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Wavelet method for locally stationary seasonal long memory processes

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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

Suggested Citation

  • Dominique Guegan & Zhiping Lu, 2009. "Wavelet method for locally stationary seasonal long memory processes," Documents de travail du Centre d'Economie de la Sorbonne 09015, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    • Handle: RePEc:mse:cesdoc:09015
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    Cited by:

    1. Souhir, Ben Amor & Heni, Boubaker & Lotfi, Belkacem, 2019. "Price risk and hedging strategies in Nord Pool electricity market evidence with sector indexes," Energy Economics, Elsevier, vol. 80(C), pages 635-655.
    2. Souhir Ben Amor & Heni Boubaker & Lotfi Belkacem, 2022. "Predictive Accuracy of a Hybrid Generalized Long Memory Model for Short Term Electricity Price Forecasting," Papers 2204.09568, arXiv.org.

    More about this item

    Keywords

    Discrete wavelet packet transform; Gegenbauer process; Nikkei Stock Average 225 index; non-stationarity; ordinary least square estimation;
    All these keywords.

    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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