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Wavelet Method for Locally Stationary Seasonal Long Memory Processes

Author

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  • Dominique Guegan

    () (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics)

  • Zhiping Lu

    () (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, ECNU - East China Normal University [Shangaï])

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.

Suggested Citation

  • Dominique Guegan & Zhiping Lu, 2009. "Wavelet Method for Locally Stationary Seasonal Long Memory Processes," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00375531, HAL.
  • Handle: RePEc:hal:cesptp:halshs-00375531
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00375531
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    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.;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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