On the Impact of Outliers in Time Series Analysis (A Case Study of NPA Generated Revenue)

A.E. Uduma¹ , O.R. Uwaeme²

Section:Research Paper, Product Type: Journal-Paper
Vol.6 , Issue.5 , pp.68-75, Oct-2019

Online published on Oct 31, 2019

Copyright © A.E. Uduma, O.R. Uwaeme . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Detection of outliers in time series analysis has turned out to be a very essential subject matter. The objective of this study is to compare the forecast of a time series data with outlier and without outliers using the forecast evaluation criterion in order to examine the impact of outliers in model building. The study therefore examined the monthly NPA revenue generated series from 2002 to 2014. The Bartlett’s power transformation technique was employed. Outlier detection methods were initiated which detected outliers in the series. The series were then divided into two (with and without outlier). The Box and Jenkins technique was employed for model building. The results indicated that the forecast of the treated transformed series without outliers produced a perfect fit for the NPA revenue generated series

Key-Words / Index Term :
Outliers, Bartlett’s power Transformation, Box and Jenkins technique

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