COWLES FOUNDATION FOR RESEARCH IN ECONOMICS
AT YALE UNIVERSITY

Box 208281
New Haven, CT 06520-8281

COWLES FOUNDATION DISCUSSION PAPER NO. 1703

LAD Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities

Jin Seo Cho, Chirok Han, and Peter C.B. Phillips

June 2009

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

JEL Classifications: C12, G11