Testing for Conditional Heteroscedasticity: Some Monte Carlo Results
Publication Type
Journal Article
Publication Date
1997
Abstract
For the purpose of testing the adequacy of an ARCH/GARCH model after one has been fitted to the data, many researchers use the Box-Pierce statistic as applied to the squared standardized residuals. Recently, Li and Mark (1994) argued that this procedure may be misleading as the asymptotic distribution of the statistic does not converge to a χ2 distribution. They derived the asymptotic distribution of the correlation coefficients of the squared standardized residuals and proposed some diagnostic tests for the ARCH/GARCH models. In this paper we report some Monte Carlo results for the finite sample performance of their tests and some other commonly used diagnostics.
Discipline
Economics
Research Areas
Econometrics
Publication
Journal of Statistical Computation and Simulation
Volume
58
First Page
237
Last Page
253
ISSN
0094-9655
Identifier
10.1080/00949659708811833
Publisher
Taylor and Francis
Citation
TSE, Yiu Kuen and Zuo, X. L..
Testing for Conditional Heteroscedasticity: Some Monte Carlo Results. (1997). Journal of Statistical Computation and Simulation. 58, 237-253.
Available at: https://ink.library.smu.edu.sg/soe_research/136
Additional URL
https://doi.org/10.1080/00949659708811833