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Change point detection with multivariate observations based on characteristic functions. (English) Zbl 06854744
Ferger, Dietmar (ed.) et al., From statistics to mathematical finance. Festschrift in honour of Winfried Stute. Cham: Springer (ISBN 978-3-319-50985-3/hbk; 978-3-319-50986-0/ebook). 273-290 (2017).
Summary: We consider break-detection procedures for vector observations, both under independence as well as under an underlying structural time series scenario. The new methods involve L2-type criteria based on empirical characteristic functions. Asymptotic as well as Monte-Carlo results are presented. The new methods are also applied to time-series data from the financial sector.
For the entire collection see [Zbl 1383.62010].
MSC:
62M07 Non-Markovian processes: hypothesis testing
62H15 Hypothesis testing in multivariate analysis
62P05 Applications of statistics to actuarial sciences and financial mathematics
Software:
mvtnorm
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