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Estimation of the location and exponent of the spectral singularity of a long memory process

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  • Javier Hidalgo
  • Philippe Soulier

Abstract

. We consider the estimation of the location of the pole and memory parameter ω0 and d of a covariance stationary process with spectral density We investigate optimal rates of convergence for the estimators of ω0 and d, and the consequence that the lack of knowledge of ω0 has on the estimation of the memory parameter d. We present estimators which achieve the optimal rates. A small Monte‐Carlo study is included to illustrate the finite sample performance of our estimators.

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  • Javier Hidalgo & Philippe Soulier, 2004. "Estimation of the location and exponent of the spectral singularity of a long memory process," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(1), pages 55-81, January.
    • Handle: RePEc:bla:jtsera:v:25:y:2004:i:1:p:55-81
    DOI: 10.1111/j.1467-9892.2004.00337.x
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    7. Liudas Giraitis & Javier Hidalgo & Peter M Robinson, 2001. "Gaussian Estimation of Parametric Spectral Density with Unknown Pole," STICERD - Econometrics Paper Series 424, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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    Cited by:

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    3. del Barrio Castro, Tomás & Rachinger, Heiko, 2021. "Aggregation of Seasonal Long-Memory Processes," Econometrics and Statistics, Elsevier, vol. 17(C), pages 95-106.
    4. Asai, Manabu & McAleer, Michael & Peiris, Shelton, 2020. "Realized stochastic volatility models with generalized Gegenbauer long memory," Econometrics and Statistics, Elsevier, vol. 16(C), pages 42-54.
    5. Asai Manabu & Peiris Shelton & McAleer Michael & Allen David E., 2020. "Cointegrated Dynamics for a Generalized Long Memory Process: Application to Interest Rates," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-18, January.
    6. Beaumont, Paul & Smallwood, Aaron, 2019. "Inference for likelihood-based estimators of generalized long-memory processes," MPRA Paper 96313, University Library of Munich, Germany.
    7. Javier Hualde & Morten {O}rregaard Nielsen, 2022. "Fractional integration and cointegration," Papers 2211.10235, arXiv.org.
    8. Leschinski, Christian & Sibbertsen, Philipp, 2019. "Model order selection in periodic long memory models," Econometrics and Statistics, Elsevier, vol. 9(C), pages 78-94.
    9. J. Arteche & C. Velasco, 2005. "Trimming and Tapering Semi‐Parametric Estimates in Asymmetric Long Memory Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(4), pages 581-611, July.
    10. Masaki Narukawa, 2016. "Semiparametric Whittle estimation of a cyclical long-memory time series based on generalised exponential models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(2), pages 272-295, June.
    11. Asai, M. & Peiris, S. & McAleer, M.J. & Allen, D.E., 2018. "Cointegrated Dynamics for A Generalized Long Memory Process," Econometric Institute Research Papers EI 2018-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Leschinski, Christian & Sibbertsen, Philipp, 2014. "Model Order Selection in Seasonal/Cyclical Long Memory Models," Hannover Economic Papers (HEP) dp-535, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    13. M. Shelton Peiris & Manabu Asai, 2016. "Generalized Fractional Processes with Long Memory and Time Dependent Volatility Revisited," Econometrics, MDPI, vol. 4(3), pages 1-21, September.
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    15. Ould Haye, Mohamedou & Philippe, Anne, 2011. "Marginal density estimation for linear processes with cyclical long memory," Statistics & Probability Letters, Elsevier, vol. 81(9), pages 1354-1364, September.
    16. Richard Hunt & Shelton Peiris & Neville Weber, 2022. "Estimation methods for stationary Gegenbauer processes," Statistical Papers, Springer, vol. 63(6), pages 1707-1741, December.

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