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COVID-19 SÜRECİNDE BORSALARARASI OYNAKLIK YAYILIMLARI: KIRILGAN BEŞLİ VE GELİŞMİŞ ÜLKE PİYASALARI ÖRNEĞİ

Year 2022, Volume: 18 Issue: 2, 449 - 469, 30.06.2022
https://doi.org/10.17130/ijmeb.979135

Abstract

Kısa dönemde küresel piyasaları etkisi altına alan COVID-19 salgını ve salgının ekonomi ve finans piyasasında yarattığı korku ve endişe, varlık fiyatlarında ve finans piyasasında oynaklıkların artmasına neden olmuştur. Bu çalışma söz konusu dönemde; Endonezya, Türkiye, Brezilya, Hindistan ve Güney Afrika’dan oluşan kırılgan beşli piyasaları ile Fransa, ABD, Almanya, İngiltere ve Japonya’dan oluşan gelişmiş ülke piyasaları arasındaki oynaklık yayılımını araştırmaktadır. Diebold ve Yılmaz (2012) yayılım endeksi yönteminin kullanıldığı çalışmada; ülkelerin 5 Ocak 2015 – 28 Mayıs 2021 dönemi günlük verileri kullanılmış ve tahmin sonuçları, oynaklık yayılımının COVID-19’un Dünya Sağlık Örgütünce küresel salgın ilan edildiği 2020 Mart ayından itibaren hızla arttığını, 2021 Nisan ayından itibaren ise aşıların yaygınlık kazanmasıyla birlikte yayılımın salgın öncesi döneme döndüğünü göstermektedir. Tahmin sonuçları ayrıca; gelişmiş ülke piyasalarındaki oynaklık yayılımının kırılgan beşli piyasalarındaki oynaklık yayılımından daha yüksek olduğunu, BOVESPA (Brezilya) ve FTSE100 (İngiltere) piyasalarının en yüksek net oynaklık yayıcısı, JKSE (Endonezya) ve NIKKEI225 (Japonya) piyasalarının ise en yüksek oynaklık alıcısı olduğunu göstermiştir.

References

  • Akhtaruzzaman, M., Boubaker, S., & Sensoy, A. (2021). Financial contagion during COVID–19 crisis. Finance Research Letters, 38, 1-20, 101604.
  • Aslam, F., Ferreira, P., Mughal, K. S., & Bashir, B. (2021). Intraday volatility spillovers among European financial markets during COVID-19. International Journal of Financial Studies, 9(1), 1-19.
  • Cheung, Y. W., & Ng, L. K. (1996). A causality-in-variance test and its application to financial market prices. Journal of Econometrics, 72(1-2), 33-48.
  • 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.
  • Daube, C. H. (2020). The corona virus stock exchange crash. ZBW – Leibniz Information Centre for Economics, Kiel, Hamburg, https://www.econstor.eu/bitstream/10419/214881/1/The%20Corona%20Virus%20Stock%20Exchange%20Crash.pdf
  • Diebold, F. X., & Yılmaz, K. (2012). Better to give than to receive: predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66.
  • 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.
  • Hafner, C. M., & Herwartz, H. (2006). A lagrange multiplier test for causality in variance. Economics Letters, 93(1), 137-141.
  • Hong, Y. (2001). A test for volatility spillover with application to exchange rates. Journal of Econometrics, 103(1-2), 183-224.
  • Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119-147.
  • Laborda, R., & Olmo, J. (2021). Volatility spillover between economic sectors in financial crisis prediction: Evidence spanning the great financial crisis and Covid-19 pandemic. Research in International Business and Finance, 57, 101402.
  • Li, Y., Zhuang, X. & Wang, J. (2021). Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: evidence from China. The North American Journal of Economics and Finance, 56, 1-15, 101359.
  • Malik, K., Sharma, S., & Kaur, M. (2021). Measuring contagion during COVID-19 through volatility spillovers of BRIC countries using diagonal BEKK approach. Journal of Economic Studies.
  • Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics letters, 58(1), 17-29.
  • 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.
  • Shu, H. C., & Chang, J. H. (2019). Spillovers of volatility index: evidence from US, European, and Asian stock markets. Applied Economics, 51(19), 2070-2083.
  • Singh, P., Kumar, B., & Pandey, A. (2010). Price and volatility spillovers across North American, European and Asian stock markets. International Review of Financial Analysis, 19(1), 55-64.
  • Wang, D., Li, P., & Huang, L. (2020). Volatility spillovers between major international financial markets during the COVID-19 pandemic. Available at SSRN 3645946.
  • WEF (2020). Mad March: how the stock market is being hit by COVID-19, World Economic Forum, https://www.weforum.org/agenda/2020/03/stock-market-volatility-coronavirus/
  • WHO (2021). WHO Coronavirus (COVID-19) Dashboard, World Health Organization, https://covid19.who.int/
  • Zhang, P., Sha, Y., & Xu, Y. (2021). Stock market volatility spillovers in G7 and BRIC. Emerging Markets Finance and Trade, 1-13.
  • Zhang, W., & Hamori, S. (2021). Crude oil market and stock markets during the COVID-19 pandemic: evidence from the US, Japan, and Germany. International Review of Financial Analysis, 74, 1-13, 101702.
  • Zhang, W., Zhuang, X., Lu, Y., & Wang, J. (2020). Spatial linkage of volatility spillovers and its explanation across G20 stock markets: a network framework. International Review of Financial Analysis, 71, 1-13, 101454.

