arXiv · 2001.00419
Prediction in locally stationary time series
Abstract
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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Holger Dette, Weichi Wu. 2020-01-04. Prediction in locally stationary time series. https://arxiv.org/abs/2001.00419
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