Forecasting European industrial production with singular spectrum analysis

Hassani, Hossein, Heravi, Saeed ORCID: https://orcid.org/0000-0002-0198-764X and Zhigljavsky, Anatoly Alexandrovich ORCID: https://orcid.org/0000-0003-0630-8279 2009. Forecasting European industrial production with singular spectrum analysis. International Journal of Forecasting 25 (1) , pp. 103-118. 10.1016/j.ijforecast.2008.09.007

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Abstract

In this paper, the performance of the Singular Spectrum Analysis (SSA) technique is assessed by applying it to 24 series measuring the monthly seasonally unadjusted industrial production for important sectors of the German, French and UK economies. The results are compared with those obtained using the Holt–Winters’ and ARIMA models. All three methods perform similarly in short-term forecasting and in predicting the direction of change (DC). However, at longer horizons, SSA significantly outperforms the ARIMA and Holt–Winters’ methods.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics) Mathematics
Subjects:	H Social Sciences > HB Economic Theory Q Science > QA Mathematics
Uncontrolled Keywords:	Singular spectrum analysis; ARIMA; Holt–Winters’ method; Forecasting; European industrial production series
Publisher:	Elsevier
ISSN:	0169-2070
Last Modified:	18 Oct 2022 13:02
URI:	https://orca.cardiff.ac.uk/id/eprint/12147

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