Testing for (in)finite moments
This paper proposes a test to verify whether the th moment of a random variable is finite. We use the fact that, under general assumptions, sample moments either converge to a finite number or diverge to infinity according as the corresponding population moment is finite or not. Building on this, we...
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| Format: | Article |
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Elsevier
2016
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| Online Access: | https://eprints.nottingham.ac.uk/46950/ |
| _version_ | 1848797435184283648 |
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| author | Trapani, Lorenzo |
| author_facet | Trapani, Lorenzo |
| author_sort | Trapani, Lorenzo |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This paper proposes a test to verify whether the th moment of a random variable is finite. We use the fact that, under general assumptions, sample moments either converge to a finite number or diverge to infinity according as the corresponding population moment is finite or not. Building on this, we propose a test for the null that the th moment does not exist. Since, by construction, our test statistic diverges under the null and converges under the alternative, we propose a randomised testing procedure to discern between the two cases. We study the application of the test to raw data, and to regression residuals. Monte Carlo evidence shows that the test has the correct size and good power; the results are further illustrated through an application to financial data. |
| first_indexed | 2025-11-14T20:03:50Z |
| format | Article |
| id | nottingham-46950 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:03:50Z |
| publishDate | 2016 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-469502020-05-04T20:03:54Z https://eprints.nottingham.ac.uk/46950/ Testing for (in)finite moments Trapani, Lorenzo This paper proposes a test to verify whether the th moment of a random variable is finite. We use the fact that, under general assumptions, sample moments either converge to a finite number or diverge to infinity according as the corresponding population moment is finite or not. Building on this, we propose a test for the null that the th moment does not exist. Since, by construction, our test statistic diverges under the null and converges under the alternative, we propose a randomised testing procedure to discern between the two cases. We study the application of the test to raw data, and to regression residuals. Monte Carlo evidence shows that the test has the correct size and good power; the results are further illustrated through an application to financial data. Elsevier 2016-03 Article PeerReviewed Trapani, Lorenzo (2016) Testing for (in)finite moments. Journal of Econometrics, 191 (1). pp. 57-68. ISSN 0304-4076 Finite moments; Randomised tests; Chover-type Law of the Iterated Logarithm; Strong Law of Large Numbers http://www.sciencedirect.com/science/article/pii/S0304407615002596 doi:10.1016/j.jeconom.2015.08.006 doi:10.1016/j.jeconom.2015.08.006 |
| spellingShingle | Finite moments; Randomised tests; Chover-type Law of the Iterated Logarithm; Strong Law of Large Numbers Trapani, Lorenzo Testing for (in)finite moments |
| title | Testing for (in)finite moments |
| title_full | Testing for (in)finite moments |
| title_fullStr | Testing for (in)finite moments |
| title_full_unstemmed | Testing for (in)finite moments |
| title_short | Testing for (in)finite moments |
| title_sort | testing for (in)finite moments |
| topic | Finite moments; Randomised tests; Chover-type Law of the Iterated Logarithm; Strong Law of Large Numbers |
| url | https://eprints.nottingham.ac.uk/46950/ https://eprints.nottingham.ac.uk/46950/ https://eprints.nottingham.ac.uk/46950/ |