Authors: Ditzhaus, Marc
Gaigall, Daniel
Title: Testing marginal homogeneity in Hilbert spaces with applications to stock market returns
Language (ISO): en
Abstract: 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.
Subject Headings: Marginal homogeneity
Functional data
Bootstrap test
Cramér–von-Mises test
Stock market return
Issue Date: 2022-02-14
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Appears in Collections:Institut für Mathematische Statistik und industrielle Anwendungen

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