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.
Cambridge University Press (CUP): HSS Journals
Cho, J. S.; Han, C.; and Peter C. B. PHILLIPS.
Lad Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities. (2010). Econometric Theory. 26, (3), 953-962. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1819
This document is currently not available here.