Dynamic correlation analysis in the ASEAN equity markets during 2009–2018
-
DOIhttp://dx.doi.org/10.21511/imfi.16(2).2019.21
-
Article InfoVolume 16 2019, Issue #2, pp. 249-259
- Cited by
- 769 Views
-
108 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
This study examines the static and dynamic correlations in the ASEAN equity markets. The importance of this research appears from the fact that practitioners can get the benefit if their investments yield the same or higher returns given lower or the same risk in their portfolio. Firstly, this advantage comes from including the assets that decrease volatility of the portfolio. Hence, the correlation between the ASEAN markets should be examined. Secondly, co-movements in market realizations may increase global financial instability. Its existence is important for international investors, financial institutions, and policy makers. The study locates the relationship between ASEAN and its major trading partners, including Japanese, US, and UK markets, in order to find more rational results. This study utilizes alternative multivariate GARCH forms to provide useful information on the dynamic evolution and implications of return volatilities. The results show that the volatilities of all the equity markets under study are persistent over time. The estimates from VEC model indicate that the movements of the US and UK equity market returns have some degree of influence on several of the ASEAN equity markets. The results imply that, first, most of the developing ASEAN equity markets work by its own information with small relation to the developed world. Second, it is still convincing to state that investing in ASEAN equity markets should provide investors a better mean-variance portfolio. And, third, buy-and-hold strategy seems to be more beneficial than readjusting the ASEAN equities portfolio.
- Keywords
-
JEL Classification (Paper profile tab)G11, G12, G15
-
References44
-
Tables10
-
Figures0
-
- Table 1. Stock market index descriptive statistics
- Table 2. Unconditional correlation matrix of market return
- Table 3. Johansen’s test statistics for cointegration rank
- Table 4. Vector error corrections model estimates and analysis
- Table 5. Univariate generalized autoregressive conditional heteroskedasticity (GARCH (1,1)) estimates
- Table 6. Conditional correlation generalized autoregressive conditional heteroskedasticity (CCC-GARCH(1,1)) estimates
- Table 7. Dynamic correlation generalized autoregressive conditional heteroskedasticity (DCC-GARCH(1,1)) estimates (mean of correlations)
- Table 8. Dynamic correlation generalized autoregressive conditional heteroskedasticity (DCC-GARCH(1,1)) estimates (maximum of correlations)
- Table 9. Dynamic correlation generalized autoregressive conditional heteroskedasticity (DCC-GARCH(1,1)) estimates (minimum of correlations)
- Table 10. Dynamic correlation generalized autoregressive conditional heteroskedasticity (DCC-GARCH(1,1)) estimates (standard deviation of correlations)
-
- Aawaar, G., Domeher, D., & Nsiah, C. (2018). Evolving Co-Movements of Africa’s Stock Markets: Evidence from DCC-GARCH Analysis. International Research Journal of Finance and Economics, 170, 110-131.
- Aggarwal, R., Inclan, C., & Leal, R. (1999). Volatility in Emerging Stock Markets. The Journal of Financial and Quantitative Analysis, 34(1), 33-55.
- Ang, A., & Chen, J. (2002). Asymmetric correlations of equity portfolios. Journal of Financial Economics, 63(3), 443-494.
- Arshanapalli, B., & Doukas, J. (1993). International stock market linkages: Evidence from the pre-and post-October 1987 period. Journal of Banking & Finance, 17(1), 193-208.
- Bekaert, G., & Wu, G. (2000). Asymmetric volatility and risk in equity markets. Review of Financial Studies, 13(1), 1-42.
- Bollerslev, T. (1990). Modelling the coherence in short-run nominal exchange rates: a multivariate generalized ARCH model. The Review of Economics and Statistics, 72(3), 498-505.
- Bollerslev, T., Engle, R. F., & Wooldridge, J. M. (1988). A Capital Asset Pricing Model with Time-Varying Covariances. Journal of Political Economy, 96(1), 116-131.
- Bowman, R. G., Chan, K. F., & Comer, M. R. (2010). Diversification, rationality and the ASEAN economic crisis. Pacific-Basin Finance Journal, 18(1), 1-23.
- Cappiello, L., Engle, R., & Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4(4), 537-572.
- Cha, B., & Oh, S. (2000). The relationship between developed equity markets and the Pacific Basin’s emerging equity markets. International Review of Economics & Finance, 9(4), 299-322.
- Chaudhuri, K., & Wu, Y. (2003). Random walk versus breaking trend in stock prices: Evidence from emerging markets. Journal of Banking & Finance, 27(4), 575-592.
- Cheung, Y., & Ng, L. (1993). Interactions between the US and Japan stock market indices. Journal of International Financial Markets, Institutions & Money, 2(2), 51-70.
