Wavelet-based estimation of long-memory parameter in stochastic volatility models using a robust log-periodogram
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866929734385926144 |
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| author | N'Daam, Manganaw Kpanzou, Tchilabalo Abozou Katchekpele, Edoh |
| author_facet | N'Daam, Manganaw Kpanzou, Tchilabalo Abozou Katchekpele, Edoh |
| contents | In this paper, we propose a novel method for estimating the long-memory parameter in time series. By combining the multi-resolution framework of wavelets with the robustness of the Least Absolute Deviations (LAD) criterion, we introduce a periodogram providing a robust alternative to classical methods in the presence of non-Gaussian noise. Incorporating this periodogram into a log-periodogram regression, we develop a new estimator. Simulation studies demonstrate that our estimator outperforms the Geweke and Porter-Hudak (GPH) and Wavelet-Based Log-Periodogram (WBLP) estimators, particularly in terms of mean squared error, across various sample sizes and parameter configurations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_20101 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Wavelet-based estimation of long-memory parameter in stochastic volatility models using a robust log-periodogram N'Daam, Manganaw Kpanzou, Tchilabalo Abozou Katchekpele, Edoh Methodology 62M10, 62J05 In this paper, we propose a novel method for estimating the long-memory parameter in time series. By combining the multi-resolution framework of wavelets with the robustness of the Least Absolute Deviations (LAD) criterion, we introduce a periodogram providing a robust alternative to classical methods in the presence of non-Gaussian noise. Incorporating this periodogram into a log-periodogram regression, we develop a new estimator. Simulation studies demonstrate that our estimator outperforms the Geweke and Porter-Hudak (GPH) and Wavelet-Based Log-Periodogram (WBLP) estimators, particularly in terms of mean squared error, across various sample sizes and parameter configurations. |
| title | Wavelet-based estimation of long-memory parameter in stochastic volatility models using a robust log-periodogram |
| topic | Methodology 62M10, 62J05 |
| url | https://arxiv.org/abs/2502.20101 |