{"title":"预测赞比亚金融业银行业绩的简单预测技术的适用性","authors":"Chresta C Kaluba","doi":"10.59413/eafj/v3.i1.6","DOIUrl":null,"url":null,"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.","PeriodicalId":330424,"journal":{"name":"East African Finance Journal","volume":"12 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Suitability of Simple Forecasting Techniques for Predicting the Performance of Banks in the Zambian Financial Industry\",\"authors\":\"Chresta C Kaluba\",\"doi\":\"10.59413/eafj/v3.i1.6\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":330424,\"journal\":{\"name\":\"East African Finance Journal\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"East African Finance Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.59413/eafj/v3.i1.6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"East African Finance Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.59413/eafj/v3.i1.6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Suitability of Simple Forecasting Techniques for Predicting the Performance of Banks in the Zambian Financial Industry
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.