- Chiang, T. C., Jeon, B. N., & Li, H. (2007). Dynamic correlation analysis of financial contagion: Evidence from ASEAN markets. Journal of International Money and Finance, 26(7), 1206-1228.
- Chittedi, K. R. (2015). Financial crisis and contagion effects to Indian stock market:‘DCC–GARCH’analysis. Global Business Review, 16(1), 50-60.
- Engle, R. (2002). Dynamic conditional correlation. Journal of Business and Economic Statistics, 20(3), 339-350.
- Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica, 50(4), 987-1007.
- Engle, R., & Ng, V. (1993). Measuring and testing the impact of news on volatility. Journal of finance, 48(5), 1749-1778.
- Engle, R., & Susmel, R. (1993). Common volatility in international equity markets. Journal of Business & Economic Statistics, 11(2), 167-176.
- Groenen, P., & Franses, P. (2000). Visualizing time-varying correlations across stock markets. Journal of Empirical Finance, 7(2), 155-172.
- Hou, Y., & Li, S. (2016). Information transmission between US and China index futures markets: An asymmetric DCC GARCH approach. Economic Modelling, 52, 884-897.
- Johansen, S. (1991). Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica: Journal of the Econometric Society, 59(6), 1551-1580.
- King, M., & Wadhwani, S. (1990). Transmission of volatility between stock markets. Review of Financial Studies, 3(1), 5-33.
- King, M., Sentana, E., & Wadhwani, S. (1994). Volatility and Links between National Stock Markets. Econometrica, 62(4), 901-933.
- Koutmos, G., & Booth, G. (1995). Asymmetric volatility transmission in international stock markets. Journal of International Money and Finance, 14(6), 747-762.
- Kroner, K., & Ng, V. (1998). Modeling asymmetric comovements of asset returns. Review of Financial Studies, 11(4), 817-844.
- Liu, Y. A., & Pan, M. S. (1997). Mean and Volatility Spillover Effects in the U.S. and Pacific–Basin Stock Markets. Multinational Finance Journal, 1(1), 47-62.
- Longin, F., & Solnik, B. (1995). Is the correlation in international equity returns constant: 1960–1990? Journal of International Money and Finance, 14(1), 3-26.
- Longin, F., & Solnik, B. (2001). Extreme correlation of international equity markets. The Journal of Finance, 56(2), 649-676.
- Markowitz, H. (1959). Portfolio Selection: Efficient Diversification of Investment. New York: John Wiley.
- Markowitz, H. (1991a). Foundations of portfolio theory. Journal of finance, 46(2), 469-477.
- Markowitz, H. (1991b). Portfolio selection: efficient diversification of invstments: Wiley.
- Markowitz, H., Todd, G., & Sharpe, W. (2000). Mean-variance analysis in portfolio choice and capital markets. Wiley.
- Mazzotta, S. (2008). How important is asymmetric covariance for the risk premium of international assets? Journal of Banking & Finance, 32(8), 1636-1647.
- Morana, C., & Beltratti, A. (2002). The effects of the introduction of the euro on the volatility of European stock markets. Journal of banking and finance, 26(10), 2047-2064.
- Morana, C., & Beltratti, A. (2008). Comovements in international stock markets. Journal of International Financial Markets, Institutions and Money, 18(1), 31-45.
- Osterwald-Lenum, M. (1992). A note with quantiles of the asymptotic distribution of the maximum likelihood cointegration rank test statistics. Oxford bulletin of economics and statistics, 54(3), 461-472.
- Ramchand, L., & Susmel, R. (1998). Volatility and cross correlation across major stock markets. Journal of Empirical Finance, 5(4), 397-416.
- Solnik, B., Boucrelle, C., & Le Fur, Y. (1996). International market correlation and volatility. Financial Analysts Journal, 52(5), 17-34.
- Syriopoulos, T. (2004). International portfolio diversification to Central European stock markets. Applied Financial Economics, 14(17), 1253-1268.
- Syriopoulos, T. (2006). Risk and return implications from investing in emerging European stock markets. Journal of International Financial Markets, Institutions and Money, 16(3), 283-299.
- Syriopoulos, T., & Roumpis, E. (2009). Dynamic correlations and volatility effects in the Balkan equity markets. Journal of International Financial Markets, Institutions and Money, 19(4), 565-587.
- Trabelsi, N., & Naifar, N. (2017). Are Islamic stock indexes exposed to systemic risk? Multivariate GARCH estimation of CoVaR. Research in International Business and Finance, 42, 727-744.
- Yang, J., Kolari, J., & Min, I. (2003). Stock market integration and financial crises: the case of Asia. Applied Financial Economics, 13(7), 477-486.
- Yang, S., & Doong, S. (2004). Price and volatility spillovers between stock prices and exchange rates: Empirical evidence from the G-7 countries. International Journal of Business, 3(2), 139-153.