THE DYNAMIC INTERRELATION OF VN-INDEX AND MAJOR WORLD STOCK MARKETS: BAYESIAN DCC-GARCH APPROACH

Đồng Mạnh Cường; Trần Minh Châu

doi:10.34238/tnu-jst.4365

THE DYNAMIC INTERRELATION OF VN-INDEX AND MAJOR WORLD STOCK MARKETS: BAYESIAN DCC-GARCH APPROACH

About this article

Received: 16/04/21 Revised: 13/05/21 Published: 19/05/21

Authors

1. Dong Manh Cuong , TNU - International School
2. Tran Minh Chau, TNU - International School

Abstract

This study examined the time-varying interrelation of the Vietnam stock market index (VN-index) and other major stock markets in the world including the New York Stock Exchange (NYSE), Japanese stock market (Nikkei), and European New Exchange Technology (Euronext). Instead of using a constant correlation, we employed the idea of a dynamic correlation in which the relationships between stock markets change overtime. This approach helps to identify the volatility of assets’ interrelation in different stock market cycles. To achieve this, we employed the multivariate time series model, DCC-GARCH model, which fits GARCH model to each of univariate time series and uses their standardized residuals to find the dynamic conditional correlation between each time series. We improved the estimation process of this model by using the Bayesian estimation approach. Our empirical results found that the linkages between VN-index and three major stock markets were always positive and the contagions were consistently transferred stronger during the distress time of global finance.

Keywords

DCC-GARCH model; VN-index; Bayesian estimation; Time-varying correlation; Stock markets

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References

[1] G. Cifarelli and G. Paladino, “Volatility linkages across three major equity markets: A financial arbitrage approach,” Journal of International Money and Finance, vol. 24, pp. 413-439, 2005.

[2] Z. Chinzara and M. J. Aziakpono, “Dynamic returns linkages and volatility transmission between south African and world major stock markets,” Studies in Economics and Econometrics, vol. 33, pp. 69-94, 2009.

[3] C. Nguyen, M. I. Bhatti, and D. Henry, “Are Vietnam and Chinese stock markets out of the US contagion effect in extreme events?” Physica A: Statistical Mechanics and its Applications, vol. 480, pp. 10-21, 2017.

[4] X. V. Vo and C. Ellis, “International financial integration: Stock return linkages and volatility transmission between Vietnam and advanced countries,” Emerging Markets Review, vol. 36, pp. 19-27, 2018.

[5] Y. K. Tse and A. K. C. Tsui, “A multivariate GARCH model with time-varying correlations,” Journal of Business and Economic Statistics, vol. 20, pp. 351–362, 2002.

[6] R. F. Engle, “Dynamic conditional correlation - a simple class of multivariate GARCH models,” Journal of Business and Economic Statistics, vol. 20, pp. 339–350, 2002.

[7] S. Celik, “The more contagion effect on emerging markets: The evidence of DCC-GARCH model,” Economic Modelling, vol. 29, pp. 1946-1959, 2012.

[8] P. M. Jones and E. Olson, “The time-varying correlation between uncertainty, output, and inflation: Evidence from a DCC-GARCH model,” Economics Letters, vol. 118, pp. 33-37, 2013.

[9] J. H. Cho, and A. M. Parhizgari, “East Asian Financial Contagion under DCC-Garch,” International Journal of Banking and Finance, vol. 6, pp. 17-30, 2009.

[10] C. W. S. Chen, R. Gerlach, and E. M. H. Lin, “Bayesian estimation of smoothly mixing time-varying parameter GARCH models,” Computational Statistics and Data Analysis, vol. 76, pp. 194–209, 2014.

[11] J. A. Fioruci, R. S. Ehlers, and M. G. A. Filho, “Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions,” Journal of Applied Statistics, vol. 41, pp. 320-331, 2014.

DOI: https://doi.org/10.34238/tnu-jst.4365

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