Examining the contemporaneous causality between Chinese and Ghanaian stock markets before and amidst the coronavirus disease 2019 (COVID-19) pandemic is of immense interest to many stakeholders in making effective and efficient decisions. This study investigates why the two stock markets’ fluctuations seem to move in tandem despite a broader economic phenomenon. Shanghai Stock Exchange and Ghanaian Stock Exchange composite indices data were used for this study spanning 2011-2020. The Granger causality and transfer entropy are applied to investigate the mean transmission. The Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH) model portrays the dynamic correlation and the ARMA model is used to fit the log-returns of the two indices. Results show that the Chinese stock market has a substantial causal effect on the Ghanaian stock market based on transfer entropy with the second order of lag while there is a considerable causality from the stock market of Ghana to the Chinese stock market through the third and fifth orders of lags. This implies the asynchronous return transmission between Chinese and Ghanaian stock markets. Moreover, the long term volatility connection significantly impacts the two markets, but the short-term volatility pattern does not heavily affect the markets based on the DCC-GARCH model. The best-fitted model for the log returns of two stock markets is ARMA (1,1). This study recommends that policymakers and investors adopt diversification as a resort to financial management.