On regression-based tests for persistence in logarithmic volatility models
Building on the work of Pantula (1986), this paper discusses how the hypothesis of conditional variance nonstationarity in the logarithmic family of generalized autoregressive conditional heteroskedasticity (GARCH) and stochastic volatility processes may be tested using regression-based tests. The latter are easy to implement, have well-defined large-sample distributions, and are less sensitive to structural changes than tests based on the quasimaximum likelihood estimator.
Volume (Year): 18 (1999)
Issue (Month): 4 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/LECR20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/LECR20|
When requesting a correction, please mention this item's handle: RePEc:taf:emetrv:v:18:y:1999:i:4:p:441-448. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()
If references are entirely missing, you can add them using this form.