Abstract
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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References
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Acknowledgements
I am grateful to Guy Nason for reading a preliminary version of the manuscript and for providing useful comments. All errors are my own responsibility.
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Cardinali, A. (2014). Local Covariance Estimation Using Costationarity. In: Akritas, M., Lahiri, S., Politis, D. (eds) Topics in Nonparametric Statistics. Springer Proceedings in Mathematics & Statistics, vol 74. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0569-0_6
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DOI: https://doi.org/10.1007/978-1-4939-0569-0_6
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