Testing marginal homogeneity in Hilbert spaces with applications to stock market returns
- This paper considers a paired data framework and discusses the question of marginal homogeneity of bivariate high-dimensional or functional data. The related testing problem can be endowed into a more general setting for paired random variables taking values in a general Hilbert space. To address this problem, a Cramér–von-Mises type test statistic is applied and a bootstrap procedure is suggested to obtain critical values and finally a consistent test. The desired properties of a bootstrap test can be derived that are asymptotic exactness under the null hypothesis and consistency under alternatives. Simulations show the quality of the test in the finite sample case. A possible application is the comparison of two possibly dependent stock market returns based on functional data. The approach is demonstrated based on historical data for different stock market indices.
| Verfasserangaben: | Marc Ditzhaus, Daniel Gaigall |
|---|---|
| DOI: | https://doi.org/10.1007/s11749-022-00802-5 |
| ISSN: | 1863-8260 |
| Titel des übergeordneten Werkes (Englisch): | Test |
| Verlag: | Springer |
| Dokumentart: | Wissenschaftlicher Artikel |
| Sprache: | Englisch |
| Erscheinungsjahr: | 2022 |
| Datum der Erstveröffentlichung: | 14.02.2022 |
| Datum der Publikation (Server): | 16.01.2023 |
| Jahrgang: | 2022 |
| Ausgabe / Heft: | 31 |
| Erste Seite: | 749 |
| Letzte Seite: | 770 |
| Link: | https://doi.org/10.1007/s11749-022-00802-5 |
| Zugriffsart: | weltweit |
| Fachbereiche und Einrichtungen: | FH Aachen / Fachbereich Medizintechnik und Technomathematik |
| collections: | Verlag / Springer |
| Open Access / Hybrid |
