University of Illinois Urbana-Champaign

Optimizing smoothing parameters for the triple exponential forecasting model

Narasingaraj, Harish Balaji

Content Files
NARASINGARAJ-THESIS-2016.pdf

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https://hdl.handle.net/2142/90834

Description

Title
Optimizing smoothing parameters for the triple exponential forecasting model
Author(s)
Narasingaraj, Harish Balaji
Issue Date
2016-04-26
Director of Research (if dissertation) or Advisor (if thesis)
Nagi, Rakesh
Department of Study
Industrial&Enterprise Sys Eng
Discipline
Industrial Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2016-07-07T20:35:18Z
Keyword(s)
  • Holt Winters
  • Triple Exponential Smoothing parameters
  • M3 Competition
Abstract
Exponential smoothing has always been a popular topic of research in forecasting. The triple exponential smoothing in particular involves modeling a function that is a combination of level, trend and seasonal factors. While simulating the model, each of the factors is associated with a parameter whose value has a significant impact on the accuracy of the forecast, yet optimizing these parameters for a time series has received relatively little attention in literature. In this thesis we will explore the results of multi-step forecasting by using parameters optimized through an algorithm centered around h-step ahead errors. An empirical study conducted on forecasting the monthly time series from the M3-Competition across a range of horizons gave us promising results. We show that this method proves to be better than the standard Holt-Winters procedure for the entire forecasting horizon in five out the six categories of data considered . We also show that this method significantly improves the accuracy over the short term forecasting horizon when compared to the automated Holt-Winters procedure used by experts in the M3 competition. Encouraged by these results, we recommend replicating this methodology to other models of the triple exponential smoothing in the future.
Graduation Semester
2016-05
Type of Resource
text
Permalink
http://hdl.handle.net/2142/90834
Copyright and License Information
Copyright 2016 Harish B Narasingaraj

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