The Corelation of Pandemic and Indonesia Presidency of G20 in The Capital Market G20 Member Countries
Abstract
The correlation between the capital market of G20 member countries is important to analyze.
Depending on a country’s economy, capital market integration may have different effects. A more intense
bilateral relationship (trade intensity) can significantly affect the movement of capital market shares
between countries. The current research used the Multivariate GARCH Model/DCC-GARCH method. The
condition of capital market integration before the Indonesian G20 Presidency showed that Indonesia
(JKSE) had the strongest integration with Australia (ASX) (0.563814) and South Korea (KOSPI) (0.542470).
After the G20 presidency, Indonesia (JKSE) had the strongest capital market integration with India (NSE)
(0.507229) and the USA (NYSE). It was also found that China (SSE) had an integration with South Korea
(KOSPI), while Germany (DAX) and Australia (ASX) had an integration with the UK (FTSE100). The
conclusion is that the higher autocorrelation, the higher the effect of the volatility of stock market
movements in the two countries involved. Furthermore, capital market integration can be influenced by
geospatial and economic relations.
Views: 5696
Downloads
References
Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31, 307–327.
Díaz, A., Esparcia, C., & López, R. (2022). The diversifying role of socially responsible investments during the COVID-19 crisis: A risk management and portfolio performance analysis. Economic Analysis and Policy, 75, 39–60. https://doi.org/10.1016/j.eap.2022.05.001
Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339–350. https://doi.org/10.1198/073500102288618487
Hess, M. K. (2004). Dynamic and asymmetric impacts of macroeconomic fundamentals on an integrated stock market. Journal of International Financial Markets, Institutions and Money, 14(5), 455–471. https://doi.org/10.1016/j.intfin.2003.12.005
Jiang, Y., Nie, H., & Monginsidi, J. Y. (2017). Co-movement of ASEAN stock markets: New evidence from wavelet and VMD-based copula tests. Economic Modelling, 64(January), 384–398. https://doi.org/10.1016/j.econmod.2017.04.012
Pretorius, E. (2002). Economic determinants of emerging stock market interdependence. Emerging Markets Review, 3(1), 84–105. https://doi.org/10.1016/S1566-0141(01)00032-2
Sugiyanto, S. C., & Robiyanto, R. (2021). Integrasi Dinamis Pasar Modal Indonesia dengan Pasar Modal International pada Masa Pandemi Covid-19. AFRE (Accounting and Financial Review), 3(2), 143–151. https://doi.org/10.26905/afr.v3i2.5551
Wang, S., & Guo, Z. (2020). A study on the co-movement and influencing factors of stock markets between China and the other G20 members. International Journal of Finance and Economics, 25(1), 43–62. https://doi.org/10.1002/ijfe.1727
Wongbangpo, P., & Sharma, S. C. (2002). Stock market and macroeconomic fundamental dynamic interactions: ASEAN-5 countries. Journal of Asian Economics, 13(1), 27–51. https://doi.org/10.1016/S1049-0078(01)00111-7
Zhang, W., Zhuang, X., & Li, Y. (2019). Dynamic evolution process of financial impact path under the multidimensional spatial effect based on G20 financial network. Physica A: Statistical Mechanics and Its Applications, 532. https://doi.org/10.1016/j.physa.2019.121876
-
28
-
25
-
20
-
14
-
13
-
12
-
12
-
11
-
11
-
11