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Time–frequency varying estimations: comparison of discrete and continuous wavelets in the market line framework

  • Roman MestreEmail author
  • Michel Terraza
Original Article
  • 2 Downloads

Abstract

This paper focus on comparison between three wavelets methodologies to estimate a time–frequency varying parameter. In the discrete case, we oppose the intuitive application of the rolling regression on wavelets frequency bands to the time–frequency rolling window. We compare if we have to use the time rolling window directly on the wavelet’s frequency bands or apply the time–frequency rolling window on the series realizing the wavelet decomposition at each step of the process. A time–frequency varying estimator by continuous wavelets is also considerate in the comparison. Our objective is to show that the time–frequency rolling window and the Continuous estimates are more suitable than the intuitive way. We use in first time simulated data and also the daily returns of AXA and the CAC 40 index from 2005 to 2015 as empirical application. We show that the differences between discrete methods are more important at low-frequencies. Moreover, the continuous time–frequency Betas are closer to the time–frequency windows estimates.

Keywords

Time–frequency rolling regression Wavelets Time–frequency Betas CWT MODWT 

JEL Classification

G00 G11 G12 C29 C18 C49 

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Copyright information

© Institute for Development and Research in Banking Technology 2019

Authors and Affiliations

  1. 1.MRE Université de Montpellier, UFR d’économie Avenue Raymond DugrandMontpellier cedex 2France

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