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Purpose This paper aims to study the daily returns and volatility spillover effects in common stock prices between China and four countries in Southeast Asia (Vietnam, Thailand, Singapore and Malaysia). Design/methodology/approach The analysis uses a vector autoregression with a bivariate GARCH-BEKK model to capture return linkage and volatility transmission spanning the period including the pre- and post-2008 Global Financial Crisis. Findings The main empirical result is that the volatility of the Chinese market has had a significant impact on the other markets in the data sample. For the stock return, linkage between China and other markets seems to be remarkable during and after the Global Financial Crisis. Notably, the findings also indicate that the stock markets are more substantially integrated into the crisis. Practical implications The results have considerable implications for portfolio managers and institutional investors in the evaluation of investment and asset allocation decisions. The market participants should pay more attention to assess the worth of across linkages among the markets and their volatility transmissions. Additionally, international portfolio managers and hedgers may be better able to understand how the volatility linkage between stock markets interrelated overtime; this situation might provide them benefit in forecasting the behavior of this market by capturing the other market information. Originality/value This paper would complement the emerging body of existing literature by examining how China stock market impacts on their neighboring countries including Vietnam, Thailand, Singapore and Malaysia. Furthermore, this is the first investigation capturing return linkage and volatility spill over between China market and the four Southeast Asian markets by using bivariate VAR-GARCH-BEKK model. The authors believe that the results of this research’s empirical analysis would amplify the systematic understanding of spillover activities between China stock market and other stock markets.

This paper represents an analysis of the spillover effects and time-frequency connectedness between crude oil prices and agricultural commodity markets using both the spillover index of Diebold and Yilmaz (2012) and the wavelet coherence model to evaluate whether the time-varying return spillover index exhibited the intensity and direction of transmission during the Covid-19 outbreak. Overall, the current results shed light on that in comparison with the pre-Covid-19 period, and the return spillover is more apparent during the Covid-19 crisis. However, levels of the intensity of this relationship vary through the period of research, with several intervals witnessing both negative and positive interactions. Further, our findings indicate significant heterogeneity among agriculture commodity markets in the degree of spillover to crude oil prices over time, amplifying our understanding of the economic channels through which the agriculture commodity markets are correlated. More importantly, there exist significant dependent patterns about the information spillovers across the crude oil and agriculture commodity markets might provide prominent implications for portfolio managers, investors, and government agencies.

This study explores the connectedness between cryptocurrencies (Bitcoin, Ethereum, Ripple, Bitcoin cash and Ethereum Operating System) and major stock markets (NYSE composite index, NASDAQ composite index, Shanghai Stock Exchange, Nikkei 225 and Euronext NV). Using the asymmetric dynamic conditional correlation (ADCC) and wavelet coherence approaches, we document a significant time-varying conditional correlation between the majority of the cryptocurrencies and stock market indices and that the negative shocks play a more prominent role than the positive shocks of the same magnitude. Overall, our findings explore potential avenues for diversification for investors across cryptocurrencies and major stock markets.

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