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:	2009-06
Authors:	Cho, Jin Seo ; Han, Chirok ; Phillips, Peter C.B.
Institutions:	Cowles Foundation for Research in Economics, Yale University
Subject:	Asymptotic leptokurtosis \| Convex function \| Infinite density \| Least absolute deviations \| Median \| Weak convergence

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Extent:	application/pdf
Series:	Cowles Foundation Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	Published in Econometric Theory (2010), 26(3): 953-962 The price is None Number 1703 10 pages
Classification:	C12 - Hypothesis Testing ; G11 - Portfolio Choice
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10004998317