Hassani, Hossein, Xu, Zhengyuan and Zhigljavsky, Anatoly Alexandrovich ORCID: https://orcid.org/0000-0003-0630-8279 2011. Singular spectrum analysis based on the perturbation theory. Nonlinear Analysis: Real World Applications 12 (5) , pp. 2752-2766. 10.1016/j.nonrwa.2011.03.020 |
Abstract
Singular Spectrum Analysis (SSA) has been exploited in different applications. It is well known that perturbations from various sources can seriously degrade the performance of the methods and techniques. In this paper, we consider the SSA technique based on the perturbation theory and examine its performance in both reconstructing and forecasting noisy series. We also consider the sensitivity of the technique to different window lengths, noise levels and series lengths. To cover a broad application range, various simulated series, from dynamic to chaotic, are used to verify the proposed algorithm. We then evaluate the performance of the technique using two real well-known series, namely, monthly accidental deaths in the USA, and the daily closing prices of several stock market indices. The results are compared with several classical methods namely, Box–Jenkins SARIMA models, the ARAR algorithm, GARCH model and the Holt–Winter algorithm.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Mathematics |
Subjects: | Q Science > QA Mathematics |
Uncontrolled Keywords: | Singular spectrum analysis; Perturbation theory; Reconstruction; Forecasting |
Publisher: | Elsevier |
ISSN: | 1468-1218 |
Last Modified: | 18 Oct 2022 13:02 |
URI: | https://orca.cardiff.ac.uk/id/eprint/12146 |
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