Ricerc@Sapienza

This paper examines the volatility transmission from energy and metal commodities to six major African exporters’ stock markets (Egypt for oil and gold, Nigeria for oil and gas, South Africa for coal and gold, Tunisia for oil, Uganda for gold and Zambia for copper). Modelling commodity volatility with the Double Asymmetric GARCH-MIDAS model with a Student’s t-distribution allows to detect the presence of impact and inertial stock market volatility spillovers at different lags and to take into account the leptokurtosis of the commodity series.

Volatility in financial markets has both low and high–frequency components which determine its dynamic evolution. Previous modelling efforts in the GARCH context (e.g. the Spline–GARCH) were aimed at estimating the low frequency component as a smooth function of time around which short–term dynamics evolves. Alternatively, recent literature has introduced the possibility of considering