{"title":"历史背景对未来影响的预测:对赞比亚银行业数据的广泛研究","authors":"Chresta C Kaluba","doi":"10.59413/eafj/v3.i2.1","DOIUrl":null,"url":null,"abstract":"This article looks at using historical data to predict future performance in the banking sector. By examining deposits, loans and advances, total assets and earnings data of four banks over an eight-year period, this study shows the practicality of using past data to predict future trends. By applying regression analysis, the study shows that models developed based on historical data can serve as valuable tools for decision making and scenario planning focused on the future in the banking sector. The article examines the accuracy of forecasts through a detailed analysis using the Normalized Root Mean Squared Error (NRMSE). It is shown that using predicted values can produce results that are almost as accurate as using actual future data, supporting the notion that historical data can be a reliable indicator of future trends.","PeriodicalId":330424,"journal":{"name":"East African Finance Journal","volume":"18 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Historical Context as a Predictor of Future Effects: A Broad Examination of Banking Data in Zambia\",\"authors\":\"Chresta C Kaluba\",\"doi\":\"10.59413/eafj/v3.i2.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article looks at using historical data to predict future performance in the banking sector. By examining deposits, loans and advances, total assets and earnings data of four banks over an eight-year period, this study shows the practicality of using past data to predict future trends. By applying regression analysis, the study shows that models developed based on historical data can serve as valuable tools for decision making and scenario planning focused on the future in the banking sector. The article examines the accuracy of forecasts through a detailed analysis using the Normalized Root Mean Squared Error (NRMSE). It is shown that using predicted values can produce results that are almost as accurate as using actual future data, supporting the notion that historical data can be a reliable indicator of future trends.\",\"PeriodicalId\":330424,\"journal\":{\"name\":\"East African Finance Journal\",\"volume\":\"18 4\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-28\",\"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.i2.1\",\"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.i2.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Historical Context as a Predictor of Future Effects: A Broad Examination of Banking Data in Zambia
This article looks at using historical data to predict future performance in the banking sector. By examining deposits, loans and advances, total assets and earnings data of four banks over an eight-year period, this study shows the practicality of using past data to predict future trends. By applying regression analysis, the study shows that models developed based on historical data can serve as valuable tools for decision making and scenario planning focused on the future in the banking sector. The article examines the accuracy of forecasts through a detailed analysis using the Normalized Root Mean Squared Error (NRMSE). It is shown that using predicted values can produce results that are almost as accurate as using actual future data, supporting the notion that historical data can be a reliable indicator of future trends.