Modified Holt's Linear Trend Method

YAPAR G., ÇAPAR S., TAYLAN SELAMLAR H., YAVUZ İ.

HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, vol.47, no.5, pp.1394-1403, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 47 Issue: 5
  • Publication Date: 2018
  • Doi Number: 10.15672/hjms.2017.493
  • Journal Name: HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.1394-1403
  • Keywords: Exponential smoothing, Forecasting, Initial value, M3-Competition, Smoothing parameter, TIME-SERIES, STATE, ACCURACY, ART
  • Dokuz Eylül University Affiliated: Yes

Abstract

Exponential smoothing models are simple, accurate and robust forecasting models and because of these they are widely applied in the literature. Holt's linear trend method is a valuable extension of exponential smoothing that helps deal with trending data. In this study we propose a modified version of Holt's linear trend method that eliminates the initialization issue faced when fitting the original model and simplifies the optimization process. The proposed method is compared empirically with the most popular forecasting algorithms based on exponential smoothing and Box-Jenkins ARIMA with respect to its predictive performance on the M3-Competition data set and is shown to outperform its competitors.