A New Approach to Glaciochemical Time Series Analysis

Abstract

In the study of time series, new technique for smoothing the data is very important and evolving. This study presents a new technique for smoothing time series data. It is based on average and works in the time domain. It is aimed at creating a new series by redistributing the average of the reduced (halved) series of the variable of interest; it has the potential of reducing large peak. In this work, simulated stock data (S&P 500 quarterly stock value for 2005:1 – 2014:4)) will be smoothed and residual analysis carried out to determined the performance of the technique. From the application of the technique, amongst other findings, the residual ɛt from the technique was found to be white noise, which is the building block for time series models