Monitoring multivariate variance changes
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Date
2015
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Abstract
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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Table of contents
Keywords
multivariate sequences, variance changes, threshold function, online detection