Random coefficient volatility models
In financial modeling, the moments of the observed process, the kurtosis and the moments of the conditional volatility play important roles. They are very important in model identification and in forecasting the volatility (see Thavaneswaran et al. [(2005b). Forecasting volatility. Statist. Probab. Lett. 75, 1-10.]). This paper introduces random coefficient GARCH models including the class random coefficient GARCH (RC-GARCH) models and derive their higher order moments and kurtosis.
Year of publication: |
2008
|
---|---|
Authors: | Thavaneswaran, A. ; Peiris, S. ; Appadoo, S. |
Published in: |
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 78.2008, 6, p. 582-593
|
Publisher: |
Elsevier |
Keywords: | Stochastic volatility Random coefficient Kurtosis Sign-switching |
Saved in:
Saved in favorites
Similar items by person
-
Thavaneswaran, A., (2005)
-
A Note on the Filtering for Some Time Series Models
Peiris, S., (2004)
-
Applications of recursive estimation methods in statistical process control
Peiris, S., (2003)
- More ...