LAD Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities

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.

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Year of publication:	2009
Authors:	Cho, Jin Seo ; Chirok-Han ; Phillips, Peter C. B.
Institutions:	Institute of Economic Research, Korea University
Subject:	Asymptotic leptokurtosis \| Convex function \| Infinite density \| Least absolute deviations \| Median \| Weak convergence

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Extent:	application/pdf
Series:	Discussion Paper Series.
Type of publication:	Book / Working Paper
Language:	English
Notes:	Number 0917 12 pages
Classification:	C12 - Hypothesis Testing ; G11 - Portfolio Choice
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10008501957