LAD asymptotics under conditional heteroskedasticity with possibly infinite error densities
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.
asymptotic leptokurtosis, convex function, infinite density, least absolute deviations, median, weak convergence
953-962
Cho, Jin Seo
73c54d86-de50-44c7-8d1f-afbfab67bfc1
Han, Chirok
acedb9ff-f19b-4313-aa72-a69cf89b4fc6
Phillips, Peter C.B.
f67573a4-fc30-484c-ad74-4bbc797d7243
Cho, Jin Seo
73c54d86-de50-44c7-8d1f-afbfab67bfc1
Han, Chirok
acedb9ff-f19b-4313-aa72-a69cf89b4fc6
Phillips, Peter C.B.
f67573a4-fc30-484c-ad74-4bbc797d7243
Cho, Jin Seo, Han, Chirok and Phillips, Peter C.B.
(2010)
LAD asymptotics under conditional heteroskedasticity with possibly infinite error densities.
Econometric Theory, 26, .
(doi:10.1017/S0266466609990703).
(In Press)
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.
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Accepted/In Press date: 2010
Keywords:
asymptotic leptokurtosis, convex function, infinite density, least absolute deviations, median, weak convergence
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Local EPrints ID: 157283
URI: http://eprints.soton.ac.uk/id/eprint/157283
PURE UUID: 354ecd5a-0681-482f-8be1-ac6d2958a5f3
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Date deposited: 04 Jun 2010 11:41
Last modified: 14 Mar 2024 01:46
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Author:
Jin Seo Cho
Author:
Chirok Han
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