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Wavelet based Estimation of Time- Varying Long Memory Model with Nonlinear Fractional Integration Parameter

  • Heni Boubaker
  • Nadia Sghaier

In this paper, we propose a time-varying long memory model where the fractional integration parameter varies nonlinearly according to Smooth Transition Regressive (STR) model. To estimate the fractional integration parameter, we suggest a new estimation method based on wavelet approach. In particular, we consider the instan- taneous least squares estimator (ILSE). We conduct some simulation experiments and provide an empirical application to modeling the dynamics of volatilities of some fi- nancial time series. The obtained results show that the model proposed offers an interesting framework to describe time-varying long range dependence of volatilities and provide evidence of regime change in persistence to shocks.

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Paper provided by Department of Research, Ipag Business School in its series Working Papers with number 2014-284.

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Length: pages
Date of creation: 29 Apr 2014
Date of revision:
Handle: RePEc:ipg:wpaper:2014-284
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  15. Alfarano, Simone & Lux, Thomas, 2006. "A minimal noise trader model with realistic time series properties," Economics Working Papers 2006,11, Christian-Albrechts-University of Kiel, Department of Economics.
  16. Gilles DUFRENOT & Dominique GUEGAN & Anne PEGUIN-FEISSOLLE, 2003. "A SETAR model with long-memory dynamics," Econometrics 0309002, EconWPA.
  17. Andersen, Torben G & Bollerslev, Tim, 1997. " Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July.
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