LAD Asymptotics under Conditional Heteroskedasticity with Possibly Infinite Error Densities

• Main Authors: CHO, Jin Seo, HAN, Chirok, Peter C. B. PHILLIPS
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2010
• Subjects: Asymptotic leptokurtosis; Convex function; Infinite density; Least absolute deviations; Median; Weak convergence; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/1819; https://ink.library.smu.edu.sg/context/soe_research/article/2818/viewcontent/LAD_Asymptotics_sv.pdf
• Institution: Singapore Management University

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.