Using the Bootstrap to test for symmetry under unknown dependence
Psaradakis, Zacharias (2015) Using the Bootstrap to test for symmetry under unknown dependence. Journal of Business and Economic Statistics 34 (3), pp. 406-415. ISSN 0735-0015.
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Abstract
This paper considers tests for symmetry of the one-dimensional marginal distribution of fractionally integrated processes. The tests are implemented by using an autoregressive sieve bootstrap approximation to the null sampling distribution of the relevant test statistics. The sieve bootstrap allows inference on symmetry to be carried out without knowledge of either the memory parameter of the data or of the appropriate norming factor for the test statistic and its asymptotic distribution. The small-sample properties of the proposed method are examined by means of Monte Carlo experiments, and applications to real-world data are also presented.
Metadata
| Item Type: | Article |
|---|---|
| Additional Information: | This is an Accepted Manuscript of an article published by Taylor & Francis, available online: http://wwww.tandfonline.com/10.1080/07350015.2015.1043368 |
| School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
| Depositing User: | Zacharias Psaradakis |
| Date Deposited: | 27 Nov 2015 13:45 |
| Last Modified: | 02 Aug 2023 17:17 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/12370 |
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