Bouezmarni, Taoufik and Van Bellegem, Sebastien and Rabhi, Yassir (2020) Nonparametric Beta Kernel Estimator for Long and Short Memory Time Series. The Canadian Journal of Statistics, 48 (3). pp. 582-595. DOI https://doi.org/10.1002/cjs.11548
Bouezmarni, Taoufik and Van Bellegem, Sebastien and Rabhi, Yassir (2020) Nonparametric Beta Kernel Estimator for Long and Short Memory Time Series. The Canadian Journal of Statistics, 48 (3). pp. 582-595. DOI https://doi.org/10.1002/cjs.11548
Bouezmarni, Taoufik and Van Bellegem, Sebastien and Rabhi, Yassir (2020) Nonparametric Beta Kernel Estimator for Long and Short Memory Time Series. The Canadian Journal of Statistics, 48 (3). pp. 582-595. DOI https://doi.org/10.1002/cjs.11548
Abstract
In this article we introduces a nonparametric estimator of the spectral density by smoothing the periodogram using beta kernel density. The estimator is proved to be bounded for short memory data and diverges at the origin for long memory data. The convergence in probability of the relative error and Monte Carlo simulations show that the proposed estimator automatically adapts to the long‐ and the short‐range dependency of the process. A cross‐validation procedure is studied in order to select the nuisance parameter of the estimator. Illustrations on historical as well as most recent returns and absolute returns of the S&P500 index show the performance of the beta kernel estimator.
Item Type: | Article |
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Uncontrolled Keywords: | Statistics & Probability; Beta kernel smoothing; cross-validation; long range dependence; nonparametric estimation; periodogram; short memor; spectral density |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 19 Aug 2020 15:38 |
Last Modified: | 30 Oct 2024 16:18 |
URI: | http://repository.essex.ac.uk/id/eprint/27339 |
Available files
Filename: CJS-18-0019.pdf