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.
Author: | Marc Ditzhaus, Daniel Gaigall |
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DOI: | https://doi.org/10.1007/s11749-022-00802-5 |
ISSN: | 1863-8260 |
Parent Title (English): | Test |
Publisher: | Springer |
Document Type: | Article |
Language: | English |
Year of Completion: | 2022 |
Date of first Publication: | 2022/02/14 |
Volume: | 2022 |
Issue: | 31 |
First Page: | 749 |
Last Page: | 770 |
Link: | https://doi.org/10.1007/s11749-022-00802-5 |
Zugriffsart: | weltweit |
Institutes: | FH Aachen / Fachbereich Medizintechnik und Technomathematik |
collections: | Verlag / Springer |
Open Access / Hybrid |