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Monitoring multivariate variance changes

Listed author(s):
  • Pape, Katharina
  • Wied, Dominik
  • Galeano, Pedro

We propose a model-independent multivariate sequential procedure to monitor changes in the vector of componentwise unconditional variances in a sequence of p-variate random vectors. The asymptotic behavior of the detector is derived and consistency of the procedure stated. A detailed simulation study illustrates the performance of the procedure confronted with different types of data generating processes. We conclude with an application to the log returns of a group of DAX listed assets.

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File URL: http://www.sciencedirect.com/science/article/pii/S0927539816301098
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Article provided by Elsevier in its journal Journal of Empirical Finance.

Volume (Year): 39 (2016)
Issue (Month): PA ()
Pages: 54-68

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Handle: RePEc:eee:empfin:v:39:y:2016:i:pa:p:54-68
DOI: 10.1016/j.jempfin.2016.08.007
Contact details of provider: Web page: http://www.elsevier.com/locate/jempfin

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