, 30.06.2022

Selma Öner , Hakan Öner , Hande Kılıç Satıcı

https://doi.org/10.26650/ISTJECON2021-994570

Abstract

This study aims to investigate the correlation and the spillover effects between Central and East European (CEE) Countries’ stock markets during the Covid-19 Pandemic Period. CEE countries are listed as Bulgaria, Croatia, the Czech Republic, Hungary, Poland, Romania, the Slovak Republic, Slovenia, Estonia, Latvia, and Lithuania by OECD. The data set was obtained from the Bloomberg data services and includes 308 observations of daily returns between March 11th, 2020 and August 1st, 2021. As a result of the empirical analysis using the Pearson Correlation, the Multivariate VAR Model, and the Granger Causality Test, a high correlation was found between the stock markets of CEE countries, and 15 causality relationships were determined. The analysis also revealed bidirectional relationships between the Bulgaria Stock Exchange Index and Romania Bucharest Stock Exchange Index, the Polish Warsaw Stock Exchange Index and Croatia Zagreb Stock Exchange Index, the Romania Bucharest Stock Exchange Index and Bulgaria Stock Exchange Index, and the Croatia Zagreb Stock Exchange Index and Polish Warsaw Stock Exchange Index. High correlation and causality relationships, which are also supported by impulse-response and variance decomposition test results, reveal that there is a spillover effect between the stock markets of CEE countries.

Keywords

Stock markets, Pearson Correlation, Granger casuality test, COVID-19 pandemic period, CEE countries.

COVID-19 Pandemi Döneminde Hisse Senedi Piyasalarının Yayılma Etkileri: Orta ve Doğu Avrupa Ülkeleri Kanıtları

Abstract

Bu çalışmanın amacı, OECD tarafından Orta ve Doğu Avrupa ülkeleri olarak adlandırılan; Bulgaristan, Hırvatistan, Çek Cumhuriyeti, Macaristan, Polonya, Romanya, Slovak Cumhuriyeti, Slovenya, Estonya, Letonya ve Litvanya ülkelerinin hisse senedi piyasaları arasındaki korelasyonu ve piyasalar arasındaki yayılma etkisini araştırmaktır. Bu çalışmada kullanılan veriler, 11 Mart 2020 - 1 Ağustos 2021 tarihleri arasındaki 308 güne ait hisse senedi getirilerini içermektedir. Veriler, Bloomberg veri servislerinden elde edilmiştir. Pearson Korelasyonu, çok değişkenli VAR modeli ve Granger Nedensellik testi kullanılan çalışma sonucuna göre; hisse senedi piyasaları arasında yüksek korelasyonlar ve 15 adet nedensellik ilişkisi tespit edilmiştir. Bu sonuçlara ilave olarak, Bulgaristan Menkul Kıymetler Borsası Endeksi ile Romanya Bukres Menkul Kıymetler Borsası Endeksi, Polonya Varşova Menkul Kıymetler Borsası Endeksi ve Hırvatistan Zagrep Menkul Kıymetler Borsası Endeksi, Romanya Bukres Menkul Kıymetler Borsası Endeksi ve Bulgaristan Menkul Kıymetler Borsası Endeksi, Hırvatistan Zagrep Borsa Endeksi ve Polonya Varşova Menkul Kıymetler Borsası Endeksi arasında çift yönlü bir nedensellik ilişkisi olduğu ortaya konulmaktadır. Etki-tepki ve varyans ayrıştırma testleri sonuçları ile desteklenen yüksek korelasyon ve nedensellik ilişkileri, Orta ve Doğu Avrupa ülkeleri borsaları arasında yayılma etkisi olduğunu ortaya koymaktadır.

Keywords

Hisse senedi piyasaları, Pearson korelasyonu, Granger nedensellik testi, COVID-19 pandemi dönemi, Orta ve Doğu Avrupa Ülkeleri.

References

• Alkan B. & Çiçek S. (2020). Spillover effect in financial markets in Turkiye. Central Bank Review, 20(2), 53-64. doi:10.1016/j.cbrev.2020.02.003 google scholar
• Bajo-Rubio, O. & Berke, B. & McMillan, D. (2017). The behaviour of asset return and volatility spillovers in Turkiye: A tale of two crises. Research in International Business and Finance, 41(C), 577-589. doi:10.1016/j.ribaf.2017.04.003 google scholar
• Balcerzak, A.P. & Zurek, M. (2011). Foreign direct investment and unemployment: VAR analysis for Poland in the years 1995-2009. European Research StudiesJournal, 14(1), 3-14. google scholar
• Beji, S. & Xiii, P. (2007). Financial openness and financial development in the south mediterranean sea countries: Institutional approach and calculation of development thresholds. European Research Studies Journal, 11(3-4), 107-127. google scholar
• Berberoğlu, M. (2020). The investigation of volatility spillover effect between stock markets of Turkiye, Italy, Greece and Russia. Business & Management Studies: An InternationalJournal, 8(2), 1576-1598. doi:10.15295/bmij.v8i2.1475 google scholar
• Bozma, G. & Başar, S. (2018). Analyzing volatility transmissions between stock markets of Turkiye, Romanıa, Poland, Hungary and Ukraine usıng M-GARCH model. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 36 (4) , 1-15. doi: 10.17065/huniibf.346119 google scholar
• 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(366), 427-431. doi:10.2307/2286348. google scholar
• Dickey, D. A. & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057-1072. doi:10.2307/1912517 google scholar
• Diebold, F. X. & Yılmaz, K. (2010). Better to give than to receive: predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. doi:10.1016/j. ijforecast.2011.02.00657-66 google scholar
• Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424-438. doi:10.2307/1912791. google scholar
• Granger, C. W. J. & Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 26, 1045-1066. doi:10.1016/0304-4076(74)90034 google scholar
• Gulzar, S., Kayani, G. M., Xiaofeng, H., Ayub U. & Rafique, A. (2019) Financial cointegration and spillover effect of global financial crisis: a study of emerging Asian financial markets. Economic Research-Ekonomska Istrazivanja, 32(1), 187-218, doi:10.1080/1331677X.2018.1550001 google scholar
• Gujarati, D. N. (2001). Temel ekonometri. (Çev. Ü. Şenesen, G.G. Şenesen). İstanbul:Literatür Yayıncılık. google scholar
• Kang S., Eom C. & Ok, S (2017, October). Dynamic volatility spillovers across emerging CDS markets. In: 11th Multidisciplinary Academic Conference, (pp. 196-202). Prague. google scholar
• 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), 155-77. doi:10.1002/ijfe.1506. google scholar
• Maddala, G.S. (2001) Introduction to econometrics. New York, Wiley. google scholar
• MacKinnon, J. G. (1996). Numerical distribution functions for unit root and cointegration tests. Journal ofApplied Econometrics, 11(6), 601-618. google scholar
• Philips P. C. B. & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346. doi:10.2307/2336182 google scholar
• Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1-48. doi:10.2307/1912017 google scholar
• Silvia, A., Zulpahmi, & Sumardi. (2019). Spillover effect of Islamic stock markets in Asia. European Research Studies Journal, 22(2), 28-40. doi:10.35808/ersj/1424 google scholar
• Yousaf I, Ali S, Wong W-K. (2020). An empirical analysis of the volatility spillover effect between world-leading and the Asian stock markets: Implications for portfolio management. Journal of Risk and Financial Management, 13(10), 1-28. doi:10.3390/jrfm13100226 google scholar