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Predicting daily exchange rate with singular spectrum analysis

Hassani, Hossein, Soofi, Abdol and Zhigljavsky, Anatoly Alexandrovich ORCID: https://orcid.org/0000-0003-0630-8279 2010. Predicting daily exchange rate with singular spectrum analysis. Nonlinear Analysis: Real World Applications 11 (3) , pp. 2023-2034. 10.1016/j.nonrwa.2009.05.008

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Abstract

This paper uses univariate and multivariate singular spectrum analysis for predicting the value and the direction of changes in the daily pound/dollar exchange rate. In prediction of daily pound/dollar rate, we use the rescaled and bootstrapped daily euro/dollar rate as a guidepost for the singular spectrum analysis method. We use the random walk model as a benchmark to evaluate performances of the singular spectrum analysis as a prediction method. Empirical results show that the forecast based on the multivariate singular spectrum analysis compares favorably to the forecast of the random walk model both for predicting the value and the direction of changes in the daily pound/dollar exchange rate. We compared the prediction results based on an error correction model in the context of a restricted vector autoregressive model and compared them with the prediction results by a random walk as well as by those of singular spectrum and multiple singular spectrum models and found that the VEC results are inferior.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Mathematics
Subjects: Q Science > QA Mathematics
Uncontrolled Keywords: Singular spectrum analysis; Forecasting exchange rate; Random walk model; VAR; Diebold–Mariano test statistic
Publisher: Elsevier
ISSN: 1468-1218
Last Modified: 18 Oct 2022 13:44
URI: https://orca.cardiff.ac.uk/id/eprint/15153

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