Modelling conditional heteroskedasticity: Application to the "IBEX-35" stock-return index
This paper compares alternative time-varying volatility models for daily stock-returns using data from Spanish equity index IBEX-35. Specifically, we estimate a parametric family of models of generalized autoregressive heteroskedasticity (which nests the most popular symmetric and asymmetric GARCH models), a semiparametric GARCH model, the generalized quadratic ARCH model, the stochastic volatility model, the Poisson Jump Diffusion model and, finally, a nonparametric model. Those models which use conditional standard deviation (specifically, TGARCH and AGARCH models) produce better fits than all other GARCH models. We also compare the within sample predictive power of all models using a standard efficiency test. Our results show that the asymmetric behaviour of responses is a statistically significant characteristic of these data. Moreover, we observe that specifications with a distribution which allows for fatter tails than a normal distribution do not necessarily outperform specifications with a normal distribution.
Volume (Year): 1 (1999)
Issue (Month): 3 ()
|Contact details of provider:|| Web page: http://www.springer.com|
Postal:Universidad del País Vasco; DFAE II; Avenida Lehendakari Aguirre, 83; 48015 Bilbao; Spain
Phone: +34 94 6013783
Fax: + 34 94 6013774
Web page: http://spaneconrev.org/
More information through EDIRC
|Order Information:||Web: http://www.springer.com/economics/journal/10108?detailsPage=societies|
When requesting a correction, please mention this item's handle: RePEc:spr:specre:v:1:y:1999:i:3:p:215-238. 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: (Sonal Shukla)or (Rebekah McClure)
If references are entirely missing, you can add them using this form.