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This study examines the integration of historical data in forecasting future outcomes, focusing on the banking sector in Zambia. The study analyzes data for five banks in Zambia from January 2010 to December 2020 and examines the accuracy of forecasts for key financial variables such as total assets, loans and advances, deposits, revenue and profit after tax. Using regression analysis, the study develops forecast models that are calibrated with historical data from 2010 to 2017. The accuracy of these forecasts is assessed using normalized root mean square error (RMSE), which provides a standardized metric for evaluation. The study highlights that historical data serves as a reliable predictor of future outcomes and demonstrates the effectiveness of forecasting techniques in projecting past trends into the future. Consequently, decisions based on these forecasts can provide a sufficiently accurate indication of future scenarios in the Zambian banking sector.
Chresta C. Kaluba (Thu,) studied this question.