Monitoring the cross-covariances of a multivariate time series

Przemyslaw Sliwa and Wolfgang Schmid ()

Metrika: International Journal for Theoretical and Applied Statistics, 2005, vol. 61, issue 1, 89-115

Abstract: In this paper sequential procedures are proposed for jointly monitoring all elements of the covariance matrix at lag 0 of a multivariate time series. All control charts are based on exponential smoothing. As a measure of the distance between the target values and the actual values the Mahalanobis distance is used. It is distinguished between residual control schemes and modified control schemes. Several properties of these charts are proved assuming the target process to be a stationary Gaussian process. Within an extensive Monte Carlo study all procedures are compared with each other. As a measure of the performance of a control chart the average run length is used. An empirical example about Eastern European stock markets illustrates how the autocovariance and the cross-covariance structure of financial assets can be monitored by these methods. Copyright Springer-Verlag 2005

Keywords: Statistical process control; Multivariate time series; Simultaneous control charts; Exponential smoothing; Financial application (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:metrik:v:61:y:2005:i:1:p:89-115

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DOI: 10.1007/s001840400326

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