Psaradakis, Zacharias and Vávra, Marian (2022) Using Triples to assess symmetry under weak dependence. Journal of Business and Economic Statistics 40 (4), pp. 1538-1551. ISSN 0735-0015.
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Abstract
The problem of assessing symmetry about an unspecified center of the one-dimensional marginal distribution of a strictly stationary random process is considered. A well-known U-statistic based on data triples is used to detect deviations from symmetry, allowing the underlying process to satisfy suitable mixing or near-epoch dependence conditions. We suggest using subsampling for inference on the target parameter, establish the asymptotic validity of the method in our setting, and discuss data-driven rules for selecting the size of subsamples. The small-sample properties of the proposed inferential procedures are examined by means of Monte Carlo simulations. Applications to time series of output growth and stock returns are also presented.
Metadata
| Item Type: | Article |
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| Additional Information: | This is an Accepted Manuscript of an article published by Taylor & Francis, available online at the link above. |
| School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
| Depositing User: | Zacharias Psaradakis |
| Date Deposited: | 03 Jun 2021 08:43 |
| Last Modified: | 18 Jan 2024 11:56 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/44573 |
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