Prediction in locally stationary time series

• Tác giả: Holger Dette, Weichi Wu
• Ngôn ngữ: eng
• Ký hiệu phân loại: 551.63 Weather forecasting and forecasts, reporting and reports
• Thông tin xuất bản: 2020
• Bộ sưu tập: Metadata
• ID: 163782

Tóm tắt

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.