Prediction in locally stationary time series

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Date

2 janvier 2020

Type de document
Périmètre
Identifiant
  • 2001.00419
Collection

arXiv

Organisation

Cornell University




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Holger Dette et al., « Prediction in locally stationary time series », arXiv - économie


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Résumé 0

We develop an estimator for the high-dimensional covariance matrix of a locally stationary process with a smoothly varying trend and use this statistic to derive consistent predictors in non-stationary time series. In contrast to the currently available methods for this problem the predictor developed here does not rely on fitting an autoregressive model and does not require a vanishing trend. The finite sample properties of the new methodology are illustrated by means of a simulation study and a financial indices study.

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