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Suitability of Simple Forecasting Techniques for Predicting the Performance of Banks in the Zambian Financial Industry

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  • Chresta C Kaluba

    (University of Zambia)

Abstract

The aim of this article is to examine the suitability of simple forecasting techniques and identify the most effective forecasting technique for predicting the performance of banks in the Zambian financial industry. The study uses various forecasting techniques using Zambian bank financial data from 2010 to 2016 and produces forecasts for the years 2017 to 2021. The accuracy of these forecasts is then compared with the actual performance during the two years and the technique that produces the closest results, is selected based on the actual results is considered the most appropriate forecasting technique. The study found that linear regression not only produces results that are closest to actual values, but is also sufficiently precise for informed decision making.

Suggested Citation

  • Chresta C Kaluba, 2024. "Suitability of Simple Forecasting Techniques for Predicting the Performance of Banks in the Zambian Financial Industry," East African Finance Journal, East African Finance Journal, vol. 3(1).
  • Handle: RePEc:cwk:eafjke:2024-06
    DOI: 10.59413/eafj/v3.i1.6
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    References listed on IDEAS

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    1. Girma Gudde Jote, 2023. "Financial Innovation and Its Effects on Bank Financial Performance: Evidence from Ethiopian Commercial Banks," African Journal of Commercial Studies, African Journal of Commercial Studies, vol. 3(1).
    2. Kalchschmidt, Matteo & Zotteri, Giulio & Verganti, Roberto, 2003. "Inventory management in a multi-echelon spare parts supply chain," International Journal of Production Economics, Elsevier, vol. 81(1), pages 397-413, January.
    3. Lucjan Kurzak, 2012. "Importance Of Forecasting In Enterprise Management," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 6(1), pages 173-182, December.
    4. Danese, Pamela & Kalchschmidt, Matteo, 2011. "The role of the forecasting process in improving forecast accuracy and operational performance," International Journal of Production Economics, Elsevier, vol. 131(1), pages 204-214, May.
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