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The Volatility and Correlations of Stock Returns of Some Crisis-Hit Countries: US, Greece, Thailand and Malaysia: Evidence from MGARCH-DCC applications

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  • Masih, Mansur
  • Majid, Hamdan Abdul

Abstract

This paper investigates the volatility and correlations of stock returns of some crisis-hit countries such as, US, Greece, Thailand and Malaysia during the major global financial crises since 1992. The paper makes an attempt to address the following two issues: Firstly, to measure the extent of volatility of the stock indices under study and also the correlation of the Malaysian index with the other country indices. Secondly, given the correlations, how best can a normal investor harness them to ensure maximum return in the short and the long run with a particular reference to the correlation between the Malaysian index and other country indices. The MGARCH-DCC approach is employed for the analysis. The findings tend to indicate that the investors’ behaviour converges and correlations are significantly higher across the two Asian countries in the sample. The level of volatilities of the indices’ return of all the four markets has increased significantly for the period under study. The level and magnitude of volatilities and correlations is consistently high between Malaysia and Thailand market (lowest of 0.02 in 1993 to highest of 0.65 in 1998) followed by US and Greece markets. Greece seems to be the most volatile market followed by Malaysia, US and Thailand (except for the period between 1993 and 1998). One possible explanation is that the contagion effect takes place early in the crisis and that herding behaviour dominates the latter stages of the crisis. For our second question, the apparent high correlation coefficients during crisis periods imply that the gain from international diversification by holding a portfolio consisting of diverse stocks from these contagion countries declines, since these stock markets are commonly exposed to systematic risk(beta). An increasing integration and stronger co-movement among stock markets will result in decreasing opportunity to gain from portfolio diversification.

Suggested Citation

  • Masih, Mansur & Majid, Hamdan Abdul, 2013. "The Volatility and Correlations of Stock Returns of Some Crisis-Hit Countries: US, Greece, Thailand and Malaysia: Evidence from MGARCH-DCC applications," MPRA Paper 58946, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:58946
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    References listed on IDEAS

    as
    1. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    2. Pesaran, Bahram & Pesaran, M. Hashem, 2007. "Modelling Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," IZA Discussion Papers 2906, Institute of Labor Economics (IZA).
    3. M. Hashem Pesaran & Bahram Pesaran, 2007. "Volatilities and Conditional Correlations in Futures Markets with a Multivariate t Distribution," CESifo Working Paper Series 2056, CESifo.
    4. Kearney, Colm & Poti, Valerio, 2006. "Correlation dynamics in European equity markets," Research in International Business and Finance, Elsevier, vol. 20(3), pages 305-321, September.
    5. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    6. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    7. Enzo Weber, 2007. "Volatility and Causality in Asia Pacific Financial Markets," SFB 649 Discussion Papers SFB649DP2007-004, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    8. Lee, Jong-Wha & Hong, Kiseok, 2012. "Economic growth in Asia: Determinants and prospects," Japan and the World Economy, Elsevier, vol. 24(2), pages 101-113.
    9. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
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    More about this item

    Keywords

    Volatility; Correlations; portfolio diversification; MGARCH-DCC;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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