arXiv 2 Jan 2020 · Statistics — Methodology · publishedJournal of Business and Economic Statistics (2020)
arXiv:2001.00419 · PDF · DOI · OpenAlex · Extracted main text
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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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Kley, T., Preuss, P., and Fryzlewicz, P (2019) Predictive, finite-sample model choice for time series under stationarity and non-stationarity | 1.000 | 13 | 3 | 100% |
| 2 | Roueff, F. and Sanchez-Perez, A (2018) Prediction of weakly locally stationary processes by auto-regression | 1.000 | 9 | 3 | 100% |
| 3 | McMurry, T. L. and Politis, D. N (2010) Banded and tapered estimates for autocovariance matrices and the linear process bootstrap | 0.928 | 5 | 4 | 80% |
| 4 | McMurry, T. L., Politis, D. N., et al (2015) High-dimensional autocovariance matrices and optimal linear prediction | 0.928 | 4 | 3 | 100% |
| 5 | Starica, C. and Granger, C (2005) Nonstationarities in stock returns | 0.928 | 4 | 3 | 100% |
| 6 | Wu, W. B. and Pourahmadi, M (2009) Banding sample autocovariance matrices of stationary processes self | 0.928 | 4 | 3 | 100% |
| 7 | Zhou, Z. and Wu, W. B (2009) Local linear quantile estimation for nonstationary time series self | 0.737 | 3 | 2 | 100% |
| 8 | Giraud, C., Roueff, F., and Sanchez-Perez, A (2015) Aggregation of predictors for nonstationary sub-linear processes and online adaptive forecasting of time varying autoregressive… | 0.693 | 7 | 1 | 100% |
| 9 | Dahlhaus, R (1997) Fitting time series models to nonstationary processes | 0.644 | 2 | 2 | 100% |
| 10 | Guillaumin, A. P., Sykulski, A. M., Olhede, S. C., Early, J. J., and… (2017) Analysis of non-stationary modulated time series with applications to oceanographic surface flow measurements | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 33 scored citations.