Wavelet Analysis of Nonlinear Long-Range Dependent Processes. Applications to Financial Time Series

Gilles Teyssière () and Patrice Abry ()
Additional contact information
Gilles Teyssière: Université Paris 1
Patrice Abry: École Normale Supérieure de Lyon, CNRS UMR 5672

A chapter in Long Memory in Economics, 2007, pp 173-238 from Springer

Abstract: Summary We present and study the performance of the semiparametric wavelet estimator for the long-memory parameter devised by [Veitch and Abry (1999)]. We compare this estimator with two semiparametric estimators in the spectral domain, the local Whittle (LW) estimator developed by [Robinson (1995a)] and the “log-periodogram” (LP) estimator by [Geweke and Porter-Hudak (1983)]. The wavelet estimator performs well for a wide range of nonlinear long-memory processes in the conditional mean and the conditional variance, and is reliable for discriminating between change-points and long-range dependence in volatility. We also address the issue of selection of the range of octaves used as regressors by the weighted least squares estimator. We will see that using the feasible optimal bandwidths for either the LW and LP estimators, respectively studied by [Henry and Robinson (1996) and [Henry (2001)], is a useful rule of thumb for selecting the lowest octave. We apply the wavelet estimator to volatility series of high frequency (intra-day) Foreign Exchange (FX) rates, and to the volatility and volume of stocks of the Dow Jones Industrial Average Index.

Keywords: Root Mean Square Error; Wavelet Analysis; Trading Volume; Nonlinear Transformation; Optimal Bandwidth (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-34625-8_7

Ordering information: This item can be ordered from
http://www.springer.com/9783540346258

DOI: 10.1007/978-3-540-34625-8_7

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().