Bootstrap Inference for Garch Models by the Least Absolute Deviation Estimation

2019 ◽  
Vol 41 (1) ◽  
pp. 21-40
Author(s):  
Qianqian Zhu ◽  
Ruochen Zeng ◽  
Guodong Li
Keyword(s):  
Garch Models ◽  
Least Absolute Deviation ◽  
Absolute Deviation ◽  
Least Absolute Deviation Estimation ◽  
Bootstrap Inference

scholarly journals LEAST ABSOLUTE DEVIATION ESTIMATION FOR UNIT ROOT PROCESSES WITH GARCH ERRORS

2009 ◽  
Vol 25 (5) ◽  
pp. 1208-1227 ◽  
Author(s):  
Guodong Li ◽  
Wai Keung Li
Keyword(s):  
Unit Root ◽  
Asymptotic Properties ◽  
Maximum Likelihood Estimators ◽  
Unit Root Tests ◽  
Order Moment ◽  
Least Absolute Deviation ◽  
Absolute Deviation ◽  
Least Absolute Deviation Estimation ◽  
Heavy Tailed ◽  
Quasi Maximum Likelihood

This paper considers a local least absolute deviation estimation for unit root processes with generalized autoregressive conditional heteroskedastic (GARCH) errors and derives its asymptotic properties under only finite second-order moment for both errors and innovations. When the innovations are symmetrically distributed, the asymptotic distribution of the estimated unit root is shown to be a functional of a bivariate Brownian motion, and then two unit root tests are derived. The simulation results demonstrate that the tests outperform those based on the Gaussian quasi maximum likelihood estimators with heavy-tailed innovations and those based on the simple least absolute deviation estimators.

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