The Future of African Financial Markets : Modelling in Traditional and Machine Learning Techniques

The opportunities, prospects and challenges of Africa is frequently been trumpeted by several scholars and experts. This study examines African Financial Markets using both traditional modelling techniques and machine learning tools. We selected proxy countries based on the macroeconomic factors and stock markets analyzed. The study revealed that even though traditional modelling can be used for modelling time series, it can significantly be improve by machine learning tools. The results show that Africa stock markets are profitably but have some underlying risk that is linked to the economy of the African economies. We highlight the weakness in the macroeconomic factors such as weakness in managing inflation, high borrowing rate, increased interests rate as well as slow growth in FDI and GDP. We recommend swift policy measures to deal with these weaknesses