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.