VOLATILITY SPILLOVERS INTER STOCK MARKETS DURING THE COVID-19 PROCESS: AN EXAMPLE OF FRAGILE FIVE AND DEVELOPED COUNTRIES

Year 2022, Volume: 18 Issue: 2, 449 - 469, 30.06.2022
https://doi.org/10.17130/ijmeb.979135

Abstract

The COVID-19 epidemic, which affected global markets in the short term, and the fear and anxiety created by the epidemic in the economy and financial markets, caused volatility in asset prices and financial markets. In this study, in the mentioned period; It investigates the volatility spillover between the fragile five markets consisting of Indonesia, Turkey, Brazil, India and South Africa, and the markets of developed countries consisting of France, USA, Germany, England and Japan. In the study, the data of the countries for the period 5 January 2015 – 28 May 2021 were estimated by the spillover index method of Diebold and Yılmaz (2012). The estimation results show that the volatility spillover has increased rapidly since March 2020, when COVID-19 was declared a global epidemic by the World Health Organization, and that the spillover returned to the pre-epidemic period from April 2021, when vaccines became widespread in countries. In the study, it was understood that the volatility spillover in the developed country markets is higher than the volatility spillover in the fragile five markets. In addition, BOVESPA (Brazil) and FTSE100 (UK) markets are the highest emitters of net volatility, while JKSE (Indonesia) and NIKKEI225 (Japan) markets are the highest volatility buyers.

References

  • Akhtaruzzaman, M., Boubaker, S., & Sensoy, A. (2021). Financial contagion during COVID–19 crisis. Finance Research Letters, 38, 1-20, 101604.
  • Aslam, F., Ferreira, P., Mughal, K. S., & Bashir, B. (2021). Intraday volatility spillovers among European financial markets during COVID-19. International Journal of Financial Studies, 9(1), 1-19.
  • Cheung, Y. W., & Ng, L. K. (1996). A causality-in-variance test and its application to financial market prices. Journal of Econometrics, 72(1-2), 33-48.
  • 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.
  • Daube, C. H. (2020). The corona virus stock exchange crash. ZBW – Leibniz Information Centre for Economics, Kiel, Hamburg, https://www.econstor.eu/bitstream/10419/214881/1/The%20Corona%20Virus%20Stock%20Exchange%20Crash.pdf
  • Diebold, F. X., & Yılmaz, K. (2012). Better to give than to receive: predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66.
  • 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.
  • Hafner, C. M., & Herwartz, H. (2006). A lagrange multiplier test for causality in variance. Economics Letters, 93(1), 137-141.
  • Hong, Y. (2001). A test for volatility spillover with application to exchange rates. Journal of Econometrics, 103(1-2), 183-224.
  • Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119-147.
  • Laborda, R., & Olmo, J. (2021). Volatility spillover between economic sectors in financial crisis prediction: Evidence spanning the great financial crisis and Covid-19 pandemic. Research in International Business and Finance, 57, 101402.
  • Li, Y., Zhuang, X. & Wang, J. (2021). Analysis of the cross-region risk contagion effect in stock market based on volatility spillover networks: evidence from China. The North American Journal of Economics and Finance, 56, 1-15, 101359.
  • Malik, K., Sharma, S., & Kaur, M. (2021). Measuring contagion during COVID-19 through volatility spillovers of BRIC countries using diagonal BEKK approach. Journal of Economic Studies.
  • Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics letters, 58(1), 17-29.
  • 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.
  • Shu, H. C., & Chang, J. H. (2019). Spillovers of volatility index: evidence from US, European, and Asian stock markets. Applied Economics, 51(19), 2070-2083.
  • Singh, P., Kumar, B., & Pandey, A. (2010). Price and volatility spillovers across North American, European and Asian stock markets. International Review of Financial Analysis, 19(1), 55-64.
  • Wang, D., Li, P., & Huang, L. (2020). Volatility spillovers between major international financial markets during the COVID-19 pandemic. Available at SSRN 3645946.
  • WEF (2020). Mad March: how the stock market is being hit by COVID-19, World Economic Forum, https://www.weforum.org/agenda/2020/03/stock-market-volatility-coronavirus/
  • WHO (2021). WHO Coronavirus (COVID-19) Dashboard, World Health Organization, https://covid19.who.int/
  • Zhang, P., Sha, Y., & Xu, Y. (2021). Stock market volatility spillovers in G7 and BRIC. Emerging Markets Finance and Trade, 1-13.
  • Zhang, W., & Hamori, S. (2021). Crude oil market and stock markets during the COVID-19 pandemic: evidence from the US, Japan, and Germany. International Review of Financial Analysis, 74, 1-13, 101702.
  • Zhang, W., Zhuang, X., Lu, Y., & Wang, J. (2020). Spatial linkage of volatility spillovers and its explanation across G20 stock markets: a network framework. International Review of Financial Analysis, 71, 1-13, 101454.
There are 23 citations in total.

Details

Primary Language Turkish
Subjects Finance
Journal Section Research Articles
Authors

Zekai Şenol 0000-0001-8818-0752

Coşkun Karaca 0000-0003-4294-2365

Publication Date June 30, 2022
Submission Date August 5, 2021
Acceptance Date February 12, 2022
Published in Issue Year 2022 Volume: 18 Issue: 2

Cite

APA Şenol, Z., & Karaca, C. (2022). COVID-19 SÜRECİNDE BORSALARARASI OYNAKLIK YAYILIMLARI: KIRILGAN BEŞLİ VE GELİŞMİŞ ÜLKE PİYASALARI ÖRNEĞİ. Uluslararası Yönetim İktisat Ve İşletme Dergisi, 18(2), 449-469. https://doi.org/10.17130/ijmeb.979135