K-th Moving, Weighted and Exponential Moving Average for Time Series Forecasting Models
Keywords:
Time series, ARIMA, k-th moving average, k-th weighted moving average, k-th exponential weighted moving average processAbstract
The objective of the present study is to investigate the effectiveness of developing a forecasting model of a given nonstationary economic realization using a k-th moving average, a k-th weighted moving average and a k-th exponential weighted moving average process. We create a new nonstationary time series from the original realization using the three different weighted methods. Using real economic data we formulate the best ARIMA model and compare short term forecasting results of the three proposed models with that of the classical ARIMA model.Downloads
Published
2010-05-22
Issue
Section
Special Issue on Granger Econometrics and Statistical Modeling
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European Journal of Pure and Applied Mathematics will be Copyright Holder.
How to Cite
K-th Moving, Weighted and Exponential Moving Average for Time Series Forecasting Models. (2010). European Journal of Pure and Applied Mathematics, 3(3), 406-416. https://ejpam.com/index.php/ejpam/article/view/633