LAD ASYMPTOTICS UNDER CONDITIONAL HETEROSKEDASTICITY WITH POSSIBLY INFINITE ERROR DENSITIES

Jin Seo Cho (), Chirok Han and Peter Phillips

Econometric Theory, 2010, vol. 26, issue 3, 953-962

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.

Date: 2010
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Working Paper: LAD Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities (2009)
Working Paper: LAD Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities (2009)
Working Paper: LAD Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities (2009)
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