Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0378-4754(03)00125-3
Title: Diagnostics for conditional heteroscedasticity models: Some simulation results
Authors: Tsui, A.K. 
Keywords: GARCH models
Residual-based diagnostics
Simulation
Issue Date: 2004
Citation: Tsui, A.K. (2004). Diagnostics for conditional heteroscedasticity models: Some simulation results. Mathematics and Computers in Simulation 64 (1) : 113-119. ScholarBank@NUS Repository. https://doi.org/10.1016/S0378-4754(03)00125-3
Abstract: In this paper, we study the size and power of various diagnostic statistics for univariate conditional heteroscedasticity models. These test statistics include the residual-based tests recently derived by Tse, Li and Mak, and Wooldridge, respectively. Monte-Carlo experiments with 1000 replications are conducted to generate conditional variances which follow the autoregressive conditional heteroscedasticity (ARCH)/GARCH processes. We use quasi-maximum likelihood estimation (MLE) method to obtain estimates of parameters under different ARCH/ generalized ARCH (GARCH) models. It is found that the Tse and Li-Mak diagnostics are more powerful.©2003 IMACS. Published by Elsevier B.V. All rights reserved.
Source Title: Mathematics and Computers in Simulation
URI: http://scholarbank.nus.edu.sg/handle/10635/19943
ISSN: 03784754
DOI: 10.1016/S0378-4754(03)00125-3
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

3
checked on Jul 14, 2018

WEB OF SCIENCETM
Citations

2
checked on Jun 18, 2018

Page view(s)

199
checked on Mar 12, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.