LAD asymptotics under conditional heteroskedasticity with possibly infinite error densities

Jin Seo Cho, Chirok Han, Peter C B Phillips

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Least absolute deviations (LAD) estimation of linear time series models is considered under conditional heteroskedasticity and serial correlation. The limit theory of the LAD estimator is obtained without assuming the finite density condition for the errors that is required in standard LAD asymptotics. The results are particularly useful in application of LAD estimation to financial time series data.

Original languageEnglish
Pages (from-to)953-962
Number of pages10
JournalEconometric Theory
Volume26
Issue number3
DOIs
Publication statusPublished - 2010 Jun 1

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time series
Deviation
Conditional heteroskedasticity

ASJC Scopus subject areas

  • Economics and Econometrics
  • Social Sciences (miscellaneous)

Cite this

LAD asymptotics under conditional heteroskedasticity with possibly infinite error densities. / Cho, Jin Seo; Han, Chirok; Phillips, Peter C B.

In: Econometric Theory, Vol. 26, No. 3, 01.06.2010, p. 953-962.

Research output: Contribution to journalArticle

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