LAD Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities

Jin Seo Cho, Chirok Han () and Peter C. B. Phillips ()
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Jin Seo Cho: Dept. of Economics, Korea University

No 1703, Cowles Foundation Discussion Papers from Cowles Foundation, Yale University

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.

Keywords: Asymptotic leptokurtosis; Convex function; Infinite density; Least absolute deviations; Median; Weak convergence (search for similar items in EconPapers)
JEL-codes: C12 G11 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
Date: 2009-06
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