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In this paper we propose a novel estimator for the time-varying covariance of locally stationary time series. This new approach is based on costationary combinations, that is, time-varying deterministic combinations of locally stationary time series that are second-order stationary. We show with a simulation example that the new estimator has smaller variance than other approaches exclusively based on the evolutionary cross-periodogram, and can therefore be appealing in a large number of applications.
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