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Goodness-of-fit tests for centralized Wishart processes
Stockholm University, Faculty of Science, Department of Mathematics.
Stockholm University, Faculty of Science, Department of Mathematics.
Stockholm University, Faculty of Science, Department of Mathematics.
Number of Authors: 32019 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415XArticle in journal (Refereed) Epub ahead of print
Abstract [en]

In this paper we present several goodness-of-fit tests for the centralized Wishart process, a popular matrix-variate time series model used to capture the stochastic properties of realized covariance matrices. The new test procedures are based on the extended Bartlett decomposition derived from the properties of the Wishart distribution and allows to obtain sets of independently and standard normally distributed random variables under the null hypothesis. Several tests for normality and independence are then applied to these variables in order to support or to reject the underlying assumption of a centralized Wishart process. In order to investigate the influence of estimated parameters on the suggested testing procedures in the finite-sample case, a simulation study is conducted. Finally, the new test methods are applied to real data consisting of realized covariance matrices computed for the returns on six assets traded on the New York Stock Exchange.

Place, publisher, year, edition, pages
2019.
Keywords [en]
Wishart autoregressive process, goodness-of-fit test, Bartlett decomposition, Wishart distribution, parameter uncertainty
National Category
Mathematics
Identifiers
URN: urn:nbn:se:su:diva-170027DOI: 10.1080/03610926.2019.1612917ISI: 000469549600001OAI: oai:DiVA.org:su-170027DiVA, id: diva2:1329234
Available from: 2019-06-24 Created: 2019-06-24 Last updated: 2019-08-15

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Alfelt, GustavBodnar, TarasTyrcha, Joanna
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