Wavelet Method for Locally Stationary Seasonal Long Memory Processes

Dominique Guegan () and Zhiping Lu ()
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Dominique Guegan: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Zhiping Lu: CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, ECNU - East China Normal University [Shangaï]

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Abstract: Long memory processes have been extensively studied over the past decades. When dealing with the financial and economic data, seasonality and time-varying long-range dependence can often be observed and thus some kind of non-stationarity can exist inside financial data sets. To take into account this kind of phenomena, we propose a new class of stochastic process : the locally stationary k-factor Gegenbauer process. We describe a procedure of estimating consistently the time-varying parameters by applying the discrete wavelet packet transform (DWPT). The robustness of the algorithm is investigated through simulation study. An application based on the error correction term of fractional cointegration analysis of the Nikkei Stock Average 225 index is proposed.

Keywords: Discrete wavelet packet transform; Gegenbauer process; Nikkei Stock Average 225 index; non-stationarity; ordinary least square estimation; Transformation d'ondelettes; processus Gegenbauer; non-stationnarité; Nikkei; méthode des moindres carrés. (search for similar items in EconPapers)
Date: 2009-03
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00375531v1
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Published in 2009

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Related works:
Working Paper: Wavelet method for locally stationary seasonal long memory processes (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:halshs-00375531

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