Prediction of Stock Performance on the Ghana Stock Exchange Using Financial Ratios: A Logistic Regression Approach

This paper examines the efficacy of financial ratios as predictors of stock performances of 20 selected companies listed on the Ghana Stock Exchange Composite Index (GSE-CI) over a three year period. Stock portfolio selection is one of the biggest challenges faced by market players when investing on the stock exchange. This study uses binary logistic regression with various financial ratios  as the explanatory variables  to investigate  indicators  that  significantly  influence  the performance  of  stocks  actively  traded  on  the  Ghana Stock Exchange-Composite Index (GSE-CI). Potential performance of a stock on the Exchange is invaluable information to an investor. The study showed that using financial ratios, companies’ annual performance on the GSE-CI can be predicted with a 70% level of accuracy into two categories – “good” or “poor” – based on whether or not that particular company outperforms the GSE-CI. This paper maintains that the model developed can enhance the stock performance forecasting ability of investors