Nonlinear Measures of Persistence in Time Series

  • Gilles Dufrénot
  • Valérie Mignon


As we noted in the introduction of chapter 2, the study of the stationarity of stochastic processes leads to various interpretations. Usual approaches consider the properties of ergodicity, trend-stationary models (either deterministic or stochastic), and semi-stationarity (for processes that are locally nonstationary although globally stationary). However, as shown in the preceding chapter, some of the commonly used approaches perform poorly when used on nonlinear processes. The need to find other definitions of stationarity and nonstationarity is motivated by at least two considerations.


White Noise Stock Return Empirical Distribution Nonlinear Time Series White Noise Process 
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Copyright information

© Springer Science+Business Media Dordrecht 2002

Authors and Affiliations

  • Gilles Dufrénot
    • 1
    • 2
  • Valérie Mignon
    • 3
  1. 1.ERUDITEUniversity of Paris 12France
  2. 2.GREQUAM-CNRSUniversity of MarseilleFrance
  3. 3.MODEMUniversity of Paris 10France

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