Purpose - This purpose of this paper is to investigate the existence of cointegration and causality between the stock market price indices of Thailand and its major trading partners (Australia, Hong Kong, Indonesia, Japan, Korea, Malaysia, the Philippines, Singapore, Taiwan, the UK and the USA), using monthly data spanning December 1987 to December 2005. Design/methodology/approach - This paper used both the Engle-Granger two-step procedure (assuming no structural breaks) and the Gregory and Hansen test (allowing for one structural break) provide no evidence of a long-run relationship between the stock prices of Thailand and these countries. Findings - Based on the empirical results obtained from these two residual-based cointegration tests, potential long-run benefits exist from diversifying the investment portfolios internationally to reduce the associated systematic risks across countries. However, in the short-run, three unidirectional Granger causalities run from the stock returns of Hong Kong, the Philippines and the UK to those of Thailand, pairwise. Furthermore, there are two unidirectional causalities running from the stock returns of Thailand to those of Indonesia and the USA. Empirical evidence was also found of bidirectional Granger causality, suggesting that the stock returns of Thailand and three of its neighbouring countries (Malaysia, Singapore and Taiwan) are interrelated. Originality/value - No previous study examines the possibility that the pair-wise long-run relationship between the stock prices of Thailand and those of both emerging and developed markets may have been subject to a structural break.

This paper examines the dynamics of cross-country GDP volatility transmission and their conditional correlations. We use quarterly data (1961-2008) for Australia, Canada, the UK and the US to construct and estimate a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model. According to the results from the mean growth equations, we identified significant cross-country GDP growth spillover among these countries. Furthermore, the growth volatility between the US and Canada indicates the highest conditional correlation. As expected, we also found that the shock influences are mainly exerted by the larger economies onto the smaller economies.

This paper provides some insight into the asymmetric effects of stock market volatility transmission using weekly stock market return data (January 1992-June 2010) of four countries, namely, Australia, Singapore, the United Kingdom and the United States within a MGARCH (multivariate generalised autoregressive conditional heteroskedasticity) framework. Our results indicate that negative shocks in each market play a more important role in increasing both volatility and covolatilities than positive shocks. In addition, as expected, we identified that all markets (particularly Australia and Singapore) exhibit significant positive mean and volatility spillovers from the US stock market returns, but not the other way around.

This paper examines the interplay between stock market returns and their volatility, focusing on the Asian and global financial crises of 1997-98 and 2008-09 for Australia, Singapore, the UK, and the US. We use a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model and weekly data (January 1992-June 2009). Based on the results obtained from the mean return equations, we could not find any significant impact on returns arising from the Asian crisis and more recent global financial crises across these four markets. However, both crises significantly increased the stock return volatilities across all of the four markets. Not surprisingly, it is also found that the US stock market is the most crucial market impacting on the volatilities of smaller economies such as Australia. Our results provide evidence of own and cross ARCH and GARCH effects among all four markets, suggesting the existence of significant volatility and cross volatility spillovers across all four markets. A high degree of time-varying co-volatility among these markets indicates that investors will be highly unlikely to benefit from diversifying their financial portfolio by acquiring stocks within these four countries only.

Purpose - The purpose of this paper is to investigate the relationships between stock market returns of 13 countries based upon monthly data spanning December 1987 to April 2007. Design/methodology/approach - Specifically, the principal component (PC) and maximum likelihood (ML) methods are used to examine any discernable patterns of stock market co-movements. Findings - Factor analysis provides evidence that stock returns in a number of Asian countries are highly correlated and, based on the resulting robust factor loadings, they form the first well-defined common factor. The paper also finds consistent results (based on both the PC and ML methods) suggesting that the stock market returns of developed countries are also highly correlated, and constitute our second factor. Practical implications - The paper concludes that, inter alia, geographical proximity and the level of economic development do matter when it comes to co-movements of stock returns and that this has important implications for financial portfolio diversification if the aim is to reduce systematic risks across countries. Originality/value - Very few previous studies have investigated the benefits from portfolio diversification by using the PC and ML methods.