BRICS hisse senedi piyasalarının Covid-19 dönemi dinamik ağ bağlantılılığı

Yıl 2021, , 1486 - 1498, 13.10.2021

Onur Polat

https://doi.org/10.25287/ohuiibf.936124

Cited By: 5

Öz

Bu çalışma, BRICS hisse senedi piyasaları arasındaki getiri ve oynaklık ağ bağlantılılığını, Barunik ve Ellington'un (2020) zamanla değişen parametreli-VAR (TVP-VAR) tabanlı frekans bağlantılılığı yaklaşımını kullanarak Ocak 2019 ve Mart 2021 döneminde incelemektedir. Bu bağlamda, COVID-19 salgınını kapsayan bir dönemde BRICS hisse senedi piyasaları arasındaki kısa, orta ve uzun vadeli getiri ve oynaklık ağ bağlantılıliğı tahmin ediyoruz. Ayrıca, ikili yayılmaların büyüklüğünü karşılaştırmak için sakin bir zamanda (11 Mart 2019) ve bir kargaşa zamanında (11 Mart 2020) frekans getiri/oynaklık bağlantılı ağ yapılarına odaklanmaktayız. Hem dinamik toplam getiri hem de oynaklık bağlantılılıkları, COVID-19 salgınının ortaya çıkmasından hemen sonra önemli bir şekilde yükselmekte ve dolayısıyla COVID-19'un BRICS hisse senedi piyasaları bağlantılılığı üzerindeki önemli etkisini göstermektedir. Dinamik getiri ve oynaklık ağ bağlantılılık yapıları, 11 Mart 2020'de önemli seviyede yükselen ikili yayılmalara işaret etmektedir.

Anahtar Kelimeler

Dinamik Ağlar, TVP-VAR, İkili Taşmalar, Finansal Bağlantılılık

Dynamic network connectedness of BRICS equity markets during the Covid-19 era

Öz

This study examines the return and volatility network connectedness of BRICS equity markets between January 2019 and March 2021 by utilizing the time varying parameter-VAR (TVP-VAR) based frequency connectedness approach of Barunik and Ellington (2020). In this context, we estimate short-, medium-, and long-term network return and volatility connectedness of BRICS equity markets during an episode that covers the recent COVID-19 pandemic. Furthermore, we focus on the network structures of frequency return/volatility connectedness at a tranquil time (March 11, 2019) and at a turmoil time (March 11, 2020) to compare the magnitude of pairwise spillovers. Both dynamic total overall return and volatility connectedness indexes markedly surged aftermath the COVID-19 outbreak, and accordingly indicate the significant impact of the COVID-19 on the BRICS equity markets connectedness. Network structures of dynamic return and volatility connectedness indicate remarkably amplified pairwise spillovers on March 11, 2020.

Anahtar Kelimeler

Dynamic Networks, TVP-VAR, Pairwise Spillovers, Financial Connectedness

Kaynakça

• 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.
• Barigozzi, M., Hallin, M., Soccorsi, S., & von Sachs, R. (2020). Time-varying general dynamic factor models and the measurement of financial connectedness. Journal of Econometrics, 222(1:B), 324-343.
• Barunik, J., & Ellington, M. (2020). Dynamic Networks in Large Financial and Economic Systems. arXiv preprint arXiv:2007.07842.
• Bissoondoyal-Bheenick, E., Do, H., Hu, X., & Zhong, A. (2020). Learning from SARS: Return and Volatility Connectedness in COVID-19. Finance Research Letters, 101796.
• Bouri, E., Cepni, O., Gabauer, D., & Gupta, R. (2021). Return connectedness across asset classes around the COVID-19 outbreak. International Review of Financial Analysis, 73, 101646.
• Chandy, L., Gertz, G., & Linn, J. (2009). Tracking the global financial crisis: An analysis of the IMF’s world economic outlook. Wolfensohn Center for Development at Brookings. Retrieved from http://www. brookings. edu/reports/2009/05_financial_crisis_linn. aspx.
• 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.
• De Bruyckere, V., Gerhardt, M., Schepens, G., & Vander Vennet, R. (2013). Bank/sovereign risk spillovers in the European debt crisis. Journal of Banking & Finance, 37(12), 4793-4809.
• Demirer, M., Diebold, F. X., Liu, L., & Yilmaz, K. (2018). Estimating global bank network connectedness. Journal of Applied Econometrics, 33(1), 1-15.
• D'Errico, M., Grassi, R., Stefani, S., & Torriero, A. (2009). Shareholding networks and centrality: an application to the Italian financial market. In Networks, Topology and Dynamics (pp. 215-228). Springer, Berlin, Heidelberg.
• Diebold, F. X., Liu, L., & Yilmaz, K. (2017). Commodity connectedness (No. w23685). National Bureau of Economic Research.
• 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.
• Eboli, M. (2004). Systemic risk in financial networks: a graph theoretic approach. Universita di Chieti Pescara.
• Erdős, P., & Rényi, A. (1959). On random graphs. Publicationes Mathematicae 6, 290–297.
• Fernández-Rodríguez, F., & Sosvilla-Rivero, S. (2020). Volatility transmission between stock and foreign exchange markets: a connectedness analysis. Applied Economics, 52(19), 2096-2108.
• Hesse, H., & Frank, N. (2009). Financial spillovers to emerging markets during the global financial crisis. IMF Working Papers, 1-20.
• IMF (2021). World Economic Outlook. Retrieved from https://www.imf.org/en/Publications/WEO/Issues/2021/03/23/world-economic-outlook-april-2021.
• Lee, H. S., & Lee, W. S. (2020). Network Connectedness among Northeast Asian Financial Markets. Emerging Markets Finance and Trade, 56(13), 2945-2962.
• Mensi, W., Boubaker, F. Z., Al-Yahyaee, K. H., & Kang, S. H. (2018). Dynamic volatility spillovers and connectedness between global, regional, and GIPSI stock markets. Finance Research Letters, 25, 230-238.
• Nier, E., Yang, J., Yorulmazer, T., & Alentorn, A. (2007). Network models and financial stability. Journal of Economic Dynamics and Control, 31(6), 2033-2060.
• Polat, O. (2020). Frequency Connectedness and Network Analysis in Equity Markets: Evidence from G-7 Countries. Akdeniz İİBF Dergisi, 20(2), 221-226.
• Saltoglu, B., & Yenilmez, T. (2010). Analyzing Systemic Risk with Financial Networks An Application During a Financial Crash (No. 26684). University Library of Munich, Germany.
• So, M. K., Chu, A. M., & Chan, T. W. (2021). Impacts of the COVID-19 pandemic on financial market connectedness. Finance Research Letters, 38, 101864.
• Su, X. (2020). Measuring extreme risk spillovers across international stock markets: A quantile variance decomposition analysis. The North American Journal of Economics and Finance, 51, 101098.
• The World Bank (2020). Global Economic Prospects. Retrieved from https://www.worldbank.org/en/publication/global-economic-prospects.
• Wang, G. J., Xie, C., Jiang, Z. Q., & Stanley, H. E. (2016). Extreme risk spillover effects in world gold markets and the global financial crisis. International Review of Economics & Finance, 46, 55-77.
• Wen, D., Wang, G. J., Ma, C., & Wang, Y. (2019). Risk spillovers between oil and stock markets: A VAR for VaR analysis. Energy Economics, 80, 524-535.
• Yang, J., & Zhou, Y. (2013). Credit risk spillovers among financial institutions around the global credit crisis: Firm-level evidence. Management Science, 59(10), 2343-2359.