CHANGE IN VOLATILITY REGIMES AND DIVERSIFICATION IN EMERGING STOCK MARKETS

A multivariate Markov-switching ARCH (MVSWARCH) model in which variance/correlations for stock returns is controlled by a state-varying mechanism is introduced and used to design a state-varying US-EM (emerging market) portfolio establishment strategy. Additionally, a conventional random-variance framework, the MVGARCH (multivariate GARCH) model, in which a time-varying technique is involved is employed and subjected to comparative analysis. The empirical results are consistent with the following notions: First, as being consistent with a study conducted by Ramchand and Susmel , the US-EM market correlations are higher when the US market is more volatile. However, this study further indicates that the US-EM market correlations increase relatively more when both the US and EM markets simultaneously experience a high variance condition. Moreover, the situation of both the US and EM stock markets at a high volatility state is associated with a minimum risk reduction benefit and a maximum cross-market correlation. Second, the state-varying portfolio loadings established by the MVSWARCH model could effectively enhance asset allocation effectiveness; however, this benefit arises more as a result of risk reduction than an increase in mean returns.