Astill, S and Harvey, DI and Taylor, AMR (2013) A bootstrap test for additive outliers in non-stationary time series. Journal of Time Series Analysis, 34 (4). pp. 454-465. DOI https://doi.org/10.1111/jtsa.12033
Astill, S and Harvey, DI and Taylor, AMR (2013) A bootstrap test for additive outliers in non-stationary time series. Journal of Time Series Analysis, 34 (4). pp. 454-465. DOI https://doi.org/10.1111/jtsa.12033
Astill, S and Harvey, DI and Taylor, AMR (2013) A bootstrap test for additive outliers in non-stationary time series. Journal of Time Series Analysis, 34 (4). pp. 454-465. DOI https://doi.org/10.1111/jtsa.12033
Abstract
<jats:p>In this paper we propose a new procedure for detecting additive outliers in a univariate time series based on a bootstrap implementation of the test of Perron and Rodríguez (2003,<jats:italic>Journal of Time Series Analysis</jats:italic>24, 193‐220). This procedure is used to test the null hypothesis that a time series is uncontaminated by additive outliers against the alternative that one or more additive outliers are present. We demonstrate that the existing tests of,<jats:italic>inter alia</jats:italic>, Vogelsang (1999,<jats:italic>Journal of Time Series Analysis</jats:italic>20, 237–52) Perron and Rodríguez (2003) and Burridge and Taylor (2006,<jats:italic>Journal of Time Series Analysis</jats:italic>27, 685–701) are unable to strike a balance between size and power when the order of integration of a time series is unknown and the time series is driven by innovations drawn from an unknown distribution. We show that the proposed bootstrap testing procedure is able to control size to such an extent that its size properties are comparable with the robust test of Burridge and Taylor (2006) when the distribution of the innovations is not assumed known, whilst maintaining power in the Gaussian environment close to that of the test of Perron and Rodríguez (2003).</jats:p>
Item Type: | Article |
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Uncontrolled Keywords: | Additive outliers; t-test; bootstrap |
Subjects: | H Social Sciences > HG Finance |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 12 Nov 2014 12:03 |
Last Modified: | 22 May 2024 05:42 |
URI: | http://repository.essex.ac.uk/id/eprint/11253 |