Estimation spectrale avec mémoire longue et hétéroscédasticité conditionnelle

Translated title of the contribution: Spectral estimatioin with long memory conditional heteroscedasticity

Research output: Contribution to journalArticlepeer-review


Semiparametric spectral methods are valuable in that they yield inference on time series under very broad assumptions. This contribution analyzes the averaged periodogram statistic in the framework of a generalized linear process with (possibly long memory) conditional heteroscedasticity in the innovations. It is shown that the averaged periodogram statistic is appropriate for asymptotically normal estimation of the spectrum of a weakly dependent process at frequency zero and for consistent estimation of long memory and stationary cointegration in strongly dependent processes.

Translated title of the contributionSpectral estimatioin with long memory conditional heteroscedasticity
Original languageFrench
Pages (from-to)811-814
Number of pages4
JournalComptes Rendus de l'Academie des Sciences - Series I: Mathematics
Issue number9
StatePublished - 1999

All Science Journal Classification (ASJC) codes

  • General Mathematics


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